Rice cultivation and area estimation methods integrating phenological and remote sensing big data

Abstract

This invention relates to the field of remote sensing technology, and more particularly to a method for estimating rice planting area by integrating phenological data and remote sensing big data. The method includes: acquiring high temporal and spatial resolution remote sensing images of rice at different growth stages; calculating the normalized vegetation index (NDI) and normalized water index (NDI) of rice at different growth stages based on the remote sensing images; establishing phenological curves for rice based on the NDI of rice at different growth stages; preliminarily determining the rice planting area based on the phenological curves; determining the normalized rice index for each growth stage based on the NDI and NDI of rice at different growth stages; determining the rice information index based on the normalized rice index for each growth stage; and calculating the rice area within the planting area based on the rice information index. This invention addresses the deficiency in existing technologies that cannot accurately obtain rice planting areas and areas.

Description

Technical Field

[0001] This invention relates to the field of remote sensing technology, and in particular to a method for estimating rice planting area by integrating phenology and remote sensing big data. Background Technology

[0002] The planting area and acreage of rice vary from year to year, mainly influenced by factors such as climate conditions, water resource supply, and food supply. Therefore, accurately determining the rice planting area is crucial for food security and sustainable development.

[0003] Remote sensing satellites, due to their wide coverage, objectivity, and speed, provide an effective means for large-scale rice monitoring. Currently, methods for estimating rice planting area using remote sensing technology mainly include: traditional classification methods such as supervised or unsupervised classification methods, artificial intelligence extraction methods, rice index extraction methods, and time series extraction methods.

[0004] Among these methods, supervised and unsupervised classification are relatively mature, but their accuracy is greatly limited by the influence of "different spectra for the same object" and "different objects for the same spectrum." Artificial intelligence extraction methods generally have high accuracy, but often require a large number of samples, especially for rice extraction over large areas, necessitating sample selection based on regional phenology. However, due to the difficulty of sample selection, differences in radiometric, spectral, and spatial scale of remote sensing images, rice extraction involves significant uncertainty and difficulty. Remote sensing index extraction methods for rice are relatively simple and computationally less demanding, primarily targeting thematic information extraction; however, due to the complexity of ground cover spectra and the current uncertainty of remote sensing indices, the accuracy of the extraction results is highly uncertain. Time series methods have the advantage of combining the differences in rice growth stages with other vegetation types, achieving high accuracy in identifying rice planting information; however, the difficulty of data acquisition and the differences in the types of remote sensing indices used also introduce some uncertainty. Summary of the Invention

[0005] This invention provides a method for estimating rice planting area by integrating phenological and remote sensing big data, in order to solve the shortcomings of existing technologies that cannot accurately obtain rice planting areas and areas.

[0006] This invention provides a method for rice cultivation and area estimation that integrates phenological and remote sensing big data, including:

[0007] High temporal and spatial resolution remote sensing images of rice at different growth stages are acquired, and the normalized vegetation index and normalized water index of rice at different growth stages are calculated based on the remote sensing images.

[0008] Phenological curves of rice were established based on the normalized vegetation index at different growth stages of the rice.

[0009] The planting area of ​​the rice was initially determined based on the phenological curve.

[0010] The normalized rice index at each growth stage is determined based on the normalized vegetation index and normalized water index of the rice at different growth stages.

[0011] The rice information index is determined based on the normalized rice index at each growth stage of the rice.

[0012] The area of ​​rice in the planting area is calculated based on the rice information index.

[0013] According to the present invention, a method for rice cultivation and area estimation based on integrated phenological and remote sensing big data, wherein the preliminary determination of the rice planting area based on the phenological curve includes:

[0014] The crop identification index is determined based on the normalized vegetation index of the remote sensing image and the phenological curve.

[0015] If the crop identification index is greater than or equal to a set threshold, the planting area of ​​the remote sensing image is initially determined.

[0016] According to the present invention, a method for rice cultivation and area estimation based on integrated phenological and remote sensing big data is provided. The crop identification index is determined based on the normalized vegetation index of the remote sensing image and the phenological curve, calculated using the following formula:

[0017] ;

[0018] Wherein, CRI represents the Crop Identification Index, and NDVI... i The normalized vegetation index represents the i-th scene of the remote sensing image; i represents the i-th scene of the remote sensing image; n1 represents the number of scenes in the remote sensing image. The mean of the normalized vegetation index represents the phenological curve.

[0019] According to the present invention, a method for estimating rice planting and its area based on integrated phenological and remote sensing big data includes determining the normalized rice index at each growth stage based on the normalized vegetation index and normalized water index of the rice at different growth stages, comprising:

[0020] The rice information extraction index for each growth stage of the rice is determined based on the normalized vegetation index and normalized water index at different growth stages of the rice.

