Vegetation status monitoring method, device and storage medium based on abundance value

Abstract

The present application discloses a vegetation status monitoring method, device and storage medium based on abundance value. The method includes: determining a plurality of first pixels corresponding to a predetermined area on the ground according to a satellite remote sensing reflection image generated based on a ground reflection spectrum signal; determining the vegetation abundance value of an end element corresponding to a vegetation feature type in the first pixel according to the spectrum characteristics corresponding to the first pixel; determining a second pixel corresponding to an edge of a vegetation area in the predetermined area according to the determined vegetation abundance value; determining a vegetation area according to the second pixel; and determining vegetation change status information in the predetermined area according to the determined vegetation area and pre-set reference area information, wherein the reference area is an area pre-determined in the predetermined area for planting vegetation.

Description

Technical Field

[0001] The present application relates to the field of satellite remote sensing technology, and in particular to a vegetation status monitoring method, device and storage medium based on abundance value. Background Art

[0002] Satellite remote sensing technology has been widely used in monitoring the state of the earth. For example, remote sensing images can be used to analyze changes in vegetation areas, such as changes in the area of ​​vegetation areas. In order to make statistics on the changes in the area of ​​vegetation areas, it is necessary to accurately determine the edges of vegetation areas.

[0003] The existing technology usually extracts the edge of the vegetation area from the remote sensing image through an image recognition model such as a neural network or an edge extraction model, and then determines the area of ​​the vegetation area. However, this recognition method can only make an accurate judgment when the edge of the vegetation area is clear.

[0004] However, in general, the edge of a vegetation area is always composed of mixed pixels containing multiple end members. Therefore, the edge of a vegetation area is usually unclear. Therefore, it is difficult to accurately extract the edge of a vegetation area through image recognition, and thus it is impossible to accurately evaluate the changes in vegetation areas.

[0005] With respect to the technical problem that the fuzzy edges of vegetation areas cannot be accurately identified by image recognition in the prior art, and thus changes in vegetation areas cannot be accurately assessed, no effective solution has been proposed so far. Summary of the invention

[0006] The embodiments of the present disclosure provide a vegetation status monitoring method, device and storage medium based on abundance value, so as to at least solve the technical problem in the prior art that the fuzzy edges of vegetation areas cannot be accurately identified through image recognition, and thus the changes in vegetation areas cannot be accurately evaluated.

[0007] According to one aspect of an embodiment of the present disclosure, a vegetation status monitoring method based on abundance value is provided, comprising: determining a plurality of first pixels corresponding to a predetermined area on the ground according to a satellite remote sensing reflection image generated based on a ground reflection spectral signal; determining a vegetation abundance value of an end pixel corresponding to a vegetation feature type in the first pixel according to a spectral feature corresponding to the first pixel; determining a second pixel corresponding to an edge of a vegetation area in the predetermined area according to the determined vegetation abundance value; determining the vegetation area according to the second pixel; and determining vegetation change status information in the predetermined area according to the determined vegetation area and pre-set reference area information, wherein the reference area is an area pre-determined in the predetermined area for planting vegetation.

[0008] According to another aspect of the embodiments of the present disclosure, a storage medium is further provided. The storage medium includes a stored program, wherein the above method is executed by a processor when the program is running.

[0009] According to another aspect of an embodiment of the present disclosure, a vegetation status monitoring device based on abundance value is also provided, including: a first pixel determination module, used to determine a plurality of first pixels corresponding to a predetermined area on the ground according to a satellite remote sensing reflection image generated based on a ground reflection spectral signal; a vegetation abundance value determination module, used to determine the vegetation abundance value of the end element corresponding to the vegetation feature type in the first pixel according to the spectral characteristics corresponding to the first pixel; a second pixel determination module, used to determine the second pixel corresponding to the edge of the vegetation area in the predetermined area according to the determined vegetation abundance value; a vegetation area determination module, used to determine the vegetation area according to the second pixel; and a vegetation change state determination module, used to determine the vegetation change state information in the predetermined area according to the determined vegetation area and pre-set reference area information, wherein the reference area is an area pre-determined in the predetermined area for planting vegetation.

[0010] According to another aspect of an embodiment of the present disclosure, a vegetation status monitoring device based on abundance value is also provided, including: a processor; and a memory connected to the processor, for providing the processor with instructions for processing the following processing steps: determining a plurality of first pixels corresponding to a predetermined area on the ground based on a satellite remote sensing reflection image generated based on a ground reflection spectral signal; determining a vegetation abundance value of an end element corresponding to a vegetation feature type in the first pixel based on a spectral feature corresponding to the first pixel; determining a second pixel corresponding to an edge of a vegetation area in the predetermined area based on the determined vegetation abundance value; determining the vegetation area based on the second pixel; and determining vegetation change status information in the predetermined area based on the determined vegetation area and pre-set reference area information, wherein the reference area is an area pre-determined in the predetermined area for planting vegetation.

