Method and device for producing common products based on remote sensing data of Geology-1 satellite

Abstract

This application discloses a method and device for producing common products based on remote sensing data from the Geology-1 satellite, relating to the fields of remote sensing technology and ecological monitoring. The method comprises: acquiring multispectral remote sensing image data from the Geology-1 satellite; performing data extraction based on the multispectral remote sensing image data for a target product to be produced, obtaining reflectances of different wavebands corresponding to the target product to be produced; and producing the target product using a product production model corresponding to the target product to be produced based on each of the reflectances. The method of this application enables the automated production of a variety of common products in the ecological and geological fields, and is suitable for a wide range of application scenarios, including natural resource management, agriculture, environmental protection, and geological exploration.

Description

Technical Field

[0001] The present invention relates to the fields of remote sensing technology and ecological monitoring, and in particular to a method and device for producing common products based on remote sensing data of the Geology-1 satellite. Background Art

[0002] The application of remote sensing technology in ecological and geological monitoring, especially dynamic monitoring and high-frequency observations of large-scale environments, has become an important research direction. The multi-band characteristics of remote sensing satellites provide technical support for obtaining information on surface vegetation, water bodies, soil, geology, etc., and the production of common monitoring products in these fields requires not only multi-spectral data coverage, but also the diversity and accuracy of band selection and calculation methods. Currently, the multi-spectral data commonly used in ecological and geological monitoring mostly come from general-purpose remote sensing satellites. The product production methods are often not optimized for the specific spectral characteristics of the Geological Satellite No. 1, and there is a lack of a product system that is universal across multiple fields. This leads to inconsistent results in data processing and production in cross-theme remote sensing applications, and it is difficult to achieve multi-faceted and simultaneous acquisition of ecological and geological information. Summary of the Invention

[0003] In view of this, the present invention provides a common product production method and device based on the remote sensing data of the Geology-1 satellite. The main purpose is to solve the problem that in the current cross-theme remote sensing applications, the results of data processing and production are inconsistent, and it is difficult to achieve multi-faceted simultaneous acquisition of ecological and geological information.

[0004] To solve the above problems, this application provides a method for producing common products based on remote sensing data from the Geology-1 satellite, including:

[0005] Acquire multispectral remote sensing image data from the Geology-1 satellite;

[0006] For a target product to be produced, data extraction is performed based on the multispectral remote sensing image data to obtain reflectances of different bands corresponding to the target product to be produced;

[0007] Based on the reflectivity, a product production model corresponding to the target product to be produced is used to produce the product to obtain the target product;

[0008] The step of producing a target product by adopting a product production model corresponding to the target product to be produced based on each of the reflectivities to obtain the target product specifically includes:

[0009] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is an alunite mineral product, based on Carry out product production;

[0010] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a calcite mineral product, based on Carry out product production;

[0011] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a clay alteration index product, based on Carry out product production;

[0012] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a dolomite index product, based on Carry out product production;

[0013] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is an epidote index product, a chlorite index product, and an amphibole index product, based on Carry out product production;

[0014] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a magnesite index product, based on Carry out product production;

[0015] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a carbonate abundance index product, based on Carry out product production;

[0016] in, 、 、 、 、 as well as They are all shortwave infrared spectrum bands of the Address-1 satellite, and the band reflectivities are 1630-1670nm, 2130-2170nm, 2190-2230nm, 2250-2290nm, 2320-2360nm and 2400-2480nm respectively.

[0017] To solve the above problems, this application provides a common product production device based on the remote sensing data of the Geology-1 satellite, including:

[0018] Acquisition module, used to obtain multispectral remote sensing image data of the Geology-1 satellite;

[0019] A data extraction module is used to extract data based on the multispectral remote sensing image data for a target product to be produced, and obtain reflectances of different bands corresponding to the target product to be produced;

[0020] A product production module is configured to produce a product based on each of the reflectivities using a product production model corresponding to the target product to be produced to obtain a target product; the process of producing a product based on each of the reflectivities using a product production model corresponding to the target product to be produced to obtain a target product specifically includes:

[0021] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is an alunite mineral product, based on Carry out product production;

[0022] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a calcite mineral product, based on Carry out product production;

[0023] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a clay alteration index product, based on Carry out product production;

[0024] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a dolomite index product, based on Carry out product production;

[0025] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is an epidote index product, a chlorite index product, and an amphibole index product, based on Carry out product production;

[0026] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a magnesite index product, based on Carry out product production;

[0027] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a carbonate abundance index product, based on Carry out product production;

[0028] in, 、 、 、 、 as well as They are all shortwave infrared spectrum bands of the Address-1 satellite, and the band reflectivities are 1630-1670nm, 2130-2170nm, 2190-2230nm, 2250-2290nm, 2320-2360nm and 2400-2480nm respectively.

[0029] The beneficial effects of this application are as follows: This application obtains multispectral remote sensing image data from the Geology-1 satellite; extracts data based on the multispectral remote sensing image data for a target product to be produced, obtaining the reflectance of different bands corresponding to the target product; and then produces the target product using a product production model corresponding to the target product based on each reflectance. This achieves automated production of a variety of common products in the ecological and geological fields, and is suitable for a wide range of application scenarios, including natural resource management, agriculture, environmental protection, and geological exploration.

[0030] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are specifically listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present invention. The same reference symbols are used throughout the drawings to represent the same components. In the drawings:

[0032] Figure 1 A schematic diagram of a process for producing a common product based on remote sensing data from the Geology-1 satellite provided in an embodiment of the present application is shown;

[0033] Figure 2 A structural block diagram of a common product production device based on remote sensing data of the Geology-1 satellite provided in another embodiment of the present application is shown. DETAILED DESCRIPTION

[0034] Various aspects and features of the present application are described herein with reference to the accompanying drawings.

[0035] It should be understood that various modifications may be made to the embodiments of the present application. Therefore, the above description should not be considered as limiting, but merely as an example of an embodiment. Other modifications within the scope and spirit of the present application will occur to those skilled in the art.

[0036] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments of the present application and, together with the general description of the present application given above and the detailed description of the embodiments given below, serve to explain the principles of the present application.

[0037] These and other characteristics of the present application will become apparent from the following description of a preferred form of embodiment given as a non-limiting example with reference to the accompanying drawings.

[0038] It should also be understood that although the present application has been described with reference to certain specific examples, those skilled in the art will readily be able to implement many other equivalent forms of the present application.

[0039] The above and other aspects, features and advantages of the present application will become more apparent from the following detailed description when taken in conjunction with the accompanying drawings.

[0040] Specific embodiments of the present application will be described hereinafter with reference to the accompanying drawings; however, it should be understood that the embodiments described are merely examples of the present application and may be implemented in a variety of ways. Familiar and / or repetitive functions and structures are not described in detail to avoid obscuring the present application with unnecessary or redundant details. Therefore, the specific structural and functional details described herein are not intended to be limiting, but rather serve merely as a basis and representative basis for the claims to teach those skilled in the art to variously utilize the present application with substantially any suitable detailed structure.

[0041] This specification may use the phrases "in one embodiment," "in another embodiment," "in a further embodiment," or "in other embodiments," which may all refer to one or more of the same or different embodiments according to the present application.

[0042] The present application embodiment provides a method for producing a common product based on remote sensing data of the Geology-1 satellite, such as Figure 1 Shown, including:

[0043] Step S101: Acquire multispectral remote sensing image data from the Geology-1 satellite;

[0044] During the implementation of this step, the multispectral remote sensing imagery from the Geology-1 satellite covers a wide range of spectrum, including visible-near-infrared and shortwave infrared, specifically designed to meet the diverse monitoring needs of the ecological and geological fields. Its key bands include the visible-near-infrared spectrum (410nm-1020nm), which covers 16 bands with a resolution of 14 meters and is primarily used for water monitoring, vegetation health, and soil moisture assessment. The characteristics of the visible-near-infrared spectrum from the Geology-1 satellite are shown in Table 1:

[0045]

[0046] Short-wave infrared spectrum (1180nm~2480nm): with a resolution of 30 meters, including 10 bands, which can be used for geological monitoring such as mineral and lithology identification and heavy metal pollution. The characteristics of the short-wave infrared spectrum of the Geology-1 satellite are shown in Table 2:

[0047]

[0048] Step S102: performing data extraction on the target product to be produced based on the multispectral remote sensing image data to obtain reflectances of different wavebands corresponding to the target product to be produced;

[0049] During the specific implementation of this step, the categories of the target products to be produced include: vegetation detection product category, water and ice and snow detection product category and geological detection product category; when the category of the target products to be produced is vegetation detection product category, the target products to be produced are normalized difference vegetation index product, red edge chlorophyll vegetation index product, normalized difference red edge vegetation index, improved soil adjusted vegetation index product, green normalized difference vegetation index product, soil conditioned vegetation index product, optimized soil conditioned vegetation index product, atmospheric resistance vegetation index product, enhanced vegetation index product, visible atmospheric resistance index product, standardized combustion rate product, structure insensitive pigment vegetation index product, green chlorophyll vegetation index product, difference vegetation index product and ratio vegetation index product. One or more of the following; when the category of the target products to be produced is water and ice and snow detection product category, the target products to be produced are One or more of the normalized difference water index product, the turbid water index product, the cyanobacteria and macrophyte index product, the phytoplankton index product and the normalized difference snow index product; when the category of the target product to be produced is the geological exploration product category, the target product to be produced is one or more of the ferrous-ferric distribution product, the iron oxide index product, the laterite product, the ferrous silicate index product, the silicate mineral product, the intermediate mud zone mineral product, the advanced mud zone mineral product, the alunite mineral product, the calcite mineral product, the clay alteration index product, the dolomite index product, the epidote index product, the chlorite index product, the hornblende index product, the magnesite index product, the carbonate abundance index product, the montmorillonite index product, the muscovite index product, the phenolic substance index product, the foliated alteration index product, the propyl metamorphic index product, the hydroxyl-containing alteration mineral index product and the kaolinite index product.

[0050] When the product category of the target product to be produced is a vegetation detection product category, the reflectivities of different bands corresponding to the target product to be produced include one or more of the blue band reflectivity, the first green band reflectivity, the first red light band reflectivity, the second red light band reflectivity, the first red edge band reflectivity, the first near-infrared band reflectivity and the first short-wave infrared band reflectivity; when the product category of the target product to be produced is a water and ice and snow detection product category, the reflectivities of different bands corresponding to the target product to be produced include the blue band reflectivity, the first green band reflectivity, the first red light band reflectivity, the first near-infrared band reflectivity and the first short-wave infrared band reflectivity. one or more of the reflectivities; when the product category of the target product to be produced is a geological exploration product category, the reflectivities of different bands corresponding to the target product to be produced include the second green band reflectivity, the first green band reflectivity, the yellow band reflectivity, the first red light band reflectivity, the second red light band reflectivity, the first near-infrared band reflectivity, the second near-infrared band reflectivity, the third near-infrared band reflectivity, the first short-wave infrared band reflectivity, the second short-wave infrared band reflectivity, the third short-wave infrared band reflectivity, the fourth short-wave infrared band reflectivity, the fifth short-wave infrared band reflectivity, the sixth short-wave infrared band reflectivity, and the seventh short-wave infrared band reflectivity.