[0021] Based on the rice information extraction index measured during the growth period, and the maximum and minimum values ​​of the rice information extraction index during the growth period, the normalized rice index for each growth period is determined.

[0022] According to the present invention, a method for estimating rice planting and its area based on integrated phenological and remote sensing big data is provided. The method involves determining the rice information extraction index for each growth stage of the rice based on the normalized vegetation index and normalized water index at different growth stages of the rice, calculated using the following formula:

[0023] ;

[0024] in, NDVI represents the normalized vegetation index at different growth stages, and NDWI represents the normalized water index at different growth stages.

[0025] The normalized rice index for each growth stage is determined based on the rice information extraction index measured during the growth period, and the maximum and minimum values ​​of the rice information extraction index during the growth period, and is calculated using the following formula:

[0026] ;

[0027] Among them, DNRI is the normalized rice index, with a value range of 0-1; This represents the maximum value of the rice information extraction index; This represents the minimum value of the rice information extraction index. Information extraction index of rice observed during the growing season.

[0028] According to the present invention, a method for estimating rice planting and its area based on integrated phenological and remote sensing big data, wherein determining the rice information index based on the normalized rice index at each growth stage includes:

[0029] The rice maturity index is determined based on the normalized rice index at the maturity stage, the normalized rice index at at least one growth stage excluding the maturity stage, and the time points of the rice at the transplanting and maturity stages.

[0030] Based on the normalized rice index at the maturity stage, the normalized rice index at the transplanting stage, the normalized rice index at at least one growth stage excluding the maturity and transplanting stages, and the time points of the rice at the transplanting and maturity stages, the crop growth line index of the rice is determined.

[0031] The rice information index for the target growth stage is determined based on the rice maturity index and the crop growth line index.

[0032] According to the present invention, a method for estimating rice planting area based on integrated phenological and remote sensing big data is provided. The method determines the rice maturity index based on the normalized rice index at the maturity stage, the normalized rice index at at least one growth stage excluding the maturity stage, and the time points of the rice at the transplanting and maturity stages, using the following formula:

[0033] ;

[0034] Among them, RGI in DNRI represents the rice maturity index. tn The normalized rice index (DNRI) represents the rice maturity period; tn is the time node of maturity; t1 is the time node of transplanting; DNRI i Normalized index of rice at different growth stages; This represents the i-th time period; i represents the number of time nodes, and n represents the number of time nodes in the maturity stage.

[0035] The crop growth line index of rice is determined based on the normalized rice index at the maturity stage, the normalized rice index at the transplanting stage, the normalized rice index at at least one growth stage excluding the maturity and transplanting stages, and the time points of the rice at the transplanting and maturity stages, and is calculated using the following formula:

[0036] ;

[0037] Wherein, RMI represents the crop growth line index; DNRI tn Normalized Difference Rice Index (DNRI) represents the rice's maturity period. t1 The normalized rice index (DNRI) represents the rice transplanting period; t represents the maturity date; t1 represents the transplanting date; DNRI i Normalized index of rice at different growth stages; This represents the i-th time period; i represents the number of time nodes, and n represents the number of time nodes in the maturity stage.

[0038] According to the present invention, a method for estimating rice planting area based on integrated phenological and remote sensing big data, wherein calculating the rice area in the planting area based on the rice information index includes:

[0039] The rice proportion index of remote sensing pixels is determined based on the rice information index and the preset threshold.

[0040] The area of ​​rice in the planting area is calculated based on the area of ​​each pixel within the planting area and the rice proportion index of the remote sensing pixels.

[0041] This invention also provides a device for estimating rice planting area by integrating phenological and remote sensing big data, comprising:

[0042] The data calculation module is used to acquire high temporal and high spatial resolution remote sensing images of rice at different growth stages, and calculate the normalized vegetation index and normalized water index of rice at different growth stages based on the remote sensing images.

[0043] The phenological curve establishment module is used to establish the phenological curve of rice based on the normalized vegetation index at different growth stages of the rice.

[0044] The planting area determination module is used to preliminarily determine the planting area of ​​the rice based on the phenological curve.

[0045] The normalized rice index determination module is used to determine the normalized rice index of rice at each growth stage based on the normalized vegetation index and normalized water index of rice at different growth stages.

[0046] The rice information index determination module is used to determine the rice information index based on the normalized rice index of the rice at each growth stage.

[0047] An area calculation module is used to calculate the area of ​​rice in the planting area based on the rice information index.

[0048] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the rice planting and area estimation method based on integrated phenology and remote sensing big data as described above.

[0049] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the rice planting and area estimation method based on integrated phenology and remote sensing big data as described above.