[0011] In the embodiment of the present disclosure, the edge of the vegetation area is not identified by image recognition, but by analyzing the abundance value of the green vegetation end member in each pixel, and determining the edge of the vegetation area according to the abundance value. Therefore, compared with the image recognition method, the present disclosure can more accurately extract the edge of the vegetation image area based on the mixed pixels of the reflected remote sensing image, and then accurately determine the vegetation area in the predetermined area, so as to accurately evaluate the change of the vegetation area. It solves the technical problem that the fuzzy edge of the vegetation area cannot be accurately identified by the image recognition method in the prior art, and thus the change of the vegetation area cannot be accurately evaluated. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] The drawings described herein are used to provide a further understanding of the present disclosure and constitute a part of the present application. The illustrative embodiments of the present disclosure and their descriptions are used to explain the present disclosure and do not constitute an improper limitation on the present disclosure. In the drawings:

[0013] Figure 1 is a hardware structure block diagram of a computing device for implementing the method according to Embodiment 1 of the present disclosure;

[0014] Figure 2 is a flow chart of the vegetation status monitoring method based on abundance value according to Embodiment 1 of the present disclosure;

[0015] Figure 3 is a schematic diagram of a predetermined area as a monitoring object according to Embodiment 1 of the present disclosure;

[0016] Figure 4 is a schematic diagram of a satellite remote sensing reflection image corresponding to a predetermined area according to Embodiment 1 of the present disclosure;

[0017] Figure 5 is a schematic diagram of a ground area corresponding to a certain pixel according to Embodiment 1 of the present disclosure;

[0018] Figure 6 is a schematic diagram of a vegetation status monitoring device based on abundance value according to Embodiment 2 of the present disclosure; and

[0019] Figure 7 It is a schematic diagram of the vegetation status monitoring device based on abundance value described in Example 3 of the present disclosure. DETAILED DESCRIPTION

[0020] In order to enable those skilled in the art to better understand the technical solutions of the present disclosure, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only embodiments of a part of the present disclosure, not all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without making creative work should fall within the scope of protection of the present disclosure.

[0021] It should be noted that the terms "first", "second", etc. in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products, or devices.

[0022] Example 1

[0023] According to this embodiment, a method embodiment of a vegetation status monitoring method based on abundance values ​​is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0024] The method embodiment provided in this embodiment can be executed in a mobile terminal, a computer terminal, a server or a similar computing device. Figure 1 FIG. 1 shows a hardware structure block diagram of a computing device for implementing a vegetation status monitoring method based on abundance value. Figure 1 As shown, the computing device may include one or more processors (the processor may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory for storing data, a transmission device for communication functions, and an input / output interface. The memory, the transmission device, and the input / output interface are connected to the processor via a bus. In addition, it may also include: a display, a keyboard, and a cursor control device connected to the input / output interface. A person skilled in the art can understand that Figure 1 The structure shown is only for illustration and does not limit the structure of the above electronic device. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations shown.

[0025] It should be noted that the one or more processors and / or other data processing circuits described above may generally be referred to herein as "data processing circuitry". The data processing circuitry may be embodied in whole or in part as software, hardware, firmware, or any other combination thereof. In addition, the data processing circuitry may be a single independent processing module, or may be incorporated in whole or in part into any of the other components of the computing device. As involved in the embodiments of the present disclosure, the data processing circuitry acts as a processor control (e.g., selection of a variable resistor terminal path connected to an interface).

[0026] The memory can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the vegetation status monitoring method based on abundance value in the embodiment of the present disclosure. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, that is, the vegetation status monitoring method based on abundance value of the above-mentioned application is realized. The memory may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include a memory remotely arranged relative to the processor, and these remote memories may be connected to the computing device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0027] The transmission device is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of the computing device. In one example, the transmission device includes a network adapter (Network Interface Controller, NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device can be a radio frequency (Radio Frequency, RF) module, which is used to communicate with the Internet wirelessly.

[0028] The display may be, for example, a touch screen liquid crystal display (LCD) that may enable a user to interact with a user interface of the computing device.

[0029] It should be noted that, in some optional embodiments, the above Figure 1 The computing device shown may include hardware elements (including circuits), software elements (including computer code stored on a computer-readable medium), or a combination of both hardware elements and software elements. Figure 1 This is merely one example of a particular embodiment and is intended to illustrate the types of components that may be present in the computing devices described above.

[0030] Under the above operating environment, according to the first aspect of this embodiment, a vegetation status monitoring method based on abundance value is provided. The method comprises: Figure 1 The computing device implementation shown in . Figure 2 A schematic diagram showing the process of the method is shown in FIG. Figure 2 As shown, the method includes:

[0031] S202: determining a plurality of first pixels corresponding to a predetermined area on the ground according to a satellite remote sensing reflection image generated based on a ground reflection spectrum signal;

[0032] S204: determining a vegetation abundance value of an end member corresponding to the vegetation feature type in the first pixel according to the frequency spectrum feature corresponding to the first pixel;

[0033] S206: Determine, according to the determined vegetation abundance value, a second pixel corresponding to an edge of a vegetation area in a predetermined area;

[0034] S208: Determine a vegetation area according to the second pixel; and

[0035] S210: Determine vegetation change status information in a predetermined area according to the determined vegetation area and pre-set reference area information, wherein the reference area is an area predetermined in the predetermined area for planting vegetation.

[0036] Specifically, Figure 3 A schematic diagram of a predetermined area 100 as a monitoring object is shown, and the predetermined area 100 is, for example, a predetermined area on the ground and includes a vegetation area 110. Further, Figure 4 A schematic diagram of a satellite remote sensing reflection image 200 corresponding to the predetermined area 100 acquired from a satellite is shown.

[0037] A schematic diagram of a satellite remote sensing reflection image 200 corresponding to a predetermined area on the ground obtained by a computing device, wherein the satellite remote sensing reflection image 200 includes a vegetation image area 210 corresponding to the vegetation area 110. Figure 4 As shown, the satellite remote sensing reflection image 200 includes a plurality of pixels 201 (ie, the first pixels described in the claims).