[0051] When the category of the target product to be produced is a vegetation detection product category and the target product to be produced is a normalized difference vegetation index product, a red edge chlorophyll vegetation index product, an improved soil adjusted vegetation index product, a soil conditioned vegetation index product, an optimized soil conditioned vegetation index product, an enhanced vegetation index product, a difference vegetation index product and a ratio vegetation index product, the reflectance of different bands corresponding to the target product to be produced includes a first near-infrared band reflectance and a first red light band reflectance; when the category of the target product to be produced is a vegetation detection product category and the target product to be produced is a normalized difference red edge vegetation index product product, the reflectivities of different bands corresponding to the target product to be produced include the first near-infrared band reflectivity and the first red-edge band reflectivity; when the category of the target product to be produced is the vegetation detection product category and the target product to be produced is the green normalized difference vegetation index product, the reflectivities of different bands corresponding to the target product to be produced include the first near-infrared band reflectivity and the first green band reflectivity; when the category of the target product to be produced is the vegetation detection product category and the target product to be produced is the atmospheric resistance vegetation index product, the reflectivities of different bands corresponding to the target product to be produced include The first near-infrared band reflectivity, the first red light band reflectivity, and the blue band reflectivity; when the category of the target product to be produced is a vegetation detection product category and the target product to be produced is a visible atmospheric resistance index product, the reflectivities of different bands corresponding to the target product to be produced include the first green band reflectivity, the second red light band reflectivity, and the blue band reflectivity; when the category of the target product to be produced is a vegetation detection product category and the target product to be produced is a standardized combustion rate product, the reflectivities of different bands corresponding to the target product to be produced include the first near-infrared band reflectivity and The reflectivity of the first short-wave infrared band; when the category of the target product to be produced is the vegetation detection product category and the target product to be produced is the structure-insensitive pigment vegetation index product, the reflectivity of different bands corresponding to the target product to be produced includes the first near-infrared band reflectivity, the blue band reflectivity and the first red light band reflectivity; when the category of the target product to be produced is the vegetation detection product category and the target product to be produced is the green chlorophyll vegetation index product, the reflectivity of different bands corresponding to the target product to be produced includes the first near-infrared band reflectivity and the first green band reflectivity.

[0052] When the category of the target product to be produced is the category of water and ice and snow detection products and the target product to be produced is a normalized difference water index product, the reflectivities of the different bands corresponding to the target product to be produced include the first near-infrared band reflectivity and the first green band reflectivity; when the category of the target product to be produced is the category of water and ice and snow detection products and the target product to be produced is a turbid water index product, the reflectivities of the different bands corresponding to the target product to be produced include the first red light band reflectivity and the first short-wave infrared band reflectivity; when the category of the target product to be produced is the category of water and ice and snow detection products and the target product to be produced is a cyanobacteria and macrophyte index product, the reflectivities of the different bands corresponding to the target product to be produced include the first red light band reflectivity and the first short-wave infrared band reflectivity. The reflectivities of different bands include the reflectivity of the first green band, the reflectivity of the blue band, and the reflectivity of the first short-wave infrared band; when the category of the target product to be produced is the category of water body and ice and snow detection products and the target product to be produced is a phytoplankton index product, the reflectivities of different bands corresponding to the target product to be produced include the reflectivity of the first near-infrared band, the reflectivity of the first red light band, and the reflectivity of the first short-wave infrared band; when the category of the target product to be produced is the category of water body and ice and snow detection products and the target product to be produced is a normalized difference snow index product, the reflectivities of different bands corresponding to the target product to be produced include the reflectivity of the first green band and the reflectivity of the first short-wave infrared band.

[0053] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a ferrous-ferric distribution product, the reflectivities of the different bands corresponding to the target product to be produced include the first near-infrared band reflectivity, the second near-infrared band reflectivity, the third near-infrared band reflectivity and the second short-wave infrared band reflectivity or the first green band reflectivity, the second green band reflectivity, the yellow band reflectivity, the second red light band reflectivity and the first red light band reflectivity; when the category of the target product to be produced is a geological exploration product category and the target product to be produced is an iron oxide index product, the reflectivities of the different bands corresponding to the target product to be produced include the second near-infrared band reflectivity The reflectivity of the first near-infrared band, the reflectivity of the third near-infrared band, the reflectivity of the first near-infrared band, the reflectivity of the first short-wave infrared band and the reflectivity of the third short-wave infrared band; when the target product to be produced is a laterite belt product, the reflectivities of the different bands corresponding to the target product to be produced include the reflectivity of the first short-wave infrared band, the reflectivity of the third short-wave infrared band and the reflectivity of the second short-wave infrared band, or the reflectivity of the first green band and the reflectivity of the third short-wave infrared band; when the target product to be produced is a ferrous silicate index product, the reflectivities of the different bands corresponding to the target product to be produced include the reflectivity of the first short-wave infrared band, the reflectivity of the third short-wave infrared band and the reflectivity of the second short-wave infrared band The reflectivity of the outer band, or the reflectivity of the third short-wave infrared band and the reflectivity of the second short-wave infrared band; when the target product to be produced is a silicate mineral product, the reflectivity of the different bands corresponding to the target product to be produced includes the reflectivity of the fourth short-wave infrared band, the reflectivity of the fifth short-wave infrared band, the reflectivity of the sixth short-wave infrared band and the reflectivity of the seventh short-wave infrared band; when the target product to be produced is an intermediate mud zone mineral product, the reflectivity of the different bands corresponding to the target product to be produced includes the reflectivity of the second short-wave infrared band, the reflectivity of the fourth short-wave infrared band and the reflectivity of the fifth short-wave infrared band; when the target product to be produced is an intermediate mud zone mineral product, The reflectivities of different wavebands corresponding to the product to be produced include the reflectivity of the second short-wave infrared waveband, the reflectivity of the fourth short-wave infrared waveband, and the reflectivity of the fifth short-wave infrared waveband; when the target product to be produced is a high-grade mudstone mineral product, the reflectivities of different wavebands corresponding to the target product to be produced include the reflectivity of the first short-wave infrared waveband, the reflectivity of the third short-wave infrared waveband, the reflectivity of the second short-wave infrared waveband, and the reflectivity of the fourth short-wave infrared waveband; when the target product to be produced is an alunite mineral product, the reflectivities of different wavebands corresponding to the target product to be produced include the reflectivity of the second short-wave infrared waveband, the reflectivity of the fifth short-wave infrared waveband, and the reflectivity of the sixth short-wave infrared waveband;When the target product to be produced is a calcite mineral product, the reflectivities of the different bands corresponding to the target product to be produced include the reflectivity of the fourth short-wave infrared band, the reflectivity of the sixth short-wave infrared band, and the reflectivity of the seventh short-wave infrared band; when the target product to be produced is a clay alteration index product, the reflectivities of the different bands corresponding to the target product to be produced include the reflectivity of the first short-wave infrared band, the reflectivity of the second short-wave infrared band, and the reflectivity of the fourth short-wave infrared band; when the target product to be produced is a dolomite index product, the reflectivities of the different bands corresponding to the target product to be produced include the reflectivity of the fourth short-wave infrared band, the reflectivity of the fifth short-wave infrared band, and the reflectivity of the seventh short-wave infrared band. The reflectivity of the different wavebands corresponding to the target products to be produced include the reflectivity of the fourth short-wave infrared band, the reflectivity of the fifth short-wave infrared band, the reflectivity of the sixth short-wave infrared band, and the reflectivity of the seventh short-wave infrared band; when the target products to be produced are epidote index products, chlorite index products, and hornblende index products, the reflectivity of the different wavebands corresponding to the target products to be produced include the reflectivity of the fourth short-wave infrared band, the reflectivity of the fifth short-wave infrared band, and the reflectivity of the sixth short-wave infrared band; when the target products to be produced are magnesite index products, the reflectivity of the different wavebands corresponding to the target products to be produced include the reflectivity of the fourth short-wave infrared band, the reflectivity of the fifth short-wave infrared band, and the reflectivity of the sixth short-wave infrared band; When the target product to be produced is a salt abundance index product, the reflectivities of different bands corresponding to the target product to be produced include the reflectivity of the fourth short-wave infrared band, the reflectivity of the sixth short-wave infrared band, and the reflectivity of the seventh short-wave infrared band; when the target product to be produced is a montmorillonite index product, the reflectivities of different bands corresponding to the target product to be produced include the reflectivity of the third short-wave infrared band, the reflectivity of the fourth short-wave infrared band, and the reflectivity of the fifth short-wave infrared band; when the target product to be produced is a muscovite index product, the reflectivities of different bands corresponding to the target product to be produced include the reflectivity of the fourth short-wave infrared band and the reflectivity of the fifth short-wave infrared band; When the product to be produced is a phenolic substance index product, the reflectivities of the different bands corresponding to the target product to be produced include the reflectivity of the second short-wave infrared band and the reflectivity of the fourth short-wave infrared band; when the target product to be produced is a foliated alteration index product, the reflectivities of the different bands corresponding to the target product to be produced include the reflectivity of the second short-wave infrared band, the reflectivity of the fourth short-wave infrared band, and the reflectivity of the fifth short-wave infrared band; when the target product to be produced is a propyl deterioration index product, the reflectivities of the different bands corresponding to the target product to be produced include the reflectivity of the fifth short-wave infrared band, the reflectivity of the sixth short-wave infrared band, and the reflectivity of the seventh short-wave infrared band;When the target product to be produced is a hydroxyl-containing altered mineral index product, the reflectivities of the different wavebands corresponding to the target product to be produced include the reflectivity of the third short-wave infrared waveband, the reflectivity of the second short-wave infrared waveband, the reflectivity of the fourth short-wave infrared waveband, and the reflectivity of the fifth short-wave infrared waveband; when the target product to be produced is a kaolinite index product, the reflectivities of the different wavebands corresponding to the target product to be produced include the reflectivity of the third short-wave infrared waveband, the reflectivity of the second short-wave infrared waveband, the reflectivity of the fourth short-wave infrared waveband, the reflectivity of the fifth short-wave infrared waveband, and the reflectivity of the sixth short-wave infrared waveband.

[0054] Step S103: Based on the reflectivity, a product production model corresponding to the target product to be produced is used to produce the product to obtain the target product.

[0055] During the specific implementation of this step, when the category of the target product to be produced is the vegetation detection product category and the target product to be produced is the normalized difference vegetation index product NDVI, the product is produced using the normalized difference vegetation index product production model based on the first near-infrared band reflectance B14 and the first red light band reflectance B8 to obtain the normalized difference vegetation index product; the calculation mathematical formula of the normalized difference vegetation index product production model can be expressed as the following formula (1):

[0056] NDVI = (B14 – B8) / (B14 + B8) (1)

[0057] Among them, B14: reflectance in the first near-infrared band (840-860 nm), and B8: reflectance in the first red band (670-690 nm). The NDVI index can reflect the health and growth of vegetation.