[0050] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the rice planting and area estimation method based on integrated phenology and remote sensing big data as described above.

[0051] The present invention provides a method for estimating rice planting area based on integrated phenological and remote sensing big data. This method establishes phenological curves for rice based on the normalized vegetation index (NDI) at different growth stages; preliminarily determines the rice planting area based on the phenological curves; then, based on the phenological information of rice at different growth stages, determines the rice planting area from high temporal and spatial resolution remote sensing images; furthermore, it calculates a rice information index based on the NDI and NDI at different growth stages; and finally, it calculates the area of ​​rice in the planting area based on the rice information index. Thus, the present invention achieves accurate identification of rice planting areas and areas based on rice phenological information and high temporal and spatial resolution remote sensing images. Attached Figure Description

[0052] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0053] Figure 1 This is a flowchart illustrating the rice planting and area estimation method based on integrated phenological and remote sensing big data provided by the present invention.

[0054] Figure 2 This is a schematic diagram of the structure of the rice planting and area estimation device that integrates phenology and remote sensing big data provided by the present invention;

[0055] Figure 3 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0056] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0057] The following is combined with Figure 1 This invention describes a method for estimating rice planting area based on integrated phenological and remote sensing big data. Please refer to [link / reference]. Figure 1 The methods for estimating rice planting and its area by integrating phenological and remote sensing big data include:

[0058] Step 100: Obtain high temporal and spatial resolution remote sensing images of rice at different growth stages, and calculate the normalized vegetation index and normalized water index of rice at different growth stages based on the remote sensing images.

[0059] The electronic device acquires high temporal and spatial resolution remote sensing images of rice at different growth stages, and calculates the normalized vegetation index and normalized water index of rice at different growth stages based on the remote sensing images. Different growth stages can include various periods in the rice growth process, such as the transplanting stage, canopy closure stage, jointing stage, grain-filling stage, and milk-ripe stage.

[0060] High temporal resolution refers to a short minimum time interval between two adjacent remote sensing observations of the same area. In this invention, the minimum time interval between two adjacent remote sensing observations of the same area in high temporal resolution remote sensing imagery is a time resolution of days, hours, or minutes. High spatial resolution refers to a small ground area represented by a single pixel in a remote sensing image, i.e., a small instantaneous field of view of the scanner, or a small minimum unit that ground objects can be resolved, but the remote sensing image has a large number of pixels. In this invention, a single pixel of a high temporal resolution remote sensing imagery can be a ground area of ​​30 meters by 30 meters, etc.

[0061] Electronic equipment calculates the normalized vegetation index and normalized water index of rice at different growth stages based on the reflectance of multiple bands in remote sensing images at different growth stages.

[0062] Specifically, the Normalized Difference Vegetation Index (NDVI) can be calculated based on the reflectance in the near-infrared band and the red band of remote sensing images. The NDVI calculation formula in this embodiment of the invention is as follows:

[0063] ;Formula (1)

[0064] In formula (1), Normalized Difference Vegetation Index (NDVI) For near-infrared reflectivity, The reflectivity is in the red band.

[0065] The normalized water index can be calculated based on the reflectance in the near-infrared band and the green band of remote sensing images. The formula for calculating the normalized water index in this embodiment of the invention is as follows:

[0066] ;Formula (2)

[0067] In formula (2), NDWI is the normalized water index. The reflectivity is for the green band.

[0068] Step 200: Establish the phenological curves of rice based on the normalized vegetation index at different growth stages of the rice.

[0069] The electronic device establishes phenological curves for rice based on the Normalized Difference Vegetation Index (NDVI) at different growth stages. Based on the NDVI obtained in the above steps for different growth stages of rice, phenological curves for rice are established. These phenological curves include growth characteristic curves for the rice transplanting stage, canopy closure stage, jointing stage, grain-filling stage, and milk-ripe stage. The phenological curves are plotted with time and the NDVI on the horizontal and vertical axes.

[0070] Step 300: Based on the phenological curve, preliminarily determine the planting area of ​​the rice;

[0071] The electronic device preliminarily determines the rice planting area based on the phenological curve. Specifically, the electronic device can determine the rice planting area based on the mean of the normalized vegetation index (NDI) at different growth stages in the phenological curve. Since the phenological curve indicates the characteristics of rice at different growth stages, preliminarily determining the rice planting area based on the phenological curve is beneficial for more accurately extracting the planting area from remote sensing images.

[0072] Step 400: Determine the normalized rice index for each growth stage of the rice based on the normalized vegetation index and normalized water index for different growth stages of the rice.