[0038] The satellite remote sensing reflection image 200 can be obtained, for example, by a surface reflectivity sensor on a satellite. For example, a Landsat 8 OLI sensor can be set on the satellite, so that the satellite remote sensing reflection image 200 of the predetermined area 100 can be obtained by the Landsat 8 OLI sensor. Figure 1The computing device shown can obtain surface reflectance data of multiple different frequency bands for each pixel. For example, the OLI sensor of LANSAT 8 can provide surface reflectance data of 9 different bands, so the computing device can obtain surface reflectance data of 9 different bands for each pixel. Thus, the computing device can determine multiple pixels 201 (i.e., first pixels) corresponding to the predetermined area 100 according to the satellite remote sensing reflection image 200 (S202).

[0039] The pixels 201 in the remote sensing reflection image 200 include both end-members (i.e., pure pixels) and mixed pixels. An end-member refers to a pixel consisting of only one type of land object. For example, in the present embodiment, different land object types include five types of land objects: green vegetation, buildings, open space, agricultural land, and water bodies. Of course, those skilled in the art can also specify more land object types, which will not be described here. Thus, for example, an end-member may only include one type of land object, namely green vegetation, or only include one type of land object, namely buildings, which will not be described here.

[0040] A mixed pixel is a pixel that contains multiple different types of objects. For example, a pixel contains both green vegetation and open space, so it can be considered a mixed pixel of green vegetation and open space. In this mixed pixel, the end members of different object types occupy different areas, which can be represented by the abundance value of the end members.

[0041] Then, further, the computing device is directed to Figure 4 For each pixel 201 shown in FIG. 2 , the abundance value of the green vegetation end member in the pixel is calculated according to the spectrum characteristics corresponding to different frequency bands. That is, the area occupied by the green vegetation in the ground area corresponding to the pixel is calculated ( S204 ).

[0042] The spectral feature may be, for example, reflectivity data of different frequency bands corresponding to the pixel obtained by a surface reflectivity sensor, or reflectivity data of several spectra corresponding to the pixel obtained after principal component analysis. Thus, the computing device can determine the abundance value of the green vegetation endmember in each pixel based on the spectral features of each pixel. The method for determining the abundance value of the green vegetation endmember in each pixel will be described in detail below and will not be repeated here.

[0043] Then, the computing device determines the pixel 201c (i.e., the second pixel) corresponding to the edge of the vegetation image area 210 according to the abundance value of the green vegetation end member in each pixel of the satellite remote sensing reflection image 200. Specifically, according to this embodiment, the abundance values ​​of the green vegetation end members in the pixels of different image areas are also different. For example, for the pixel 201a in the vegetation image area, the abundance value of the green vegetation end member will be close to 100%, and for the pixel 201b in the non-vegetation image area, the abundance value of the green vegetation end member will be very low, even close to 0. Therefore, the pixel 201c corresponding to the edge of the vegetation image area 210 can be determined according to the abundance value of the green vegetation end member in the pixel 201 in the satellite remote sensing reflection image 200. For example, since the pixel 201c corresponding to the edge of the vegetation image area is likely to be a mixed pixel containing some green vegetation end elements, the pixel 201c (i.e., the second pixel) corresponding to the edge of the vegetation image area can be determined based on the pixels whose abundance values ​​of the green vegetation end elements are lower than a predetermined threshold.

[0044] Then, the computing device further determines the vegetation image region 210 surrounded by the pixel 201 c according to the determined pixel 201 c , thereby further determining the vegetation region 110 corresponding to the vegetation image region ( S208 ).

[0045] Then, the computing device further compares the determined vegetation area 110 with the preset reference area information. The reference area information may be, for example, land planning information made by a relevant department, which specifies the location, shape, area, and other information of the vegetation area in the predetermined area where vegetation should be planted. Thus, through the comparison, the computing device can determine the vegetation change state information of the actual vegetation area 110 relative to the reference area information (S210).

[0046] The vegetation change state information includes (but is not limited to): vegetation area change information (used to indicate whether the area of ​​the vegetation area has increased or decreased), vegetation degradation area information (used to indicate the vegetation degradation area), and vegetation expansion area information (used to indicate the vegetation expansion area information), etc. Thus, the vegetation area can be monitored through the above information.

[0047] As described in the background technology, usually, the edge of the vegetation area is always composed of mixed pixels containing multiple end members. Therefore, the edge of the vegetation area is usually unclear. Therefore, it is difficult to accurately extract the edge of the vegetation area by image recognition, and thus it is impossible to accurately evaluate the changes in the vegetation area.

[0048] In view of this, the technical solution proposed in the present disclosure is not to identify the edge of the vegetation area by image recognition, but to analyze the abundance value of the green vegetation end member in each pixel and determine the edge of the vegetation area according to the abundance value. Therefore, compared with the image recognition method, the present disclosure can more accurately extract the edge of the vegetation image area based on the mixed pixels of the reflected remote sensing image, and then accurately determine the vegetation area in the predetermined area, so as to accurately evaluate the change of the vegetation area. It solves the technical problem that the fuzzy edge of the vegetation area cannot be accurately identified by the image recognition method in the prior art, and thus the change of the vegetation area cannot be accurately evaluated.

[0049] Optionally, the operation of determining the vegetation abundance value of the end-member corresponding to the vegetation land object type in the first pixel based on the spectral characteristics corresponding to the first pixel includes: obtaining reference spectral characteristics corresponding to the end-members of different land object types; and determining the abundance value of the end-members of different land object types in the first pixel based on the reference spectral characteristics and the spectral characteristics corresponding to the first pixel.