[0058] When the category of the target product to be produced is a vegetation detection product category and the target product to be produced is a red-edge chlorophyll vegetation index product RECl, a red-edge chlorophyll vegetation index product production model is used to produce the product based on the first near-infrared band reflectivity B14 and the first red light band reflectivity B8 to obtain the red-edge chlorophyll vegetation index product; the mathematical expression of the red-edge chlorophyll vegetation index product production model can be expressed as the following formula (2):

[0059] RECI = (B14 / B8) – 1 (2)

[0060] B14 is the reflectance index in the first near-infrared band (840-860 nm), and B8 is the reflectance index in the first red band (670-690 nm). The RECI index responds to the chlorophyll content in nitrogen-nourished leaves. The RECI index indicates canopy photosynthetic activity and is most useful during active vegetation development but not during harvest season.

[0061] When the category of the target product to be produced is a vegetation detection product category and the target product to be produced is a normalized difference red edge vegetation index product NDRE, the product is produced using a normalized difference red edge vegetation index product production model based on the first near-infrared band reflectance B14 and the first red edge band reflectance B11 to obtain the normalized difference red edge vegetation index product; the mathematical expression of the normalized difference red edge vegetation index product production model can be expressed as the following formula (3):

[0062] NDRE = (B14–B11) / (B14 + B11) (3)

[0063] B14 is the reflectance of the first near-infrared band (840-860 nm), and B11 is the reflectance of the first red-edge band (740-750 nm). The NDRE index is suitable for high-density tree canopy cover.

[0064] When the category of the target product to be produced is a vegetation detection product category and the target product to be produced is a modified soil adjusted vegetation index product MSAVI, the product is produced using a modified soil adjusted vegetation index product production model based on the first near-infrared band reflectivity B14 and the first red light band reflectivity B8 to obtain the modified soil adjusted vegetation index product; the mathematical expression of the modified soil adjusted vegetation index product production model can be expressed as the following formula (4):

[0065] MSAVI = (2 *B14 + 1 – sqrt ((2 * B14 + 1)2 – 8 * (B14– B8))) / 2 (4)

[0066] B14: Reflectance in the first near-infrared band (840-860 nm), and B8: Reflectance in the first red band (670-690 nm). The MSAVI vegetation index is designed to mitigate the influence of soil on crop monitoring results. Therefore, it is suitable for situations where NDVI cannot provide accurate values, particularly where there is a high proportion of bare soil, sparse vegetation, or low chlorophyll content in plants. MSAVI is particularly useful at the beginning of the crop production season—when seedlings begin to grow.

[0067] When the target product to be produced is a vegetation detection product and is a green normalized difference vegetation index (GNDVI) product, a green normalized difference vegetation index (GNDVI) product production model is used to produce the product based on the first near-infrared band reflectance B14 and the first green band reflectance B5 to obtain the green normalized difference vegetation index product. The mathematical expression of the green normalized difference vegetation index product production model can be expressed as the following formula (5):

[0068] GNDVI = (B14 – B5) / (B14 + B5) (5)

[0069] Among them, B14: reflectivity of the first near-infrared band (840-860 nm), B5: reflectivity of the first green band (540-560 nm).

[0070] When the category of the target product to be produced is a vegetation detection product category and the target product to be produced is a soil-adjusted vegetation index product SAVI, the soil-adjusted vegetation index product production model is used to produce the product based on the first near-infrared band reflectivity B14 and the first red light band reflectivity B8 to obtain the soil-adjusted vegetation index product; the mathematical expression of the soil-adjusted vegetation index product production model can be expressed as the following formula (6):

[0071] SAVI = ((B14- B8) / (B14+ B8+ L)) * (1 + L) (6)

[0072] Where B14 is the reflectance of the first near-infrared band (840-860 nm), and B8 is the reflectance of the first red band (670-690 nm). L is the soil adjustment factor. L ranges from –1 to +1, depending on the density of green vegetation in the problem area. In areas with high green vegetation, L = 0, in which case SAVI is the same as NDVI. Conversely, in areas with low green vegetation, L = 1. Typically, L is set to 0.5 to accommodate most land cover. The GNDVI index is suitable for detecting wilting or aging crops and measuring nitrogen content in leaves when the red band is unavailable, and for monitoring dense tree canopies or mature vegetation. The SAVI index is used to analyze young seedlings and is suitable for arid areas with sparse vegetation (less than 15% of the total area) and exposed soil surfaces.

[0073] When the category of the target product to be produced is the vegetation detection product category and the target product to be produced is the optimized soil-adjusted vegetation index product OSAVI, the optimized soil-adjusted vegetation index product production model is used to produce the product based on the first near-infrared band reflectivity B14 and the first red light band reflectivity B8 to obtain the optimized soil-adjusted vegetation index; the mathematical expression of the optimized soil-adjusted vegetation index product production model can be expressed as the following formula (7):

[0074] OSAVI = (B14–B8) / (B14+ B8+ 0.16) (7)

[0075] B14: reflectance in the first near-infrared band (840-860 nm), and B8: reflectance in the first red band (670-690 nm). The OSAVI vegetation index is a modified version of the SAVI index, also using reflectance from B14 and B8. The difference between the two indices is that OSAVI incorporates a standardized value (0.16) for the canopy background adjustment factor. This adjustment allows for greater soil variability in OSAVI compared to SAVI when canopy cover is low. OSAVI is more sensitive to canopy cover exceeding 50%.

[0076] When the category of the target product to be produced is a vegetation detection product category and the target product to be produced is an atmospheric vegetation index product ARVI, the product is produced by adopting an optimized soil-adjusted vegetation index product production model based on the first near-infrared band reflectivity B14, the first red light band reflectivity B8, and the blue band reflectivity B3 to obtain the atmospheric vegetation index product; the mathematical expression of the optimized soil-adjusted vegetation index product production model can be expressed as the following formula (8):

[0077] ARVI = (B14– (2 * B8) + B3) / (B14+ (2 * B8) + B3) (8)

[0078] Among them, B14 is the reflectance of the first near-infrared band (840-860 nm), B8 is the reflectance of the first red band (670-690 nm), and B3 is the reflectance of the blue band (480-500 nm). This is the first vegetation index that is relatively insensitive to atmospheric factors such as aerosols. NDVI is corrected by doubling the red band measurement and adding the blue band to mitigate atmospheric scattering. Compared to other indices, ARVI is insensitive to aerosols and is particularly suitable for monitoring agricultural fields affected by straw burning and tropical mountainous areas frequently covered in smoke and dust.

[0079] When the category of the target product to be produced is a vegetation detection product category and the target product to be produced is an enhanced vegetation index product EVI, the enhanced vegetation index product production model is used to produce the product based on the first near-infrared band reflectivity B14 and the first red light band reflectivity B8 to obtain the enhanced vegetation index product; the mathematical expression of the enhanced vegetation index product production model can be expressed as the following formula (9):

[0080] EVI = 2.5 * ((B14–B8) / ((B14) + (C1 * B8) – (C2 * B3) + L)) (9)

[0081] The EVI includes the blue band reflectance (480-500nm). The coefficients C1 and C2 are used to correct for atmospheric aerosol scattering, and L is used to adjust for soil and tree canopy backgrounds. Therefore, compared to NDVI, EVI is more resistant to atmospheric interference and noise, making it more suitable for weather conditions with high aerosol content and areas with dense vegetation.

[0082] When the target product to be produced is a vegetation detection product and is a visible atmospheric resistance index product VARI, a visible atmospheric resistance index product production model is used to produce the product based on the first green band reflectivity B5, the second red band reflectivity B7, and the blue band reflectivity B3 to obtain the visible atmospheric resistance index product. The mathematical expression of the visible atmospheric resistance index product production model can be expressed as follows:

[0083] VARI = (B5 – B7) / (B5 + B7 – B3) (10)

[0084] Among them, B5: reflectance of the first green band (540-560nm), B7: reflectance of the second red band (620-650nm), and B3: reflectance of the blue band (480-500nm). The VARI index is well-suited for RGB or color imagery because it applies to the entire visible portion of the electromagnetic spectrum (including the red, green, and blue bands). Its specific task is to enhance vegetation under strong atmospheric influences while smoothing out illumination variations. Due to its low sensitivity to atmospheric influences, the VARI index has an error of less than 10% in vegetation monitoring under various atmospheric thickness conditions.

[0085] When the category of the target product to be produced is a vegetation detection product category and the target product to be produced is a standardized combustion rate product NBR, a standardized combustion rate product production model is used to produce the product based on the first near-infrared band reflectivity B14 and the first short-wave infrared band reflectivity B18 to obtain the standardized combustion rate product; the mathematical expression of the standardized combustion rate product production model can be expressed as the following formula (11):

[0086] NBR = (B14– B18) / (B14+ B18) (11)

[0087] Among them, B14: first near-infrared band reflectance (840-860 nm), B18: first short-wave infrared band reflectance (1580-1620 nm). NBR is used to highlight burned areas after a fire, which has become particularly important in the past few years as extreme weather conditions have led to a significant increase in wildfires that have recently destroyed forest biomass.

[0088] When the category of the target product to be produced is a vegetation detection product category and the target product to be produced is a structure-insensitive pigment vegetation index product SIPI, a structure-insensitive pigment vegetation index product production model is used to produce the product based on the first near-infrared band reflectivity B14, the blue band reflectivity B3 and the first red band reflectivity B8 to obtain the structure-insensitive pigment vegetation index product. The mathematical expression of the structure-insensitive pigment vegetation index product production model can be expressed as the following formula (12):

[0089] SIPI = (B14– B3) / (B14– B8) (12)

[0090] The SIPI vegetation index includes B14, which measures reflectance in the first near-infrared band (840-860 nm), B3, which measures reflectance in the blue band (480-500 nm), and B8, which measures reflectance in the first red band (670-690 nm). The SIPI vegetation index is useful for analyzing vegetation with variable canopy structure. It estimates the ratio of carotenoids to chlorophyll. Increased values indicate vegetation stress, which may indicate crop disease and often leads to chlorophyll loss in vegetation.

[0091] When the category of the target product to be produced is a vegetation detection product category and the target product to be produced is a green chlorophyll vegetation index product GCI, a green chlorophyll vegetation index product production model is used to produce the product based on the first near-infrared band reflectance B14 and the first green band reflectance B5 to obtain the green chlorophyll vegetation index product. The mathematical expression of the green chlorophyll vegetation index product production model can be expressed as the following formula (13):

[0092] GCI = B14 / B5–1 (13)

[0093] B14 is the reflectance of the first near-infrared band (840-860 nm), and B5 is the reflectance of the first green band (540-560 nm). In remote sensing, the GCI vegetation index is used to estimate the chlorophyll content in various plant species. Chlorophyll content reflects the physiological state of vegetation; it decreases in stressed plants and can therefore be used as a measure of vegetation health.