[0073] The electronic device calculates the rice information extraction index for each growth stage based on the normalized vegetation index and normalized water index of the rice at different growth stages. Then, it determines the normalized rice index for each growth stage based on the rice information extraction index.

[0074] Step 500: Determine the rice information index based on the normalized rice index at each growth stage of the rice.

[0075] Specifically, electronic devices can determine the rice maturity index and the rice crop growth line index based on the normalized rice index at each growth stage, and then determine the rice information index based on the rice maturity index and the rice crop growth line index.

[0076] Step 600: Calculate the area of ​​rice in the planting area based on the rice information index.

[0077] The electronic device calculates the area of ​​rice in the planting area based on the rice information index. Specifically, the electronic device calculates the rice proportion estimation index for remote sensing pixels based on the rice information index. The area of ​​the planting area is calculated based on the area of ​​each pixel in the planting area and the rice proportion estimation index for remote sensing pixels.

[0078] This invention establishes phenological curves for rice based on the normalized vegetation index (NDI) at different growth stages; preliminarily determines the rice planting area based on the phenological curves; then, based on the phenological information of rice at different growth stages, determines the rice planting area from high temporal and spatial resolution remote sensing images; furthermore, it calculates a rice information index based on the NDI and NDI at different growth stages; and finally, it calculates the area of ​​rice in the planting area based on the rice information index. Thus, this invention achieves accurate identification of rice planting areas and areas based on rice phenological information and high temporal and spatial resolution remote sensing images.

[0079] In one embodiment, step 300, preliminarily determining the rice planting area based on the phenological curve, includes:

[0080] Step 310: Determine the crop identification index based on the normalized vegetation index of the remote sensing image and the phenological curve;

[0081] Specifically, the electronic device determines the crop identification index based on the normalized vegetation index of the remote sensing image and the phenological curve, calculated using the following formula:

[0082] ;Formula (3)

[0083] Wherein, CRI represents the Crop Identification Index, and NDVI... i The normalized vegetation index represents the i-th scene of the remote sensing image; i represents the i-th scene of the remote sensing image; n1 represents the number of scenes in the remote sensing image. The mean of the normalized vegetation index represents the phenological curve.

[0084] For example, when the remote sensing image shows the rice transplanting period, formula (3)... This represents the mean of the normalized vegetation index (NDI) of the phenological curve at the transplanting stage. A crop identification index is calculated based on the NDI of the remote sensing image and the mean of the NDI of the phenological curve at the transplanting stage.

[0085] Step 320: If the crop identification index is greater than or equal to a set threshold, the planting area of ​​the remote sensing image is initially determined.

[0086] when When the crop identification index is greater than a set threshold, the pixels are identified as rice-grown, and the area formed by these pixels is defined as the rice-grown area in the remote sensing image. a4 can be set according to actual conditions; a specific value is not limited here.

[0087] Thus, phenological curves of rice are established based on the normalized vegetation index at different growth stages of the rice; the planting area of ​​the rice is preliminarily determined based on the phenological curves; and the planting area of ​​rice is determined from remote sensing images with high temporal and spatial resolution based on the phenological information of rice at different growth stages.

[0088] In one embodiment, step 400, determining the normalized rice index at each growth stage of the rice based on the normalized vegetation index and normalized water index at different growth stages of the rice, includes:

[0089] Step 410: Determine the rice information extraction index for each growth stage of the rice based on the normalized vegetation index and normalized water index for different growth stages of the rice.

[0090] Specifically, the formula for calculating the rice information extraction index is as follows:

[0091] ;Formula (4)

[0092] In formula (4), NDVI represents the normalized vegetation index at different growth stages, and NDWI represents the normalized water index at different growth stages.

[0093] Step 420: Based on the rice information extraction index measured during the growth period, and the maximum and minimum values ​​of the rice information extraction index during the growth period, determine the normalized rice index for each growth period.

[0094] Specifically, the formula for calculating the normalized rice index is as follows:

[0095] ;Formula (5)

[0096] In formula (5), DNRI is the normalized rice index, which ranges from 0 to 1; This represents the maximum value of the rice information extraction index; This represents the minimum value of the rice information extraction index. Information extraction index of rice observed during the growing season.

[0097] For example, when it is necessary to calculate the rice information extraction index during the rice transplanting period, the normalized rice index for the transplanting period is calculated based on the maximum value, minimum value and actual observed rice information extraction index during the transplanting period.

[0098] Specifically, step 500, determining the rice information index based on the normalized rice index at each growth stage of the rice, includes:

[0099] Step 510: Based on the normalized rice index at the maturity stage, the normalized rice index at at least one growth stage excluding the maturity stage, and the time nodes of the rice at the transplanting and maturity stages, determine the rice maturity index.