[0050] Specifically, in the process of determining the vegetation abundance value of the green vegetation endmember in each pixel 201 of the satellite remote sensing reflection image 200, the computing device determines the abundance value of the endmember corresponding to different ground object types in the pixel 201 for each pixel 201 through the following operations.

[0051] First, for the pixel 201, the computing device obtains the frequency spectrum feature Fd corresponding to the pixel 201:

[0052] Fd=[fd1,fd2,...,fd m ] T

[0053] Among them, fd i (i=1-m) is the reflectivity data of different frequency bands corresponding to the pixel 201. The different frequency bands may be, for example, reflectivity data of different frequency bands generated by a surface reflectivity sensor, or reflectivity data of several frequency bands obtained after principal component analysis.

[0054] In this embodiment, the variables to be determined include the abundance values ​​corresponding to the end members of 5 different types of land objects, and an error term. Therefore, m≥6, that is, the number of parameters in the spectrum characteristics is at least 1 more than the number of end members of different types of land objects. In addition, in the following text, the frequency bands corresponding to the reference spectrum characteristics corresponding to the end members of different types of land objects are the same as the frequency bands in the spectrum characteristics of pixel 201. For example, the reference spectrum characteristics corresponding to the end members of different types of land objects also include m frequency bands, and are the same as the frequency bands of the spectrum characteristics of pixel 201. No further details will be given here.

[0055] Then, the computing device obtains reference spectrum features corresponding to end members of different types of objects respectively. The reference spectrum features may be predetermined by measurement, for example. In this embodiment, the reference spectrum features corresponding to end members of different types of objects include, for example:

[0056] The reference spectrum feature F1 of the green vegetation end member corresponding to the vegetation feature type is:

[0057] F1=[f 11 ,f 12 ,...,f 1m ], where f 1i (i=1~m) is the reflectance data of different frequency bands corresponding to the green vegetation end members.

[0058] The reference spectrum feature F2 of the building end element corresponding to the building feature type:

[0059] F2=[f 21 ,f 22 ,...,f 2m ], where f 2i (i=1~m) is the reflectivity data of different frequency bands corresponding to the building end elements.

[0060] Reference spectrum feature F3 of the air-ground end member corresponding to the air-ground object type:

[0061] F3=[f 31 ,f 32 ,...,f 3m ], where f 3i (i=1~m) is the reflectivity data of different frequency bands corresponding to the empty ground end member.

[0062] Reference spectrum feature F4 of the agricultural land end element corresponding to the agricultural land feature type:

[0063] F4=[f 41 ,f 42 ,...,f 4m ], where f 4i (i=1~m) is the reflectivity data of different frequency bands corresponding to the agricultural land end members.

[0064] Reference spectrum feature F5 of the water body end member corresponding to the water body feature type:

[0065] F5=[f 51 ,f 52 ,...,f 5m ], where f 5i (i=1~m) is the reflectivity data of different frequency bands corresponding to the water end members.

[0066] The computing device then creates an equation based on the following formula:

[0067] k0+k1F1+k2F2+k3F3+k4F4+k5F5=Fd (1)

[0068] Among them, k1 is the abundance value of the green vegetation end member in the first pixel; k2 is the abundance value of the building end member in the first pixel; k3 is the abundance value of the vacant land end member in the first pixel; k4 is the abundance value of the agricultural land end member in the first pixel; k5 is the abundance value of the water body end member in the first pixel; and k0 is the error term to be determined.

[0069] Thus, the computing device substitutes the spectrum feature Fd of pixel 201, the reference spectrum feature F1 of the green vegetation end member, the reference spectrum feature F2 of the building end member, the reference spectrum feature F3 of the vacant land end member, the reference spectrum feature F4 of the agricultural land end member, and the reference spectrum feature F5 of the water body end member into the above formula (1), thereby obtaining k0 to k5. Further, the abundance value k1 of the end member corresponding to the vegetation feature type in pixel 201 is obtained.

[0070] In this way, the computing device calculates the abundance values ​​of end members of different land object types for each pixel 201 in the satellite remote sensing reflection image 200, so that the vegetation abundance value of the green vegetation end member in each pixel 201 can be determined.

[0071] Optionally, the operation of determining the second pixel corresponding to the edge of the vegetation area in the predetermined area according to the determined vegetation abundance value includes: determining, in the first pixel, a third pixel corresponding to the vegetation area and a fourth pixel corresponding to the non-vegetation area; and determining the second pixel according to the third pixel and the fourth pixel.

[0072] Specifically, after determining the vegetation abundance value of the green vegetation end element in each pixel 201 (i.e., the first pixel), the computing device can determine the pixel 201a (i.e., the third pixel) corresponding to the vegetation area and the pixel 201b (i.e., the fourth pixel) corresponding to the non-vegetation area in each pixel 201 according to the vegetation abundance value of each pixel 201.

[0073] Then, the computing device determines the pixel 201c corresponding to the edge of the vegetation image area 210 according to the determined pixel 201a and pixel 201b. For example, the computing device may determine the pixel 201a adjacent to the pixel 201b as the pixel 201c. Alternatively, the computing device may determine the pixel 201b adjacent to the pixel 201a as the pixel 201c. Thus, in this way, the computing device can accurately determine the vegetation image area 210 corresponding to the vegetation area 110 according to the vegetation abundance value of each pixel 201.

[0074] Optionally, the operation of determining a third pixel corresponding to a vegetation area and a fourth pixel corresponding to a non-vegetation area in a first pixel based on vegetation abundance values ​​includes: when the vegetation abundance value of the first pixel is greater than the abundance value of an end pixel of other land object types in the first pixel, determining that the first pixel is the third pixel.