[0094] When the category of the target product to be produced is a vegetation detection product category and the target product to be produced is a difference vegetation index product DVI, a difference vegetation index product production model is used to produce the product based on the first near-infrared band reflectivity B14 and the first red light band reflectivity B8 to obtain the difference vegetation index product. The mathematical expression of the difference vegetation index product production model can be expressed as the following formula (14):

[0095] DVI = B14- B8 (14)

[0096] B14: Reflectance in the first near-infrared band (840-860 nm), B8: Reflectance in the first red band (670-690 nm). This sensor is suitable for use when vegetation cover is low and has higher sensitivity.

[0097] When the target product to be produced is a vegetation detection product and is a ratio vegetation index product (RVI), a ratio vegetation index product production model is used to produce the product based on the first near-infrared band reflectance B14 and the first red light band reflectance B8 to obtain the ratio vegetation index product. The mathematical expression of the ratio vegetation index product production model can be expressed as the following formula (15):

[0098] RVI = B14 / B8 (15)

[0099] B14: Reflectance in the first near-infrared band (840-860 nm), B8: Reflectance in the first red band (670-690 nm). Reflectance Visibility (RVI) is a sensitive indicator of green vegetation and can effectively detect and estimate plant biomass. Vegetation cover significantly influences RVI. When vegetation cover is high, RVI is highly sensitive to vegetation status. This sensitivity decreases significantly when vegetation cover is below 50%. RVI is affected by atmospheric conditions, which can reduce its sensitivity for vegetation detection.

[0100] When the category of the target product to be produced is the category of water and ice and snow detection products and the target product to be produced is the normalized difference water index product NDWI, the normalized difference water index product production model is used to produce the product based on the first near-infrared band reflectance B14 and the first green band reflectance B5 to obtain the normalized difference water index product; the mathematical expression of the normalized difference water index product production model can be expressed as the following formula (16):

[0101] NDWI = (B5– B14) / (B5+ B14) (16)

[0102] B14: Reflectance in the first near-infrared band (840-860 nm), B5: Reflectance in the first green band (540-560 nm). The NDWI index has significant advantages in extracting pure water bodies, but it does not effectively suppress shadows cast by mountains or tall buildings. It is suitable for detecting flooded farmland, allocating floodwaters on-site, monitoring irrigated farmland, and allocating wetlands.

[0103] When the category of the target product to be produced is the category of water and ice and snow detection products and the target product to be produced is a turbid water index product TWI, the turbid water index product production model is used to produce the product based on the first red light band reflectance B8 and the first short-wave infrared band reflectance B18 to obtain the turbid water index product; the mathematical expression of the turbid water index product production model can be expressed as the following formula (17):

[0104] TWI = B8- B18 (17)

[0105] B8: Reflectance in the first red band (670-690 nm), B18: Reflectance in the first shortwave infrared band (1580-1620 nm). The Turbid Water Index (TWI) is primarily used to assess water turbidity and is also used in identifying algal blooms.

[0106] When the category of the target product to be produced is the category of water body and ice and snow detection products and the target product to be produced is the cyanobacteria and macrophyte index product CMI, the cyanobacteria and macrophyte index product production model is used to produce the product based on the first green band reflectivity B5, the blue band reflectivity B3 and the first short-wave infrared band reflectivity B18 to obtain the cyanobacteria and macrophyte index product; the mathematical expression of the cyanobacteria and macrophyte index product production model can be expressed as the following formula (18):

[0107] (18)

[0108] Among them, B5: first green band reflectivity (540-560nm), B3: blue band reflectivity (480-500nm), B18: first short-wave infrared band reflectivity (1580-1620nm), Indicates the central wavelength of a band. CMI is designed to detect cyanobacteria and aquatic plants in water by testing the chlorophyll content in the water.

[0109] When the category of the target product to be produced is the category of water and ice and snow detection products and the target product to be produced is the phytoplankton index product FAI, the phytoplankton index product production model is used to produce the product based on the first near-infrared band reflectivity B14, the first red light band reflectivity B8 and the first short-wave infrared band reflectivity B18 to obtain the phytoplankton index product; the mathematical expression of the phytoplankton index product production model can be expressed as the following formula (19):

[0110] (19)

[0111] Among them, B14: reflectivity of the first near-infrared band (840-860 nm), B8: reflectivity of the first red light band (670-690 nm), B18: reflectivity of the short-wave infrared band (1580-1620 nm), Indicates the center wavelength of a band. FAI is primarily used for extracting floating algae blooms, but it also addresses the issue of CMI's inability to separate cyanobacteria and aquatic plants.

[0112] When the target product to be produced is a water and snow detection product and is a normalized difference snow index (NDSI) product, a normalized difference snow index product production model is used to produce the product based on the first green band reflectance B5 and the first shortwave infrared band reflectance B18 to obtain the normalized difference snow index product. The mathematical expression of the normalized difference snow index product production model can be expressed as follows:

[0113] NDSI = (B5–B18) / (B5+ B18) (20)

[0114] B5: Reflectance of the first green band (540-560nm), B18: Reflectance of the first shortwave infrared band (1580-1620nm). NDSI can effectively reduce the impact of noise from vegetation, building shadows, and other factors on lake ice monitoring.

[0115] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a ferrous-ferric distribution product, the first ferrous-ferric distribution product production model is used to produce the product based on the first near-infrared band reflectivity B14, the second near-infrared band reflectivity B12, the third near-infrared band reflectivity B13 and the second short-wave infrared band reflectivity B22 to obtain the ferrous-ferric distribution product; or, the second ferrous-ferric distribution product production model is used to produce the product based on the first green band reflectivity B5, the second green band reflectivity B4, the yellow band reflectivity B6, the second red light band reflectivity B7 and the first red light band reflectivity B8 to obtain the ferrous-ferric distribution product; the mathematical expression of the first ferrous-ferric distribution product production model can be expressed as follows:

[0116] Index = B22 / (B12+B13+B14)(21)

[0117] Among them, B12: reflectivity of the second near-infrared band (760-780nm), B13: reflectivity of the third near-infrared band (800-830nm), B14: reflectivity of the first near-infrared band (840-860nm), and B22: reflectivity of the second short-wave infrared band (2130-2170nm).

[0118] The mathematical expression of the second ferrous-ferric distribution product production model can be expressed as the following formula (22):

[0119] Index = (B7+B8) / (B4+B5+B6) (22)

[0120] Among them, B4: reflectivity of the second green band (520-540nm), B5: reflectivity of the first green band (540-560nm), B6: reflectivity of the yellow band (560-590nm), B7: reflectivity of the second red band (620-650nm), and B8: reflectivity of the first red band (670-690nm).

[0121] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is an iron oxide index product, the iron oxide index product production model is used to produce the product based on the second near-infrared band reflectivity B12, the third near-infrared band reflectivity B13, the first near-infrared band reflectivity B14, the first short-wave infrared band reflectivity B18 and the third short-wave infrared band reflectivity B19 to obtain the iron oxide index product; the mathematical expression of the iron oxide index product production model can be expressed as the following formula (23):

[0122] Index = (B18+B19) / (B12+B13+B14)(23)

[0123] Among them, B12: reflectivity of the second near-infrared band (760-780nm), B13: reflectivity of the third near-infrared band (800-830nm), B14: reflectivity of the first near-infrared band (840-860nm), B18: reflectivity of the first short-wave infrared band (1580-1620nm), and B19: reflectivity of the third short-wave infrared band (1630-1670nm).

[0124] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a laterite product, the first laterite product production model is used to produce the product based on the first shortwave infrared band reflectivity B18, the third shortwave infrared band reflectivity B19 and the second shortwave infrared band reflectivity B22 to obtain the laterite product; or, the second laterite product production model is used to produce the product based on the first green band reflectivity and the third shortwave infrared band reflectivity to obtain the laterite product; the mathematical expression of the first laterite product production model can be expressed as the following formula (24):

[0125] Index = (B18+B19) / B22 (24)

[0126] Among them, B18: reflectance of the first shortwave infrared band (1580-1620nm), B19: reflectance of the third shortwave infrared band (1630-1670nm), and B22: reflectance of the second shortwave infrared band (2130-2170nm).

[0127] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a ferrous silicate index product, a first ferrous silicate index product production model is used to produce the product based on the first short-wave infrared band reflectivity B18, the third short-wave infrared band reflectivity B19 and the second short-wave infrared band reflectivity B22 to obtain the ferrous silicate index product; or a second ferrous silicate index product production model is used to produce the product based on the third short-wave infrared band reflectivity B19 and the second short-wave infrared band reflectivity B22 to obtain the ferrous silicate index product; the mathematical expression of the first ferrous silicate index product production model can be expressed as the following formula (25):

[0128] Index = B22 / (B18+B19)(25)

[0129] Wherein, B18: reflectivity of the first short-wave infrared band (1580-1620nm), B19: reflectivity of the third short-wave infrared band (1630-1670nm), and B22: reflectivity of the second short-wave infrared band (2130-2170nm). The mathematical expression of the production model of the second ferrous silicate index product can be expressed as the following formula (26):

[0130] Index = B22 / B19 (26)

[0131] Among them, B19: reflectivity of the third shortwave infrared band (1630-1670nm), B22: reflectivity of the second shortwave infrared band (2130-2170nm).

[0132] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a silicate mineral product, the silicate mineral product production model is used to produce the product based on the fourth short-wave infrared band reflectivity B23, the fifth short-wave infrared band reflectivity B24, the sixth short-wave infrared band reflectivity B25 and the seventh short-wave infrared band reflectivity B26 to obtain the silicate mineral product; the mathematical expression of the silicate mineral product production model can be expressed as the following formula (27):

[0133] Index = (B23+B26) / (B24+B25)(27)

[0134] Among them, B23: reflectivity of the fourth shortwave infrared band (2190-2230nm), B24: reflectivity of the fifth shortwave infrared band (2250-2290nm), B25: reflectivity of the sixth shortwave infrared band (2320-2360nm), and B26: reflectivity of the seventh shortwave infrared band (2400-2480nm).

[0135] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is an intermediate mud zone mineral product, the intermediate mud zone mineral product production model is used to produce the product based on the second shortwave infrared band reflectivity B22, the fourth shortwave infrared band reflectivity B23 and the fifth shortwave infrared band reflectivity B24 to obtain the intermediate mud zone mineral product; the mathematical expression of the intermediate mud zone mineral product production model can be expressed as the following formula (28):

[0136] Index = (B22 + B24) / B23 (28)

[0137] Among them, B22: reflectivity of the second shortwave infrared band (2130-2170nm), B23: reflectivity of the fourth shortwave infrared band (2190-2230nm), and B24: reflectivity of the fifth shortwave infrared band (2250-2290nm).