[0100] Based on the normalized rice index at maturity, the normalized rice index for at least one growth stage excluding maturity, and the time points of the rice at transplanting and maturity, the rice maturity index is determined using the following formula:

[0101] ;Formula (6)

[0102] In formula (6), RGI in DNRI represents the rice maturity index. tn The normalized rice index (DNRI) represents the rice maturity period; tn is the time node of maturity; t1 is the time node of transplanting; DNRI i Normalized index of rice at different growth stages; This represents the i-th time period; i represents the number of time nodes, and n represents the number of time nodes in the maturity stage.

[0103] For example, this invention includes the transplanting period, canopy closure period, jointing period, grain filling period, and milk-ripe period of rice. The rice maturity index is calculated by combining the normalized rice index of the transplanting period, canopy closure period, jointing period, grain filling period, and milk-ripe period of rice using formula (6).

[0104] Step 520: Based on the normalized rice index at the maturity stage, the normalized rice index at the transplanting stage, the normalized rice index at at least one growth stage excluding the maturity and transplanting stages, and the time nodes of the rice at the transplanting and maturity stages, determine the crop growth line index of the rice.

[0105] Specifically, based on the normalized rice index at the maturity stage, the normalized rice index at the transplanting stage, the normalized rice index for at least one growth stage excluding the maturity and transplanting stages, and the time points of the rice at the transplanting and maturity stages, the crop growth line index of the rice is determined and calculated using the following formula:

[0106] ;Formula (7)

[0107] In formula (7), RMI represents the crop growth line index; DNRI tn Normalized Difference Rice Index (DNRI) represents the rice's maturity period. t1The normalized rice index (DNRI) represents the rice transplanting period; t represents the maturity date; t1 represents the transplanting date; DNRI i Normalized index of rice at different growth stages; This represents the i-th time period; i represents the number of time nodes, and n represents the number of time nodes in the maturity stage.

[0108] For example, this invention includes the transplanting period, canopy closure period, jointing period, grain-filling period, and milk-ripe period of rice. The crop growth line index of rice is calculated by combining the normalized rice index of the transplanting period, canopy closure period, jointing period, grain-filling period, and milk-ripe period of rice using formula (7). Among them, the maturity period specifically refers to the milk-ripe period.

[0109] Step 530: Determine the rice information index of the rice at the target growth stage based on the rice maturity index and the crop growth line index.

[0110] The electronic device determines the rice information index of the rice at the target growth stage based on the rice maturity index and the crop growth line index. Specifically, the rice information index of the rice at the target growth stage is determined based on the quotient of the rice maturity index and the crop growth line index. This is expressed by formula (8):

[0111] ;Formula (8)

[0112] In formula (8), RGI is the rice information index. in is the rice maturity index, and RMI is the crop growth line index.

[0113] It should be noted that when It can be identified as rice. a5 can be set according to the actual situation; a specific value is not limited here.

[0114] In one embodiment, step 600, calculating the area of ​​rice in the planting area based on the rice information index, includes:

[0115] Step 610: Determine the rice proportion index of remote sensing pixels based on the rice information index and the preset threshold;

[0116] Specifically, the rice proportion index in remote sensing pixels is calculated using the following formula:

[0117] ;Formula (9)

[0118] In formula (9), , where A is the rice proportion index in remote sensing pixels, and A is the preset threshold.

[0119] Step 620: Calculate the area of ​​rice in the planting area based on the area of ​​each pixel in the planting area and the rice proportion index of the remote sensing pixel.

[0120] Specifically, the planting area is calculated using the following formula:

[0121] ;Formula (10)

[0122] In formula (10), S is the rice planting area; Let be the area of ​​the pixel in the i-th row and j-th column.

[0123] The rice information index is calculated based on the normalized vegetation index and normalized water index at different growth stages of the rice; and the area of ​​the rice in the planting area is calculated based on the rice information index. Thus, the present invention achieves accurate identification of rice planting areas and areas based on rice phenological information and remote sensing images with high temporal and spatial resolution.

[0124] The following describes the rice planting and area estimation device based on integrated phenology and remote sensing big data provided by the present invention. The rice planting and area estimation device based on integrated phenology and remote sensing big data described below can be referred to in correspondence with the rice planting and area estimation method based on integrated phenology and remote sensing big data described above.

[0125] Please refer to Figure 2 The present invention also provides a device for estimating rice planting area by integrating phenological and remote sensing big data, comprising:

[0126] The data calculation module 201 is used to acquire high temporal and high spatial resolution remote sensing images of rice at different growth stages, and calculate the normalized vegetation index and normalized water index of rice at different growth stages based on the remote sensing images.