[0075] Specifically, Figure 5 FIG. 1 is a schematic diagram showing a ground area 101 corresponding to a certain pixel 201. Figure 5 As shown, when the vegetation abundance value in pixel 201 is greater than the abundance values ​​of other land object types (such as building endmembers, vacant land endmembers, agricultural land endmembers, and water body endmembers), that is, relative to the endmembers of other land object types, the abundance value of the green vegetation endmember in the pixel 201 is the largest, it means that in the ground area 101 corresponding to the pixel 201, the green vegetation occupies the main position relative to other endmembers, so the pixel 201 is determined as a pixel corresponding to the vegetation area. In this way, the pixel corresponding to the vegetation area can be accurately determined in the pixel 201.

[0076] Optionally, the operation of determining a third pixel corresponding to a vegetation area and a fourth pixel corresponding to a non-vegetation area in the first pixel based on vegetation abundance values ​​also includes: when the end element with the largest abundance value in the first pixel is a building end element, an agricultural land end element or a water body end element, determining that the first pixel is the fourth pixel.

[0077] Specifically, when the computing device determines that the vegetation abundance value of a certain pixel 201 is not the largest relative to the abundance values ​​of other land object types (such as building endmembers, vacant land endmembers, agricultural land endmembers, and water body endmembers), this means that the green vegetation endmember does not occupy a dominant position in the pixel 201. Therefore, the computing device needs to further determine the endmember that occupies a dominant position in the pixel 201.

[0078] When the computing device determines that the endmember that occupies the main position in the pixel 201 (i.e., the endmember with the largest abundance value) is a building endmember, an agricultural land endmember, or a water body endmember, it means that the ground object type of the area corresponding to the pixel 201 has changed to a ground object type different from green vegetation. In this case, the computing device can determine that the ground area corresponding to the pixel 201 is not a vegetation area, so the pixel 201 is also a pixel 201b of a non-vegetation area.

[0079] Optionally, the operation of determining, in the first pixel, a third pixel corresponding to a vegetation area and a fourth pixel corresponding to a non-vegetation area based on the vegetation abundance value, further includes: when the end element with the largest abundance value in the first pixel is an open space end element, obtaining historical statistical information related to the vegetation abundance value of the first pixel; and determining, based on the historical statistical information, whether the first pixel is the third pixel or the fourth pixel.

[0080] Specifically, when the computing device determines that the endmember with the largest abundance value in a certain pixel 201 in the satellite remote sensing reflection image 200 is an open space endmember, that is, in the ground area corresponding to the pixel 201, the open space accounts for the largest proportion of the area. In order to avoid misjudgment, the computing device can obtain historical statistical information related to the vegetation abundance value corresponding to the pixel 201.

[0081] For example, the computing device can obtain the vegetation abundance values ​​corresponding to the pixel 201 in each past month. Therefore, it is possible to determine whether the vegetation abundance value of the current pixel 201 is normal based on the periodicity and seasonality of the vegetation abundance value of the pixel 201. If the vegetation abundance value of the current pixel 201 is normal, the pixel 201 is still determined to be the third pixel corresponding to the vegetation area, otherwise the pixel 201 is determined to be the fourth pixel corresponding to the non-vegetation area. For example, if the computing device can determine the months in which the vegetation abundance value of the pixel 201 in the past predetermined period is close to the currently calculated vegetation abundance value (for example, less than a predetermined threshold) based on historical statistical information. If the determined months show periodicity in each year (for example, they are all corresponding months in each year), it means that the ground area corresponding to the pixel 201 is still the area corresponding to the vegetation area. If the determined months do not show periodicity in each year (for example, the vegetation abundance values ​​of the most recent consecutive months are relatively close to the currently calculated vegetation abundance value), it means that the pixel 201 has been transformed into a non-vegetation area.

[0082] In addition, optionally, when the end element with the largest abundance value in the first pixel is an open space end element, the computing device can also obtain historical statistical information related to the spectral characteristics of the first pixel; and determine whether the first pixel is the third pixel or the fourth pixel based on the historical statistical information.

[0083] Specifically, the computing device may obtain historical statistical information corresponding to the frequency spectrum characteristics of the pixel 201. For example, the computing device may obtain the frequency spectrum characteristics of the pixel 201 in each month within a predetermined period in the past.

[0084] Then, the computing device calculates the correlation between the frequency spectrum characteristics of the pixel 201 in each past month and the currently calculated frequency spectrum characteristics.

[0085] For example, as mentioned above, the frequency spectrum feature of pixel 201 in the current month is Fd = [fd1, fd2, ..., fd m ] T .

[0086] Then, the frequency spectrum characteristics of pixel 201 in each month in the past are obtained as Fd1~Fd n Among them, Fd1=[fd 1,1 ,fd 1,2 ,...,fd 1,m ] T ; Fd2 = [fd 2,1 ,fd 2,2 ,...,fd 2,m ] T ;...;Fd n =[fd n,1 ,fd n,2 ,...,fd n,m ] T .

[0087] Among them, fd 1,i (i=1-m) is the reflectivity data of different frequency bands corresponding to the first month of the past for the pixel 201. 2,i (i=1-m) is the reflectivity data of different frequency bands corresponding to the pixel 201 in the second month in the past. n,i (i=1-m) is the reflectivity data of different frequency bands corresponding to the pixel 201 in the nth month in the past.