[0138] When the target product to be produced is a geological exploration product and is a high-grade argillaceous zone mineral product, a high-grade argillaceous zone mineral product production model is used to produce the product based on the first short-wave infrared band reflectivity B18, the third short-wave infrared band reflectivity B19, the second short-wave infrared band reflectivity B22, and the fourth short-wave infrared band reflectivity B23 to obtain the high-grade argillaceous zone mineral product. The mathematical expression of the high-grade argillaceous zone mineral product production model can be expressed as the following formula (29):

[0139] Index =(B18+B19+B23) / B22(29)

[0140] B18: Reflectivity of the first shortwave infrared band (1580-1620nm), B19: Reflectivity of the third shortwave infrared band (1630-1670nm), B22: Reflectivity of the second shortwave infrared band (2130-2170nm), B23: Reflectivity of the fourth shortwave infrared band (2190-2230nm).

[0141] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is an alunite mineral product, the alunite mineral product production model is used to produce the product based on the second shortwave infrared band reflectivity B22, the fifth shortwave infrared band reflectivity B24 and the sixth shortwave infrared band reflectivity B25 to obtain the alunite mineral product; the mathematical expression of the alunite mineral product production model can be expressed as the following formula (30):

[0142] = (B24×B22) / (B24×B25) (30)

[0143] Among them, B22: reflectivity of the second shortwave infrared band (2130-2170nm), B24: reflectivity of the fifth shortwave infrared band (2250-2290nm), and B25: reflectivity of the sixth shortwave infrared band (2320-2360nm).

[0144] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a calcite mineral product, a calcite mineral product production model is used to produce the product based on the fourth short-wave infrared band reflectivity B23, the sixth short-wave infrared band reflectivity B25, and the seventh short-wave infrared band reflectivity B26 to obtain the calcite mineral product; the mathematical expression of the calcite mineral product production model can be expressed as the following formula (31):

[0145] = (B23 / B25)×(B26 / B25) (31)

[0146] Among them, B23: reflectivity of the fourth shortwave infrared band (2190-2230nm), B25: reflectivity of the sixth shortwave infrared band (2320-2360nm), and B26: reflectivity of the seventh shortwave infrared band (2400-2480nm).

[0147] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a clay alteration index product, the clay alteration index product production model is used to produce the product based on the third shortwave infrared band reflectivity B19, the second shortwave infrared band reflectivity B22 and the fourth shortwave infrared band reflectivity B23 to obtain the clay alteration index product; the mathematical expression of the clay alteration index product production model can be expressed as the following formula (32):

[0148] = (B19+B23) / B22 (32)

[0149] Among them, B19: reflectivity of the third shortwave infrared band (1630-1670nm), B22: reflectivity of the second shortwave infrared band (2130-2170nm), and B23: reflectivity of the fourth shortwave infrared band (2190-2230nm).

[0150] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a dolomite index product, the dolomite index product production model is used to produce the product based on the fourth shortwave infrared band reflectivity B23, the fifth shortwave infrared band reflectivity B24, and the sixth shortwave infrared band reflectivity B25 to obtain the dolomite index product; the mathematical expression of the dolomite index product production model can be expressed as the following formula (33):

[0151] = (B23+B25) / B24 (33)

[0152] Among them, B23: reflectivity of the fourth shortwave infrared band (2190-2230nm), B24: reflectivity of the fifth shortwave infrared band (2250-2290nm), and B25: reflectivity of the sixth shortwave infrared band (2320-2360nm).

[0153] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is an epidote index product, a chlorite index product and an amphibole index product, the epidote index product production model, the chlorite index product production model or the amphibole index product production model is adopted to produce the product based on the fourth shortwave infrared band reflectivity B23, the fifth shortwave infrared band reflectivity B24, the sixth shortwave infrared band reflectivity B25 and the seventh shortwave infrared band reflectivity B26 to obtain the epidote index product, the chlorite index product or the amphibole index product; the mathematical expression of the epidote index product production model, the chlorite index product production model or the amphibole index product production model can be expressed as the following formula (34):

[0154] = (B23+B26) / (B24+B25) (34)

[0155] Among them, B23: reflectivity of the fourth shortwave infrared band (2190-2230nm), B24: reflectivity of the fifth shortwave infrared band (2250-2290nm), B25: reflectivity of the sixth shortwave infrared band (2320-2360nm), and B26: reflectivity of the seventh shortwave infrared band (2400-2480nm).

[0156] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a magnesite index product, a magnesite index product production model is used to produce the product based on the fourth shortwave infrared band reflectivity B23, the fifth shortwave infrared band reflectivity B24, the sixth shortwave infrared band reflectivity B25, and the seventh shortwave infrared band reflectivity B26 to obtain the magnesite index product; the mathematical expression of the magnesite index product production model can be expressed as the following formula (35):

[0157] = (B23+B25) / (B24+B26) (35)

[0158] Among them, B23: reflectivity of the fourth shortwave infrared band (2190-2230nm), B24: reflectivity of the fifth shortwave infrared band (2250-2290nm), B25: reflectivity of the sixth shortwave infrared band (2320-2360nm), and B26: reflectivity of the seventh shortwave infrared band (2400-2480nm).

[0159] When the target product to be produced is a geological exploration product and is a carbonate abundance index product, a carbonate abundance index product production model is used to produce the product based on the fourth shortwave infrared band reflectivity B23, the sixth shortwave infrared band reflectivity B25, and the seventh shortwave infrared band reflectivity B26 to obtain the carbonate abundance index product. The mathematical expression of the carbonate abundance index product production model can be expressed as the following formula (36):

[0160] = (B26+B23) / B25 (36)

[0161] Among them, B23: reflectivity of the fourth shortwave infrared band (2190-2230nm), B25: reflectivity of the sixth shortwave infrared band (2320-2360nm), and B26: reflectivity of the seventh shortwave infrared band (2400-2480nm).

[0162] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a montmorillonite index product, the montmorillonite index product production model is used to produce the product based on the third shortwave infrared band reflectivity B19, the fourth shortwave infrared band reflectivity B23 and the fifth shortwave infrared band reflectivity B24 to obtain the montmorillonite index product; the mathematical expression of the montmorillonite index product production model can be expressed as the following formula (37):

[0163] Index = (B19+B23) / B24 (37)

[0164] Among them, B19: reflectivity of the third shortwave infrared band (1630-1670nm), B23: reflectivity of the fourth shortwave infrared band (2190-2230nm), and B24: reflectivity of the fifth shortwave infrared band (2250-2290nm).

[0165] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a muscovite index product, the muscovite index product production model is used to produce the product based on the fourth shortwave infrared band reflectivity B23 and the fifth shortwave infrared band reflectivity B24 to obtain the muscovite index product; the mathematical expression of the muscovite index product production model can be expressed as the following formula (38):

[0166] Index = B24 / B23 (38)

[0167] Among them, B23: reflectivity of the fourth shortwave infrared band (2190-2230nm), B24: reflectivity of the fifth shortwave infrared band (2250-2290nm).

[0168] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a phenolic index product, the phenolic index product production model is used to produce the product based on the second short-wave infrared band reflectivity B22 and the fourth short-wave infrared band reflectivity B23 to obtain the phenolic index product; the mathematical expression of the phenolic index product production model can be expressed as the following formula (39):

[0169] Index = B22 / B23 (39)

[0170] Among them, B22: reflectivity of the second shortwave infrared band (2130-2170nm), B23: reflectivity of the fourth shortwave infrared band (2190-2230nm).

[0171] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a foliation alteration index product, the foliation alteration index product production model is used to produce the product based on the second shortwave infrared band reflectivity B22, the fourth shortwave infrared band reflectivity B23 and the fifth shortwave infrared band reflectivity B24 to obtain the foliation alteration index product. The mathematical expression of the foliation alteration index product production model can be expressed as the following formula (40):

[0172] Index = (B22+B24) / B23 (40)

[0173] Among them, B22: reflectivity of the second shortwave infrared band (2130-2170nm), B23: reflectivity of the fourth shortwave infrared band (2190-2230nm), and B24: reflectivity of the fifth shortwave infrared band (2250-2290nm).

[0174] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a propyl metamorphic index product, a propyl metamorphic index product production model is used to produce the product based on the fifth shortwave infrared band reflectivity B24, the sixth shortwave infrared band reflectivity B25, and the seventh shortwave infrared band reflectivity B26 to obtain the propyl metamorphic index product. The mathematical expression of the propyl metamorphic index product production model can be expressed as the following formula (41):

[0175] Index = (B24+B26) / B25 (41)

[0176] Among them, B24: reflectivity of the fifth shortwave infrared band (2250-2290nm), B25: reflectivity of the sixth shortwave infrared band (2320-2360nm), and B26: reflectivity of the seventh shortwave infrared band (2400-2480nm).

[0177] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a hydroxyl-containing altered mineral index product, a hydroxyl-containing altered mineral index product production model is used to produce the product based on the third shortwave infrared band reflectivity B19, the second shortwave infrared band reflectivity B22, the fourth shortwave infrared band reflectivity B23 and the fifth shortwave infrared band reflectivity B24 to obtain the hydroxyl-containing altered mineral index product; the mathematical expression of the hydroxyl-containing altered mineral index product production model can be expressed as the following formula (42), (43) or (44):

[0178] Index1 = (B24 / B22)×(B19 / B22) (42)

[0179] Index2 = (B19×B24) / (B23×B23) (43)

[0180] Index3 = (B19×B24) / (B22×B22) (44)

[0181] Among them, B19: reflectivity of the third shortwave infrared band (1630-1670nm), B22: reflectivity of the second shortwave infrared band (2130-2170nm), B23: reflectivity of the fourth shortwave infrared band (2190-2230nm), and B24: reflectivity of the fifth shortwave infrared band (2250-2290nm).

[0182] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a kaolinite index product, the kaolinite index product production model is used to produce the product based on the third shortwave infrared band reflectivity B19, the second shortwave infrared band reflectivity B22, the fourth shortwave infrared band reflectivity B23, the fifth shortwave infrared band reflectivity B24, and the sixth shortwave infrared band reflectivity B25 to obtain the kaolinite index product. The mathematical expression of the kaolinite index product production model can be expressed as the following formula (45), (46), or (47):

[0183] Index1 = B24×B22 (45)

[0184] Index2 = (B19 / B22)×(B25 / B23) (46)

[0185] Index3 = (B19+B24) / B23 (47)

[0186] Among them, B19: reflectivity of the third shortwave infrared band (1630-1670nm), B22: reflectivity of the second shortwave infrared band (2130-2170nm), B23: reflectivity of the fourth shortwave infrared band (2190-2230nm), B24: reflectivity of the fifth shortwave infrared band (2250-2290nm), and B25: reflectivity of the sixth shortwave infrared band (2320-2360nm).

[0187] This application acquires multispectral remote sensing image data from the Geology-1 satellite; extracts data based on this multispectral remote sensing image data to obtain the reflectance of the target product in different wavebands; and then produces the target product using a production model corresponding to the target product based on each reflectance. This system achieves automated production of a variety of common products in the ecological and geological fields, suitable for a wide range of applications, including natural resource management, agriculture, environmental protection, and geological exploration.