[0127] The phenological curve establishment module 202 is used to establish the phenological curve of rice based on the normalized vegetation index of different growth stages of the rice.

[0128] The planting area determination module 203 is used to preliminarily determine the planting area of ​​the rice based on the phenological curve.

[0129] The normalized rice index determination module 204 is used to determine the normalized rice index of rice at each growth stage based on the normalized vegetation index and normalized water index of rice at different growth stages.

[0130] The rice information index determination module 205 is used to determine the rice information index based on the normalized rice index of the rice at each growth stage.

[0131] The area calculation module 206 is used to calculate the area of ​​rice in the planting area based on the rice information index.

[0132] The rice planting and area estimation device of the present invention, which integrates phenological and remote sensing big data, establishes phenological curves of rice based on normalized vegetation indices (NDI) at different growth stages of rice; preliminarily determines the rice planting area based on the phenological curves; thereby determining the rice planting area from high temporal and spatial resolution remote sensing images based on phenological information of rice at different growth stages; calculates a rice information index based on the NDI and NDI at different growth stages of rice; and calculates the area of ​​rice in the planting area based on the rice information index. Thus, the present invention achieves accurate identification of rice planting areas and areas based on rice phenological information and high temporal and spatial resolution remote sensing images.

[0133] In one embodiment, the planting area determination module includes:

[0134] The crop identification index determination module is used to determine the crop identification index based on the normalized vegetation index of the remote sensing image and the phenological curve;

[0135] The final planting area determination module is used to initially determine the planting area of ​​the remote sensing image when the crop identification index is greater than or equal to a set threshold.

[0136] In one embodiment, the crop identification index determination module calculates the index using the following formula:

[0137] ;

[0138] Wherein, CRI represents the Crop Identification Index, and NDVI... i The normalized vegetation index represents the i-th scene of the remote sensing image; i represents the i-th scene of the remote sensing image; n1 represents the number of scenes in the remote sensing image. The mean of the normalized vegetation index represents the phenological curve.

[0139] In one embodiment, the normalized rice index determination module includes:

[0140] The rice information extraction index determination module is used to determine the rice information extraction index for each growth stage of the rice based on the normalized vegetation index and normalized water index for different growth stages of the rice.

[0141] The final normalized rice index determination module is used to determine the normalized rice index of rice in each growth stage based on the rice information extraction index measured during the growth period, and the maximum and minimum values ​​of the rice information extraction index during the growth period.

[0142] In one embodiment, the rice information extraction index determination module calculates it using the following formula:

[0143] ;

[0144] in, NDVI represents the normalized vegetation index at different growth stages, and NDWI represents the normalized water index at different growth stages.

[0145] The final normalized rice index determination module calculates it using the following formula:

[0146] ;

[0147] Among them, DNRI is the normalized rice index, with a value range of 0-1; This represents the maximum value of the rice information extraction index; This represents the minimum value of the rice information extraction index. Information extraction index of rice observed during the growing season.

[0148] In one embodiment, the rice information index determination module includes:

[0149] The rice maturity index determination module is used to determine the rice maturity index based on the normalized rice index of the rice at the maturity stage, the normalized rice index of at least one growth stage excluding the maturity stage, and the time nodes of the rice at the transplanting stage and the maturity stage respectively.

[0150] The crop growth line index determination module is used to determine the crop growth line index of rice based on the normalized rice index of rice at the maturity stage, the normalized rice index of rice at the transplanting stage, the normalized rice index of rice at at least one growth stage excluding the maturity stage and the transplanting stage, and the time nodes of rice at the transplanting stage and the maturity stage respectively.

[0151] The final rice information index determination module is used to determine the rice information index of the rice at the target growth stage based on the rice maturity index and the crop growth line index.

[0152] In one embodiment, the rice maturity index determination module calculates it using the following formula:

[0153] ;

[0154] Among them, RGI in DNRI represents the rice maturity index. tn The normalized rice index (DNRI) represents the rice maturity period; tn is the time node of maturity; t1 is the time node of transplanting; DNRIi Normalized index of rice at different growth stages; This represents the i-th time period; i represents the number of time nodes, and n represents the number of time nodes in the maturity stage.

[0155] The crop growth line index determination module calculates it using the following formula:

[0156] ;

[0157] Wherein, RMI represents the crop growth line index; DNRI tn Normalized Difference Rice Index (DNRI) represents the rice's maturity period. t1 The normalized rice index (DNRI) represents the rice transplanting period; t represents the maturity date; t1 represents the transplanting date; DNRI i Normalized index of rice at different growth stages; This represents the i-th time period; i represents the number of time nodes, and n represents the number of time nodes in the maturity stage.