[0088] Then, the computing device calculates the correlation R1~R between the spectrum features of each previous month and the spectrum features calculated in the current month. n The correlation calculation can refer to the existing correlation calculation formula:

[0089]

[0090] Therefore, according to the above formula, the correlation between the frequency spectrum characteristics of the pixel 201 in each previous month and the frequency spectrum characteristics of the current month can be calculated.

[0091] Then, the computing device may select a month with a correlation greater than a predetermined threshold as a month with a high correlation between the spectrum characteristics of the pixel 201 and the spectrum characteristics of the current month. Then, the computing device determines whether the pixel 201 is a pixel corresponding to a vegetation area based on the periodicity of the determined month with a high correlation.

[0092] For example, if the determined months show periodicity in each year (for example, they are all corresponding months in each year), it means that the ground area corresponding to the pixel 201 is still the area corresponding to the vegetation area. If the determined months do not show periodicity in each year (for example, the vegetation abundance values ​​of the last several consecutive months are relatively close to the currently calculated vegetation abundance value), it means that the pixel 201 has been transformed into a non-vegetation area.

[0093] Thus, by the above method, it is possible to effectively avoid the mistaken determination of pixels corresponding to vegetation areas as pixels corresponding to non-vegetation areas due to seasonal changes in vegetation. Thus, it is possible to more accurately determine pixels corresponding to vegetation areas and pixels corresponding to non-vegetation areas, and further more accurately evaluate changes in vegetation areas.

[0094] The operation of determining vegetation change status information in a predetermined area based on the determined vegetation area and the pre-set reference area information also includes: determining a degraded area where green vegetation is degraded based on the determined vegetation area and the pre-set reference area information; and determining the cause of green vegetation degradation in the degraded area based on the type of land feature of the end element with the largest abundance value in the fifth pixel corresponding to the degraded area.

[0095] Specifically, after determining the third pixel 201a corresponding to the vegetation area and the fourth pixel 201b corresponding to the non-vegetation area, the computing device compares the third pixel 201a and the fourth pixel 201b with the reference area information, thereby determining the fifth pixel corresponding to the degraded area of ​​vegetation degeneration in the fourth pixel 201b.

[0096] For example, when the reference area information indicates that a certain ground area should be a vegetation area, but the pixel corresponding to the ground area is the fourth pixel 201b, it can be determined that the ground area is a degraded area with degraded vegetation, and the corresponding pixel is the fifth pixel.

[0097] Then, the computing device can determine the cause of the degradation of green vegetation in the degraded area by analyzing the fifth type of the end member with the largest abundance value in the fifth pixel. For example, when the end member with the largest abundance value in the fifth pixel is a building end member, it can be determined that the cause of the degradation of green vegetation is that someone uses the vegetation area to build building facilities; when the end member with the largest abundance value in the fifth pixel is an agricultural land end member, it can be determined that the cause of the degradation of green vegetation is that someone cultivates the ground area, resulting in the degradation of green vegetation. And so on.

[0098] Therefore, according to the embodiments of the present disclosure, the causes of degradation of vegetation areas can be accurately analyzed based on the abundance values ​​of pixels, thereby making a more accurate and comprehensive assessment of the changing state of the vegetation areas.

[0099] In addition, reference Figure 1 As shown, according to the second aspect of this embodiment, a storage medium is provided, wherein the storage medium includes a stored program, wherein when the program is run, a processor executes any one of the above methods.

[0100] Therefore, in the embodiment of the present disclosure, the edge of the vegetation area is not identified by image recognition, but by analyzing the abundance value of the green vegetation end member in each pixel, and determining the edge of the vegetation area according to the abundance value. Therefore, compared with the image recognition method, the present disclosure can more accurately extract the edge of the vegetation image area based on the mixed pixels of the reflected remote sensing image, and then accurately determine the vegetation area in the predetermined area, so as to accurately evaluate the change of the vegetation area. It solves the technical problem that the fuzzy edge of the vegetation area cannot be accurately identified by the image recognition method in the prior art, and thus the change of the vegetation area cannot be accurately evaluated.

[0101] It should be noted that, for the above-mentioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should know that the present invention is not limited by the described action sequence, because according to the present invention, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present invention.

[0102] Through the description of the above implementation methods, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus a necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for enabling a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0103] Example 2

[0104] Figure 6 FIG. 6 shows a vegetation status monitoring device 600 based on abundance value according to the first aspect of this embodiment, and the device 600 corresponds to the method according to the first aspect of embodiment 1. Figure 6As shown, the device 600 includes: a first pixel determination module 610, which is used to determine a plurality of first pixels corresponding to a predetermined area on the ground according to a satellite remote sensing reflection image generated based on a ground reflection spectrum signal; a vegetation abundance value determination module 620, which is used to determine the vegetation abundance value of the end element corresponding to the vegetation feature type in the first pixel according to the spectrum characteristics corresponding to the first pixel; a second pixel determination module 630, which is used to determine the second pixel corresponding to the edge of the vegetation area in the predetermined area according to the determined vegetation abundance value; a vegetation area determination module 640, which is used to determine the vegetation area according to the second pixel; and a vegetation change state determination module 650, which is used to determine the vegetation change state information in the predetermined area according to the determined vegetation area and pre-set reference area information, wherein the reference area is an area pre-determined in the predetermined area for planting vegetation.