[0188] Another embodiment of the present application provides a common product production device based on the remote sensing data of the Geology-1 satellite, such as Figure 2 Shown, including:

[0189] Acquisition module 1 is used to acquire multispectral remote sensing image data of the Geology-1 satellite;

[0190] A data extraction module 2 is configured to extract data based on the multispectral remote sensing image data for a target product to be produced, and obtain reflectances of different wavebands corresponding to the target product to be produced;

[0191] The product production module 3 is configured to produce a product based on each of the reflectivities using a product production model corresponding to the target product to be produced to obtain a target product; the product production model corresponding to the target product to be produced based on each of the reflectivities to obtain a target product specifically includes:

[0192] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is an alunite mineral product, based on Carry out product production;

[0193] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a calcite mineral product, based on Carry out product production;

[0194] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a clay alteration index product, based on Carry out product production;

[0195] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a dolomite index product, based on Carry out product production;

[0196] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is an epidote index product, a chlorite index product, and an amphibole index product, based on Carry out product production;

[0197] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a magnesite index product, based on Carry out product production;

[0198] When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a carbonate abundance index product, based on Carry out product production;

[0199] in, 、 、 、 、 as well as They are all shortwave infrared spectrum bands of the Address-1 satellite, and the band reflectivities are 1630-1670nm, 2130-2170nm, 2190-2230nm, 2250-2290nm, 2320-2360nm and 2400-2480nm respectively.

[0200] In the specific implementation process, the data extraction module 2 is specifically used for: when the product category of the target product to be produced is the vegetation detection product category, the reflectivity of different bands corresponding to the target product to be produced includes one or more of the blue band reflectivity, the first green band reflectivity, the first red light band reflectivity, the second red light band reflectivity, the first red edge band reflectivity, the first near-infrared band reflectivity and the first short-wave infrared band reflectivity; when the product category of the target product to be produced is the water and ice and snow detection product category, the reflectivity of different bands corresponding to the target product to be produced includes the blue band reflectivity, the first green band reflectivity, the first red light band reflectivity, the first near-infrared band reflectivity rate and one or more of the first short-wave infrared band reflectivity; when the product category of the target product to be produced is a geological exploration product category, the reflectivities of different bands corresponding to the target product to be produced include the second green band reflectivity, the first green band reflectivity, the yellow band reflectivity, the first red light band reflectivity, the second red light band reflectivity, the first near-infrared band reflectivity, the second near-infrared band reflectivity, the third near-infrared band reflectivity, the first short-wave infrared band reflectivity, the second short-wave infrared band reflectivity, the third short-wave infrared band reflectivity, the fourth short-wave infrared band reflectivity, the fifth short-wave infrared band reflectivity, the sixth short-wave infrared band reflectivity, and the seventh short-wave infrared band reflectivity.

[0201] In the specific implementation process, the product production module 3 is specifically used for: when the category of the target product to be produced is the vegetation detection product category and the target product to be produced is the normalized difference vegetation index product, based on the first near-infrared band reflectivity and the first red light band reflectivity, the normalized difference vegetation index product production model is used to produce the product to obtain the normalized difference vegetation index product; when the category of the target product to be produced is the vegetation detection product category and the target product to be produced is the red edge chlorophyll vegetation index product, based on the first near-infrared band reflectivity and the first red light band reflectivity, the red edge chlorophyll vegetation index product is used to produce the product to obtain the red edge chlorophyll vegetation index product; when the category of the target product to be produced is the vegetation detection product category and the target product to be produced is the normalized difference red edge vegetation index product, based on the The first near-infrared band reflectivity and the first red edge band reflectivity are used to produce products using the normalized difference red edge vegetation index product production model to obtain the normalized difference red edge vegetation index product; when the category of the target product to be produced is the vegetation detection product category and the target product to be produced is the improved soil adjusted vegetation index product, the improved soil adjusted vegetation index product is produced based on the first near-infrared band reflectivity and the first red light band reflectivity to obtain the improved soil adjusted vegetation index product; when the category of the target product to be produced is the vegetation detection product category and the target product to be produced is the green normalized difference vegetation index product, the green normalized difference vegetation index product production model is used to produce products based on the first near-infrared band reflectivity and the first green band reflectivity to obtain the green normalized difference vegetation index product.

[0202] In the specific implementation process, the product production module 3 is also used for: when the category of the target product to be produced is the vegetation detection product category and the target product to be produced is the soil adjustment vegetation index product, the soil adjustment vegetation index product production model is used to produce the product based on the first near-infrared band reflectivity and the first red light band reflectivity to obtain the soil adjustment vegetation index product; when the category of the target product to be produced is the vegetation detection product category and the target product to be produced is the optimized soil adjustment vegetation index product, the optimized soil adjustment vegetation index product production model is used to produce the product based on the first near-infrared band reflectivity and the first red light band reflectivity to obtain the optimized soil adjustment vegetation index; when the category of the target product to be produced is the vegetation detection product category and the target product to be produced is the atmospheric resistance vegetation index product, The first near-infrared band reflectivity, the first red light band reflectivity and the blue band reflectivity are produced using the optimized soil adjustment vegetation index product production model to obtain the atmospheric resistance vegetation index product; when the category of the target product to be produced is the vegetation detection product category and the target product to be produced is the enhanced vegetation index product, the enhanced vegetation index product production model is used based on the first near-infrared band reflectivity and the first red light band reflectivity to produce the product to obtain the enhanced vegetation index product; when the category of the target product to be produced is the vegetation detection product category and the target product to be produced is the visible atmospheric resistance index product, the visible atmospheric resistance index product production model is used based on the first green band reflectivity, the second red light band reflectivity and the blue band reflectivity to produce the product to obtain the visible atmospheric resistance index product.

[0203] In the specific implementation process, the product production module 3 is also used for: when the category of the target product to be produced is the vegetation detection product category and the target product to be produced is the standardized combustion rate product, based on the first near-infrared band reflectivity and the first short-wave infrared band reflectivity, the standardized combustion rate product production model is used to produce the product to obtain the standardized combustion rate product; when the category of the target product to be produced is the vegetation detection product category and the target product to be produced is the structure-insensitive pigment vegetation index product, based on the first near-infrared band reflectivity, the blue band reflectivity and the first red light band reflectivity, the structure-insensitive pigment vegetation index product production model is used to produce the product to obtain the structure-insensitive pigment vegetation index product; when the category of the target product to be produced is the vegetation detection product category and the target product to be produced is the vegetation detection product category When it is a green chlorophyll vegetation index product, the green chlorophyll vegetation index product production model is adopted based on the first near-infrared band reflectivity and the first green band reflectivity to produce the product, and the green chlorophyll vegetation index product is obtained; when the category of the target product to be produced is the vegetation detection product category and the target product to be produced is the difference vegetation index product, the difference vegetation index product production model is adopted based on the first near-infrared band reflectivity and the first red light band reflectivity to produce the product, and the difference vegetation index product is obtained; when the category of the target product to be produced is the vegetation detection product category and the target product to be produced is the ratio vegetation index product, the ratio vegetation index product production model is adopted based on the first near-infrared band reflectivity and the first red light band reflectivity to produce the product, and the ratio vegetation index product is obtained.

[0204] In the specific implementation process, the product production module 3 is also used for: when the category of the target product to be produced is the category of water and ice and snow detection products and the target product to be produced is a normalized difference water index product, based on the first near-infrared band reflectivity and the first green band reflectivity, the normalized difference water index product production model is used to produce the product to obtain the normalized difference water index product; when the category of the target product to be produced is the category of water and ice and snow detection products and the target product to be produced is a turbidity water index product, based on the first red light band reflectivity and the first shortwave infrared band reflectivity, the turbidity water index product production model is used to produce the product to obtain the turbidity water index product; when the category of the target product to be produced is the category of water and ice and snow detection products and the target product to be produced is a cyanobacteria and large aquatic plant index product, based on the first green band reflectivity and The blue band reflectivity and the first shortwave infrared band reflectivity are used to produce products using the cyanobacteria and large aquatic plant index product production model to obtain the cyanobacteria and large aquatic plant index product; when the category of the target product to be produced is the water body and ice and snow detection product category and the target product to be produced is the phytoplankton index product, the phytoplankton index product production model is used to produce the product based on the first near-infrared band reflectivity, the first red light band reflectivity and the first shortwave infrared band reflectivity to obtain the phytoplankton index product; when the category of the target product to be produced is the water body and ice and snow detection product category and the target product to be produced is the normalized difference snow index product, the normalized difference snow index product production model is used to produce the product based on the first green band reflectivity and the first shortwave infrared band reflectivity to obtain the normalized difference snow index product.

[0205] In the specific implementation process, the product production module 3 is also used for: when the category of the target product to be produced is a geological exploration product category and the target product to be produced is a ferrous-ferric distribution product, based on the first near-infrared band reflectivity, the second near-infrared band reflectivity, the third near-infrared band reflectivity and the second short-wave infrared band reflectivity, the first ferrous-ferric distribution product production model is used to produce the product to obtain the ferrous-ferric distribution product; or, based on the first green band reflectivity, the second green band reflectivity, the yellow band reflectivity, the second red light band reflectivity and the first red light band reflectivity, the second ferrous-ferric distribution product production model is used to produce the product to obtain the ferrous-ferric distribution product; when the target product to be produced is a geological exploration product category and the target product to be produced is a ferrous-ferric distribution product, based on the first near-infrared band reflectivity, the second near-infrared band reflectivity, the third near-infrared band reflectivity and the second short-wave infrared band reflectivity, the first ferrous-ferric distribution product is produced When the category of the target product to be produced is a geological exploration product category and the target product to be produced is an iron oxide index product, the iron oxide index product production model is used to produce the product based on the second near-infrared band reflectivity, the third near-infrared band reflectivity, the first near-infrared band reflectivity, the first short-wave infrared band reflectivity, and the third short-wave infrared band reflectivity to obtain the iron oxide index product; when the category of the target product to be produced is a geological exploration product category and the target product to be produced is a laterite product, the first laterite product production model is used to produce the product based on the first short-wave infrared band reflectivity, the third short-wave infrared band reflectivity, and the second short-wave infrared band reflectivity to obtain the laterite product; Alternatively, based on the first green band reflectivity and the third shortwave infrared band reflectivity, a second laterite belt product production model is used to produce the product to obtain the laterite belt product; when the category of the target product to be produced is a geological exploration product category and the target product to be produced is a ferrous silicate index product, based on the first shortwave infrared band reflectivity, the third shortwave infrared band reflectivity and the second shortwave infrared band reflectivity, a first ferrous silicate index product production model is used to produce the product to obtain the ferrous silicate index product; or, based on the third shortwave infrared band reflectivity and the second shortwave infrared band reflectivity, a second ferrous silicate index product production model is used to produce the product to obtain the ferrous silicate index product. products; when the category of the target product to be produced is a geological exploration product category and the target product to be produced is a silicate mineral product, the silicate mineral product production model is used to produce the product based on the fourth short-wave infrared band reflectivity, the fifth short-wave infrared band reflectivity, the sixth short-wave infrared band reflectivity and the seventh short-wave infrared band reflectivity to obtain the silicate mineral product; when the category of the target product to be produced is a geological exploration product category and the target product to be produced is an intermediate mud zone mineral product, the intermediate mud zone mineral product production model is used to produce the product based on the second short-wave infrared band reflectivity, the fourth short-wave infrared band reflectivity and the fifth short-wave infrared band reflectivity to obtain the intermediate mud zone mineral product;When the target product to be produced is a geological exploration product and is a high-grade argillaceous zone mineral product, a high-grade argillaceous zone mineral product production model is used to produce the product based on the first shortwave infrared band reflectivity, the third shortwave infrared band reflectivity, the second shortwave infrared band reflectivity, and the fourth shortwave infrared band reflectivity to obtain the high-grade argillaceous zone mineral product.