[0158] According to the present invention, a rice planting and area estimation device integrating phenology and remote sensing big data is provided, wherein the area calculation module includes:

[0159] The remote sensing pixel rice proportion index determination module is used to determine the remote sensing pixel rice proportion index based on the rice information index and a preset threshold.

[0160] The final area determination module is used to calculate the area of ​​rice in the planting area based on the area of ​​each pixel in the planting area and the rice proportion index of the remote sensing pixel.

[0161] Figure 3 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 3As shown, the electronic device may include: a processor 310, a communication interface 320, a memory 330, and a communication bus 340, wherein the processor 310, the communication interface 320, and the memory 330 communicate with each other through the communication bus 340. The processor 310 can call logical instructions in the memory 330 to execute a method for estimating rice planting area based on integrated phenological and remote sensing big data. This method includes: acquiring high temporal and spatial resolution remote sensing images of rice at different growth stages; calculating the normalized vegetation index (NDI) and normalized water index (NDI) of rice at different growth stages based on the remote sensing images; establishing phenological curves for rice based on the NDI of rice at different growth stages; preliminarily determining the rice planting area based on the phenological curves; determining the normalized rice index for each growth stage based on the NDI and NDI of rice at different growth stages; determining the rice information index based on the normalized rice index for each growth stage; and calculating the area of ​​rice in the planting area based on the rice information index.

[0162] Furthermore, the logical instructions in the aforementioned memory 330 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, essentially, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0163] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the rice planting and area estimation method based on the comprehensive phenological and remote sensing big data provided by the above methods. The method includes: acquiring high temporal and spatial resolution remote sensing images of rice at different growth stages, and calculating the normalized vegetation index and normalized water index of rice at different growth stages based on the remote sensing images; establishing a phenological curve of rice based on the normalized vegetation index of rice at different growth stages; preliminarily determining the planting area of ​​rice based on the phenological curve; determining the normalized rice index of rice at each growth stage based on the normalized vegetation index and normalized water index of rice at different growth stages; determining the rice information index based on the normalized rice index of rice at each growth stage; and calculating the area of ​​rice in the planting area based on the rice information index.

[0164] In another aspect, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon. When executed by a processor, the computer program implements a method for estimating rice planting and its area based on comprehensive phenological and remote sensing big data provided by the methods described above. This method includes: acquiring high temporal and spatial resolution remote sensing images of rice at different growth stages; calculating normalized vegetation index and normalized water index of rice at different growth stages based on the remote sensing images; establishing phenological curves of rice based on the normalized vegetation index of rice at different growth stages; preliminarily determining the planting area of ​​rice based on the phenological curves; determining the normalized rice index of rice at each growth stage based on the normalized vegetation index and normalized water index of rice at different growth stages; determining a rice information index based on the normalized rice index of rice at each growth stage; and calculating the area of ​​rice in the planting area based on the rice information index.

[0165] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0166] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0167] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for estimating rice planting area by integrating phenological and remote sensing big data, characterized in that, include: High temporal and spatial resolution remote sensing images of rice at different growth stages are acquired, and the normalized vegetation index and normalized water index of rice at different growth stages are calculated based on the remote sensing images. Phenological curves of rice were established based on the normalized vegetation index at different growth stages of the rice. The planting area of ​​the rice was initially determined based on the phenological curve. The normalized rice index at each growth stage is determined based on the normalized vegetation index and normalized water index of the rice at different growth stages. The rice information index is determined based on the normalized rice index at each growth stage of the rice. The area of ​​rice in the planting area is calculated based on the rice information index; The step of determining the rice information index based on the normalized rice index at each growth stage includes: determining the rice information index at the target growth stage based on the rice maturity index and the crop growth line index of the rice, calculated using the following formula: ； RGI stands for Rice Information Index; in The rice maturity index is represented by the RMI (Rice Growth Line Index). The step of calculating the area of ​​rice in the planting area based on the rice information index includes: determining the rice proportion index of remote sensing pixels based on the rice information index and a preset threshold; and calculating the area of ​​rice in the planting area based on the area of ​​each pixel in the planting area and the rice proportion index of remote sensing pixels. The rice proportion index of remote sensing pixels is determined based on the rice information index and a preset threshold, and is calculated using the following formula: ； in, , where A is the rice percentage index in remote sensing pixels, and A is the preset threshold. The area of ​​rice in the planting area is calculated based on the area of ​​each pixel within the planting area and the rice proportion index of the remote sensing pixels, using the following formula: ； Where S represents the rice planting area; Let M be the area of ​​the pixel in the i-th row and j-th column; M and N are the number of rows and columns of the pixel.