[0105] Optionally, the vegetation abundance value determination module 620 includes: a reference spectrum feature acquisition submodule, used to acquire reference spectrum features corresponding to endmembers of different ground object types; and an abundance value determination submodule, used to determine the abundance values ​​of endmembers of different ground object types in the first pixel based on the following formula according to the reference spectrum features and the spectrum features corresponding to the first pixel:

[0106] k0+k1F1+k2F2+k3F3+k4F4+k5F5=Fd,where

[0107] Fd is the spectral characteristic of the first pixel; F1 is the reference spectral characteristic of the green vegetation end element corresponding to the vegetation feature type; k1 is the abundance value of the green vegetation end element in the first pixel; F2 is the reference spectral characteristic of the building end element corresponding to the building feature type; k2 is the abundance value of the building end element in the first pixel; F3 is the reference spectral characteristic of the vacant land end element corresponding to the vacant land feature type; k3 is the abundance value of the vacant land end element in the first pixel; F4 is the reference spectral characteristic of the agricultural land end element corresponding to the agricultural land feature type; 4 is the abundance value of the agricultural land end element in the first pixel; F5 is the reference spectral characteristic of the water body end element corresponding to the water body feature type; k5 is the abundance value of the water body end element in the first pixel; and k0 is the error term to be determined.

[0108] Optionally, the second pixel determination module 630 includes: a first pixel determination submodule, used to determine, in the first pixel, a third pixel corresponding to the vegetation area and a fourth pixel corresponding to the non-vegetation area according to the vegetation abundance value; and a second pixel determination submodule, used to determine the second pixel based on the third pixel and the fourth pixel.

[0109] Optionally, the first pixel determination submodule includes: a first determination unit, configured to determine that the first pixel is a third pixel when the vegetation abundance value of the first pixel is greater than the abundance value of the end member of other land feature types in the first pixel.

[0110] Optionally, the first pixel determination submodule further includes: a second determination unit, configured to determine that the first pixel is the fourth pixel when the end member with the largest abundance value in the first pixel is a building end member, an agricultural land end member or a water body end member.

[0111] Optionally, the first pixel determination submodule also includes: a historical statistical information unit, used to obtain historical statistical information related to the vegetation abundance value of the first pixel when the end element with the largest abundance value in the first pixel is an open space end element; and a third determination unit, used to determine whether the first pixel is a third pixel or a fourth pixel based on the historical statistical information.

[0112] Optionally, the vegetation change state determination module 650 includes: a degradation area determination submodule, which is used to determine the degradation area of ​​green vegetation degradation based on the determined vegetation area and pre-set reference area information; and a degradation cause determination submodule, which is used to determine the cause of green vegetation degradation in the degradation area based on the type of land feature of the end element with the largest abundance value in the fifth pixel corresponding to the degradation area.

[0113] Therefore, in the embodiment of the present disclosure, the edge of the vegetation area is not identified by image recognition, but by analyzing the abundance value of the green vegetation end member in each pixel, and determining the edge of the vegetation area according to the abundance value. Therefore, compared with the image recognition method, the present disclosure can more accurately extract the edge of the vegetation image area based on the mixed pixels of the reflected remote sensing image, and then accurately determine the vegetation area in the predetermined area, so as to accurately evaluate the change of the vegetation area. It solves the technical problem that the fuzzy edge of the vegetation area cannot be accurately identified by the image recognition method in the prior art, and thus the change of the vegetation area cannot be accurately evaluated.

[0114] Example 3

[0115] Figure 7 The apparatus 700 for monitoring vegetation status based on abundance value according to the first aspect of this embodiment is shown. The apparatus 700 corresponds to the method according to the first aspect of embodiment 1. Figure 7As shown, the device 700 includes: a processor 710; and a memory 720, which is connected to the processor 710 and is used to provide the processor with instructions for processing the following processing steps: determining a plurality of first pixels corresponding to a predetermined area on the ground based on a satellite remote sensing reflection image generated based on a ground reflection spectrum signal; determining a vegetation abundance value of an end element corresponding to a vegetation feature type in the first pixel based on a spectrum feature corresponding to the first pixel; determining a second pixel corresponding to an edge of a vegetation area in the predetermined area based on the determined vegetation abundance value; determining a vegetation area based on the second pixel; and determining vegetation change status information in the predetermined area based on the determined vegetation area and pre-set reference area information, wherein the reference area is an area pre-determined in the predetermined area for planting vegetation.

[0116] Optionally, the operation of determining the vegetation abundance value of the endmember corresponding to the vegetation feature type in the first pixel according to the spectrum feature corresponding to the first pixel includes: obtaining reference spectrum features corresponding to the endmembers of different feature types; and determining the abundance values ​​of the endmembers of different feature types in the first pixel according to the reference spectrum features and the spectrum features corresponding to the first pixel based on the following formula:

[0117] k0+k1F1+k2F2+k3F3+k4F4+k5F5=Fd,where

[0118] Fd is the spectral characteristic of the first pixel; F1 is the reference spectral characteristic of the green vegetation end element corresponding to the vegetation feature type; k1 is the abundance value of the green vegetation end element in the first pixel; F2 is the reference spectral characteristic of the building end element corresponding to the building feature type; k2 is the abundance value of the building end element in the first pixel; F3 is the reference spectral characteristic of the vacant land end element corresponding to the vacant land feature type; k3 is the abundance value of the vacant land end element in the first pixel; F4 is the reference spectral characteristic of the agricultural land end element corresponding to the agricultural land feature type; k4 is the abundance value of the agricultural land end element in the first pixel; F5 is the reference spectral characteristic of the water body end element corresponding to the water body feature type; k5 is the abundance value of the water body end element in the first pixel; and k0 is the error term to be determined.