[0206] In the specific implementation process, the product production module 3 is also used for: when the category of the target product to be produced is a geological exploration product category and the target product to be produced is an alunite mineral product, the alunite mineral product production model is used to produce the product based on the second short-wave infrared band reflectivity, the fifth short-wave infrared band reflectivity and the sixth short-wave infrared band reflectivity to obtain the alunite mineral product; when the category of the target product to be produced is a geological exploration product category and the target product to be produced is a calcite mineral product, the calcite mineral product production model is used to produce the product based on the fourth short-wave infrared band reflectivity, the sixth short-wave infrared band reflectivity and the seventh short-wave infrared band reflectivity. Production, to obtain the calcite mineral product; when the category of the target product to be produced is the geological exploration product category and the target product to be produced is the clay alteration index product, based on the third shortwave infrared band reflectivity, the second shortwave infrared band reflectivity and the fourth shortwave infrared band reflectivity, the clay alteration index product production model is used to produce the product to obtain the clay alteration index product; when the category of the target product to be produced is the geological exploration product category and the target product to be produced is the dolomite index product, based on the fourth shortwave infrared band reflectivity, the fifth shortwave infrared band reflectivity and the sixth shortwave infrared band reflectivity, the dolomite index product production model is used to produce the product Product production is carried out to obtain the dolomite index product; when the category of the target product to be produced is the geological exploration product category and the target product to be produced is the epidote index product, the chlorite index product and the amphibole index product, the epidote index product production model, the chlorite index product production model or the amphibole index product production model is used to produce the product based on the fourth shortwave infrared band reflectivity, the fifth shortwave infrared band reflectivity, the sixth shortwave infrared band reflectivity and the seventh shortwave infrared band reflectivity to obtain the epidote index product, the chlorite index product or the amphibole index product; when the category of the target product to be produced is the geological exploration product category And when the target product to be produced is a magnesite index product, a magnesite index product production model is used to produce the product based on the fourth short-wave infrared band reflectivity, the fifth short-wave infrared band reflectivity, the sixth short-wave infrared band reflectivity, and the seventh short-wave infrared band reflectivity to obtain the magnesite index product; when the category of the target product to be produced is a geological exploration product category and the target product to be produced is a carbonate abundance index product, a carbonate abundance index product production model is used to produce the product based on the fourth short-wave infrared band reflectivity, the sixth short-wave infrared band reflectivity, and the seventh short-wave infrared band reflectivity to obtain the carbonate abundance index product.

[0207] In the specific implementation process, the product production module 3 is also used for: when the category of the target product to be produced is the geological exploration product category and the target product to be produced is the montmorillonite index product, the montmorillonite index product production model is used to produce the product based on the third short-wave infrared band reflectivity, the fourth short-wave infrared band reflectivity and the fifth short-wave infrared band reflectivity to obtain the montmorillonite index product; when the category of the target product to be produced is the geological exploration product category and the target product to be produced is the muscovite index product, the muscovite index product production model is used to produce the product based on the fourth short-wave infrared band reflectivity and the fifth short-wave infrared band reflectivity. The product is produced by adopting the phenolic index product production model to obtain the muscovite index product; when the category of the target product to be produced is the geological exploration product category and the target product to be produced is the phenolic index product, the product is produced by adopting the phenolic index product production model based on the second shortwave infrared band reflectivity and the fourth shortwave infrared band reflectivity to obtain the phenolic index product; when the category of the target product to be produced is the geological exploration product category and the target product to be produced is the foliated alteration index product, the foliated alteration index is adopted based on the second shortwave infrared band reflectivity, the fourth shortwave infrared band reflectivity and the fifth shortwave infrared band reflectivity. The product production model is used to produce the product to obtain the foliated alteration index product; when the category of the target product to be produced is the geological exploration product category and the target product to be produced is the propyl metamorphic index product, the propyl metamorphic index product production model is used to produce the product based on the reflectivity of the fifth short-wave infrared band, the reflectivity of the sixth short-wave infrared band and the reflectivity of the seventh short-wave infrared band to obtain the propyl metamorphic index product; when the category of the target product to be produced is the geological exploration product category and the target product to be produced is the hydroxyl-containing alteration mineral index product, the propyl metamorphic index product production model is used to produce the product based on the reflectivity of the third short-wave infrared band, the reflectivity of the second short-wave infrared band and the reflectivity of the seventh short-wave infrared band The hydroxyl-containing altered mineral index product production model is used to produce products based on the reflectivity of the third shortwave infrared band, the reflectivity of the second shortwave infrared band, the reflectivity of the fourth shortwave infrared band, and the reflectivity of the fifth shortwave infrared band to obtain the hydroxyl-containing altered mineral index product; when the category of the target product to be produced is the geological exploration product category and the target product to be produced is the kaolinite index product, the kaolinite index product production model is used to produce products based on the reflectivity of the third shortwave infrared band, the reflectivity of the second shortwave infrared band, the reflectivity of the fourth shortwave infrared band, the reflectivity of the fifth shortwave infrared band, and the reflectivity of the sixth shortwave infrared band to obtain the kaolinite index product.

[0208] This application acquires multispectral remote sensing image data from the Geology-1 satellite; extracts data based on this multispectral remote sensing image data to obtain the reflectance of the target product in different wavebands; and then produces the target product using a production model corresponding to the target product based on each reflectance. This system achieves automated production of a variety of common products in the ecological and geological fields, suitable for a wide range of applications, including natural resource management, agriculture, environmental protection, and geological exploration.

[0209] The specific implementation process of the above method steps can refer to any of the above embodiments of the product production method based on the remote sensing data of the Geology-1 satellite, and this embodiment will not be repeated here.

[0210] The above embodiments are merely exemplary embodiments of the present application and are not intended to limit the scope of the present application. The scope of protection of the present application is defined by the claims. Those skilled in the art may make various modifications or equivalent substitutions to the present application within the essence and scope of protection of the present application, and such modifications or equivalent substitutions shall also be deemed to fall within the scope of protection of the present application.

Claims

1. A method for producing common products based on remote sensing data from the Geology-1 satellite, characterized in that: include: Acquire multispectral remote sensing image data from the Geology-1 satellite; For a target product to be produced, data extraction is performed based on the multispectral remote sensing image data to obtain reflectances of different bands corresponding to the target product to be produced; Based on the reflectivity, a product production model corresponding to the target product to be produced is used to produce the product to obtain the target product; The step of producing a target product by adopting a product production model corresponding to the target product to be produced based on each of the reflectivities to obtain the target product specifically includes: When the category of the target product to be produced is a geological exploration product category and the target product to be produced is an alunite mineral product, based on Carry out product production; When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a calcite mineral product, based on Carry out product production; When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a clay alteration index product, based on Carry out product production; When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a dolomite index product, based on Carry out product production; When the category of the target product to be produced is a geological exploration product category and the target product to be produced is an epidote index product, a chlorite index product, and an amphibole index product, based on Carry out product production; When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a magnesite index product, based on Carry out product production; When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a carbonate abundance index product, based on Carry out product production; in, 、 、 、 、 as well as They are all shortwave infrared spectrum bands of the Address-1 satellite, and the band reflectivities are 1630-1670nm, 2130-2170nm, 2190-2230nm, 2250-2290nm, 2320-2360nm and 2400-2480nm respectively.

2. The method according to claim 1, wherein The method of extracting data based on the multispectral remote sensing image data for the target product to be produced to obtain reflectances of different bands corresponding to the target product to be produced specifically includes: When the product category of the target product to be produced is a vegetation detection product category, the reflectances of different bands corresponding to the target product to be produced include one or more of a blue band reflectance, a first green band reflectance, a first red light band reflectance, a second red light band reflectance, a first red edge band reflectance, a first near-infrared band reflectance, and a first short-wave infrared band reflectance; When the product category of the target product to be produced is a water and ice and snow detection product category, the reflectances of different bands corresponding to the target product to be produced include one or more of the blue band reflectance, the first green band reflectance, the first red band reflectance, the first near-infrared band reflectance, and the first short-wave infrared band reflectance; When the product category of the target product to be produced is a geological exploration product category, the reflectivities of different bands corresponding to the target product to be produced include the second green band reflectivity, the first green band reflectivity, the yellow band reflectivity, the first red light band reflectivity, the second red light band reflectivity, the first near-infrared band reflectivity, the second near-infrared band reflectivity, the third near-infrared band reflectivity, the first short-wave infrared band reflectivity, the second short-wave infrared band reflectivity, the third short-wave infrared band reflectivity, the fourth short-wave infrared band reflectivity, the fifth short-wave infrared band reflectivity, the sixth short-wave infrared band reflectivity, and the seventh short-wave infrared band reflectivity.

3. The method according to claim 1, wherein The step of producing a target product by adopting a product production model corresponding to the target product to be produced based on each of the reflectivities to obtain the target product specifically includes: When the category of the target product to be produced is a vegetation detection product category and the target product to be produced is a normalized difference vegetation index product, a normalized difference vegetation index product production model is used to produce the product based on the first near-infrared band reflectance and the first red light band reflectance to obtain the normalized difference vegetation index product; When the category of the target product to be produced is a vegetation detection product category and the target product to be produced is a red-edge chlorophyll vegetation index product, a red-edge chlorophyll vegetation index product production model is used to produce the product based on the first near-infrared band reflectance and the first red light band reflectance to obtain the red-edge chlorophyll vegetation index product; When the category of the target product to be produced is a vegetation detection product category and the target product to be produced is a normalized difference red edge vegetation index product, a normalized difference red edge vegetation index product production model is used to produce the product based on the first near-infrared band reflectance and the first red edge band reflectance to obtain the normalized difference red edge vegetation index product; When the category of the target product to be produced is a vegetation detection product category and the target product to be produced is an improved soil adjusted vegetation index product, producing the product using an improved soil adjusted vegetation index product production model based on the first near-infrared band reflectivity and the first red light band reflectivity to obtain the improved soil adjusted vegetation index product; When the category of the target product to be produced is a vegetation detection product category and the target product to be produced is a green normalized difference vegetation index product, the green normalized difference vegetation index product production model is used to produce the product based on the first near-infrared band reflectivity and the first green band reflectivity to obtain the green normalized difference vegetation index product.