2. The method for estimating rice planting area based on integrated phenology and remote sensing big data according to claim 1, characterized in that, The preliminary determination of the rice planting area based on the phenological curve includes: The crop identification index is determined based on the normalized vegetation index of the remote sensing image and the phenological curve. If the crop identification index is greater than or equal to a set threshold, the planting area of ​​the remote sensing image is initially determined.

3. The method for estimating rice planting area based on integrated phenology and remote sensing big data according to claim 2, characterized in that, The crop identification index, determined based on the normalized vegetation index of the remote sensing image and the phenological curve, is calculated using the following formula: ； Wherein, CRI represents the Crop Identification Index, and NDVI... i The normalized vegetation index represents the i-th scene of the remote sensing image; i represents the i-th scene of the remote sensing image; n1 represents the number of scenes in the remote sensing image. The mean of the normalized vegetation index represents the phenological curve.

4. The method for estimating rice planting area based on integrated phenology and remote sensing big data according to claim 1, characterized in that, The determination of the normalized rice index at each growth stage based on the normalized vegetation index and normalized water index of the rice includes: The rice information extraction index for each growth stage of the rice is determined based on the normalized vegetation index and normalized water index at different growth stages of the rice. Based on the rice information extraction index measured during the growth period, and the maximum and minimum values ​​of the rice information extraction index during the growth period, the normalized rice index for each growth period is determined.

5. The method for estimating rice planting area based on integrated phenology and remote sensing big data according to claim 4, characterized in that, The rice information extraction index for each growth stage of the rice is determined based on the normalized vegetation index and normalized water index at different growth stages of the rice, and is calculated using the following formula: ； in, NDVI represents the normalized vegetation index at different growth stages, and NDWI represents the normalized water index at different growth stages. The normalized rice index for each growth stage is determined based on the rice information extraction index measured during the growth period, and the maximum and minimum values ​​of the rice information extraction index during the growth period, and is calculated using the following formula: ； Among them, DNRI is the normalized rice index, with a value range of 0-1; This represents the maximum value of the rice information extraction index; This represents the minimum value of the rice information extraction index. Information extraction index of rice observed during the growing season.

6. The method for estimating rice planting area based on integrated phenology and remote sensing big data according to claim 1, characterized in that, The determination of the rice information index based on the normalized rice index at each growth stage includes: The rice maturity index is determined based on the normalized rice index at the maturity stage, the normalized rice index at at least one growth stage excluding the maturity stage, and the time points of the rice at the transplanting and maturity stages. Based on the normalized rice index at the maturity stage, the normalized rice index at the transplanting stage, the normalized rice index at at least one growth stage excluding the maturity and transplanting stages, and the time points of the rice at the transplanting and maturity stages, the crop growth line index of the rice is determined. The rice information index for the target growth stage is determined based on the rice maturity index and the crop growth line index.

7. The method for estimating rice planting area based on integrated phenology and remote sensing big data according to claim 6, characterized in that, The rice maturity index is determined based on the normalized rice index at the maturity stage, the normalized rice index at at least one growth stage excluding the maturity stage, and the time points of the rice at the transplanting and maturity stages, and is calculated using the following formula: ； Among them, RGI in DNRI represents the rice maturity index. tn The normalized rice index (DNRI) represents the rice maturity period; tn is the time node of maturity; t1 is the time node of transplanting; DNRI i Normalized index of rice at different growth stages; This represents the i-th time period; i represents the number of time nodes, and n represents the number of time nodes in the maturity stage. The crop growth line index of rice is determined based on the normalized rice index at the maturity stage, the normalized rice index at the transplanting stage, the normalized rice index at at least one growth stage excluding the maturity and transplanting stages, and the time points of the rice at the transplanting and maturity stages, and is calculated using the following formula: ； Wherein, RMI represents the crop growth line index; DNRI tn Normalized Difference Rice Index (DNRI) represents the rice's maturity period. t1 The normalized rice index (DNRI) represents the rice transplanting period; tn represents the maturity date; t1 represents the transplanting date; DNRI i Normalized index of rice at different growth stages; This represents the i-th time period; i represents the number of time nodes, and n represents the number of time nodes in the maturity stage.

8. The method for estimating rice planting area based on integrated phenological and remote sensing big data according to claim 1, characterized in that, The calculation of the rice area in the planting region based on the rice information index includes: The rice proportion index of remote sensing pixels is determined based on the rice information index and the preset threshold. The area of ​​rice in the planting area is calculated based on the area of ​​each pixel within the planting area and the rice proportion index of the remote sensing pixels.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the rice planting and area estimation method based on integrated phenology and remote sensing big data as described in any one of claims 1 to 8.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the rice planting and area estimation method based on integrated phenological and remote sensing big data as described in any one of claims 1 to 8.

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