4. The method according to claim 1, wherein The step of producing a target product by adopting a product production model corresponding to the target product to be produced based on each of the reflectivities to obtain the target product comprises: When the category of the target product to be produced is a vegetation detection product category and the target product to be produced is a soil-adjusted vegetation index product, producing the product using a soil-adjusted vegetation index product production model based on the first near-infrared band reflectance and the first red light band reflectance to obtain the soil-adjusted vegetation index product; When the category of the target product to be produced is a vegetation detection product category and the target product to be produced is an optimized soil-adjusted vegetation index product, the optimized soil-adjusted vegetation index product production model is used to produce the product based on the first near-infrared band reflectivity and the first red light band reflectivity to obtain the optimized soil-adjusted vegetation index; When the category of the target product to be produced is a vegetation detection product category and the target product to be produced is an atmosphere-resistant vegetation index product, an optimized soil-adjusted vegetation index product production model is used to produce the product based on the first near-infrared band reflectivity, the first red light band reflectivity, and the blue band reflectivity to obtain the atmosphere-resistant vegetation index product; When the category of the target product to be produced is a vegetation detection product category and the target product to be produced is an enhanced vegetation index product, producing the product using an enhanced vegetation index product production model based on the first near-infrared band reflectivity and the first red light band reflectivity to obtain the enhanced vegetation index product; When the category of the target product to be produced is a vegetation detection product category and the target product to be produced is a visible atmospheric resistance index product, the visible atmospheric resistance index product production model is used to produce the product based on the first green band reflectivity, the second red light band reflectivity and the blue band reflectivity to obtain the visible atmospheric resistance index product.

5. The method according to claim 1, wherein The step of producing a target product by adopting a product production model corresponding to the target product to be produced based on each of the reflectivities to obtain the target product comprises: When the category of the target product to be produced is a vegetation detection product category and the target product to be produced is a standardized combustion rate product, producing the product using a standardized combustion rate product production model based on the first near-infrared band reflectance and the first short-wave infrared band reflectance to obtain the standardized combustion rate product; When the category of the target product to be produced is a vegetation detection product category and the target product to be produced is a structure-insensitive pigment vegetation index product, a structure-insensitive pigment vegetation index product production model is used to produce the product based on the first near-infrared band reflectivity, the blue band reflectivity, and the first red band reflectivity to obtain the structure-insensitive pigment vegetation index product; When the category of the target product to be produced is a vegetation detection product category and the target product to be produced is a green chlorophyll vegetation index product, producing the product using a green chlorophyll vegetation index product production model based on the first near-infrared band reflectance and the first green band reflectance to obtain the green chlorophyll vegetation index product; When the category of the target product to be produced is a vegetation detection product category and the target product to be produced is a difference vegetation index product, producing the product using a difference vegetation index product production model based on the first near-infrared band reflectance and the first red light band reflectance to obtain the difference vegetation index product; When the category of the target product to be produced is a vegetation detection product category and the target product to be produced is a ratio vegetation index product, the product is produced using a ratio vegetation index product production model based on the first near-infrared band reflectivity and the first red light band reflectivity to obtain the ratio vegetation index product.

6. The method according to claim 1, wherein The step of producing a target product by adopting a product production model corresponding to the target product to be produced based on each of the reflectivities to obtain the target product comprises: When the category of the target product to be produced is a water and ice and snow detection product category and the target product to be produced is a normalized difference water index product, a normalized difference water index product production model is used to produce the product based on the first near-infrared band reflectance and the first green band reflectance to obtain the normalized difference water index product; When the category of the target product to be produced is a water and ice and snow detection product category and the target product to be produced is a turbid water index product, a turbid water index product production model is used to produce the product based on the reflectivity of the first red light band and the reflectivity of the first shortwave infrared band to obtain the turbid water index product; When the category of the target product to be produced is a water body and ice and snow detection product category and the target product to be produced is a cyanobacteria and macro-aquatic plant index product, a cyanobacteria and macro-aquatic plant index product production model is used to produce the product based on the first green band reflectivity, the blue band reflectivity, and the first shortwave infrared band reflectivity to obtain the cyanobacteria and macro-aquatic plant index product; When the category of the target product to be produced is a water and ice and snow detection product category and the target product to be produced is a phytoplankton index product, a phytoplankton index product production model is used to produce the product based on the first near-infrared band reflectivity, the first red light band reflectivity, and the first short-wave infrared band reflectivity to obtain the phytoplankton index product; When the category of the target product to be produced is the category of water body and ice and snow detection products and the target product to be produced is a normalized difference snow index product, the normalized difference snow index product production model is used to produce the product based on the first green band reflectivity and the first shortwave infrared band reflectivity to obtain the normalized difference snow index product.

7. The method according to claim 1, wherein The step of producing a target product by adopting a product production model corresponding to the target product to be produced based on each of the reflectivities to obtain the target product comprises: When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a ferrous-ferric distribution product, a first ferrous-ferric distribution product production model is used to produce the product based on the first near-infrared band reflectivity, the second near-infrared band reflectivity, the third near-infrared band reflectivity and the second short-wave infrared band reflectivity to obtain the ferrous-ferric distribution product; or, a second ferrous-ferric distribution product production model is used to produce the product based on the first green band reflectivity, the second green band reflectivity, the yellow band reflectivity, the second red light band reflectivity and the first red light band reflectivity to obtain the ferrous-ferric distribution product; When the category of the target product to be produced is a geological exploration product category and the target product to be produced is an iron oxide index product, an iron oxide index product production model is used to produce the product based on the second near-infrared band reflectivity, the third near-infrared band reflectivity, the first near-infrared band reflectivity, the first short-wave infrared band reflectivity, and the third short-wave infrared band reflectivity to obtain the iron oxide index product; When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a laterite belt product, a first laterite belt product production model is used to produce the product based on the first shortwave infrared band reflectivity, the third shortwave infrared band reflectivity, and the second shortwave infrared band reflectivity to obtain the laterite belt product; or a second laterite belt product production model is used to produce the product based on the first green band reflectivity and the third shortwave infrared band reflectivity to obtain the laterite belt product; When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a ferrous silicate index product, a first ferrous silicate index product production model is used to produce the product based on the first short-wave infrared band reflectivity, the third short-wave infrared band reflectivity, and the second short-wave infrared band reflectivity to obtain the ferrous silicate index product; or a second ferrous silicate index product production model is used to produce the product based on the third short-wave infrared band reflectivity and the second short-wave infrared band reflectivity to obtain the ferrous silicate index product; When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a silicate mineral product, a silicate mineral product production model is used to produce the product based on the fourth shortwave infrared band reflectivity, the fifth shortwave infrared band reflectivity, the sixth shortwave infrared band reflectivity, and the seventh shortwave infrared band reflectivity to obtain the silicate mineral product; When the category of the target product to be produced is a geological exploration product category and the target product to be produced is an intermediate mud zone mineral product, an intermediate mud zone mineral product production model is used to produce the product based on the reflectivity of the second shortwave infrared band, the reflectivity of the fourth shortwave infrared band, and the reflectivity of the fifth shortwave infrared band to obtain the intermediate mud zone mineral product; When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a high-grade mudstone mineral product, a high-grade mudstone mineral product production model is used to produce the product based on the first short-wave infrared band reflectivity, the third short-wave infrared band reflectivity, the second short-wave infrared band reflectivity and the fourth short-wave infrared band reflectivity to obtain the high-grade mudstone mineral product.

8. The method according to claim 1, wherein The step of producing a target product by adopting a product production model corresponding to the target product to be produced based on each of the reflectivities to obtain the target product comprises: When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a montmorillonite index product, a montmorillonite index product production model is used to produce the product based on the reflectivity of the third shortwave infrared band, the reflectivity of the fourth shortwave infrared band, and the reflectivity of the fifth shortwave infrared band to obtain the montmorillonite index product; When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a muscovite index product, producing the product using a muscovite index product production model based on the reflectivity of the fourth shortwave infrared band and the reflectivity of the fifth shortwave infrared band to obtain the muscovite index product; When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a phenolic substance index product, a phenolic substance index product production model is used to produce the product based on the reflectivity of the second short-wave infrared band and the reflectivity of the fourth short-wave infrared band to obtain the phenolic substance index product; When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a foliation alteration index product, a foliation alteration index product production model is used to produce the product based on the second shortwave infrared band reflectivity, the fourth shortwave infrared band reflectivity, and the fifth shortwave infrared band reflectivity to obtain the foliation alteration index product; When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a propyl metamorphic index product, a propyl metamorphic index product production model is used to produce the product based on the reflectivity of the fifth shortwave infrared band, the reflectivity of the sixth shortwave infrared band, and the reflectivity of the seventh shortwave infrared band to obtain the propyl metamorphic index product; When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a hydroxyl-containing altered mineral index product, a hydroxyl-containing altered mineral index product production model is used to produce the product based on the third shortwave infrared band reflectivity, the second shortwave infrared band reflectivity, the fourth shortwave infrared band reflectivity, and the fifth shortwave infrared band reflectivity to obtain the hydroxyl-containing altered mineral index product; When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a kaolinite index product, the kaolinite index product production model is used to produce the product based on the third shortwave infrared band reflectivity, the second shortwave infrared band reflectivity, the fourth shortwave infrared band reflectivity, the fifth shortwave infrared band reflectivity and the sixth shortwave infrared band reflectivity to obtain the kaolinite index product.

9. A device for producing common products based on remote sensing data from the Geology-1 satellite, characterized in that: include: Acquisition module, used to obtain multispectral remote sensing image data of the Geology-1 satellite; A data extraction module is used to extract data based on the multispectral remote sensing image data for a target product to be produced, and obtain reflectances of different bands corresponding to the target product to be produced; A product production module, configured to produce a target product by adopting a product production model corresponding to the target product to be produced based on each of the reflectivities; The step of producing a target product by adopting a product production model corresponding to the target product to be produced based on each of the reflectivities to obtain the target product specifically includes: When the category of the target product to be produced is a geological exploration product category and the target product to be produced is an alunite mineral product, based on Carry out product production; When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a calcite mineral product, based on Carry out product production; When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a clay alteration index product, based on Carry out product production; When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a dolomite index product, based on Carry out product production; When the category of the target product to be produced is a geological exploration product category and the target product to be produced is an epidote index product, a chlorite index product, and an amphibole index product, based on Carry out product production; When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a magnesite index product, based on Carry out product production; When the category of the target product to be produced is a geological exploration product category and the target product to be produced is a carbonate abundance index product, based on Carry out product production; in, 、 、 、 、 as well as They are all shortwave infrared spectrum bands of the Address-1 satellite, and the band reflectivities are 1630-1670nm, 2130-2170nm, 2190-2230nm, 2250-2290nm, 2320-2360nm and 2400-2480nm respectively.

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