[0119] Optionally, the operation of determining the second pixel corresponding to the edge of the vegetation area in the predetermined area according to the determined vegetation abundance value includes: determining, in the first pixel, a third pixel corresponding to the vegetation area and a fourth pixel corresponding to the non-vegetation area; and determining the second pixel according to the third pixel and the fourth pixel.

[0120] Optionally, the operation of determining a third pixel corresponding to a vegetation area and a fourth pixel corresponding to a non-vegetation area in a first pixel based on vegetation abundance values ​​includes: when the vegetation abundance value of the first pixel is greater than the abundance value of an end pixel of other land object types in the first pixel, determining that the first pixel is the third pixel.

[0121] Optionally, the operation of determining a third pixel corresponding to a vegetation area and a fourth pixel corresponding to a non-vegetation area in the first pixel based on vegetation abundance values ​​also includes: when the end element with the largest abundance value in the first pixel is a building end element, an agricultural land end element or a water body end element, determining that the first pixel is the fourth pixel.

[0122] Optionally, the operation of determining, in the first pixel, a third pixel corresponding to a vegetation area and a fourth pixel corresponding to a non-vegetation area based on the vegetation abundance value, further includes: when the end element with the largest abundance value in the first pixel is an open space end element, obtaining historical statistical information related to the vegetation abundance value of the first pixel; and determining, based on the historical statistical information, whether the first pixel is the third pixel or the fourth pixel.

[0123] Optionally, the operation of determining vegetation change status information in a predetermined area based on the determined vegetation area and pre-set reference area information also includes: determining a degraded area where green vegetation is degraded based on the determined vegetation area and pre-set reference area information; and determining the cause of green vegetation degradation in the degraded area based on the type of land feature of the end element with the largest abundance value in the fifth pixel corresponding to the degraded area.

[0124] Therefore, in the embodiment of the present disclosure, the edge of the vegetation area is not identified by image recognition, but by analyzing the abundance value of the green vegetation end member in each pixel, and determining the edge of the vegetation area according to the abundance value. Therefore, compared with the image recognition method, the present disclosure can more accurately extract the edge of the vegetation image area based on the mixed pixels of the reflected remote sensing image, and then accurately determine the vegetation area in the predetermined area, so as to accurately evaluate the change of the vegetation area. It solves the technical problem that the fuzzy edge of the vegetation area cannot be accurately identified by the image recognition method in the prior art, and thus the change of the vegetation area cannot be accurately evaluated.

[0125] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0126] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0127] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0128] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0129] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0130] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0131] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A vegetation status monitoring method based on abundance value, characterized in that: include: Determining a plurality of first pixels corresponding to a predetermined area on the ground according to a satellite remote sensing reflection image generated based on a ground reflection spectrum signal; Determining the vegetation abundance value of the end member corresponding to the vegetation feature type in the first pixel according to the frequency spectrum feature corresponding to the first pixel; According to the determined vegetation abundance value, a second pixel corresponding to the edge of the vegetation area in the predetermined area is determined, wherein The operation of determining the vegetation abundance value of the endmember corresponding to the vegetation feature type in the first pixel according to the spectrum feature corresponding to the first pixel includes: obtaining reference spectrum features corresponding to the endmembers of different feature types; and determining the abundance values ​​of the endmembers of different feature types in the first pixel according to the reference spectrum features and the spectrum features corresponding to the first pixel based on the following formula: ,in F is the spectrum characteristic of the first pixel; F 1 is the reference spectrum characteristic of the green vegetation end member corresponding to the vegetation feature type; k 1 is the abundance value of the green vegetation end member in the first pixel; F 2 is the reference spectrum characteristic of the building end element corresponding to the building feature type; k 2 is the abundance value of the building end member in the first pixel; F 3 is the reference spectrum characteristic of the air-ground end element corresponding to the air-ground object type; k 3 is the abundance value of the open space end member in the first pixel; F 4 is the reference spectrum characteristics of the agricultural land end element corresponding to the agricultural land feature type; k 4 is the abundance value of the agricultural land end member in the first pixel; F 5 is the reference spectrum characteristic of the water body end member corresponding to the water body feature type; k 5 is the abundance value of the water body end member in the first pixel; and k 0 is the error term to be determined, where The operation of determining the second pixel corresponding to the edge of the vegetation area in the predetermined area according to the determined vegetation abundance value includes: determining the third pixel corresponding to the vegetation area and the fourth pixel corresponding to the non-vegetation area in the first pixel according to the vegetation abundance value; and determining the second pixel corresponding to the edge of the vegetation image area according to the pixel whose abundance value of the green vegetation end member is lower than the predetermined threshold, wherein The operation of determining, in the first pixel, a third pixel corresponding to a vegetation area and a fourth pixel corresponding to a non-vegetation area according to the vegetation abundance value includes: determining that the first pixel is a third pixel when the vegetation abundance value of the first pixel is greater than the abundance value of an end member of another type of land object in the first pixel, wherein The operation of determining, in the first pixel, a third pixel corresponding to a vegetation area and a fourth pixel corresponding to a non-vegetation area according to the vegetation abundance value, further includes: when the end member with the largest abundance value in the first pixel is a building end member, an agricultural land end member or a water body end member, determining that the first pixel is the fourth pixel; Determining the vegetation area according to the second pixel; and Based on the determined vegetation area and pre-set reference area information, the vegetation change status information in the predetermined area is determined, wherein the reference area is an area pre-determined in the predetermined area for planting vegetation, and the reference area information is land planning information, which specifies the position, shape and area information of the vegetation area in the predetermined area where vegetation should be planted, and the vegetation change status information at least includes: vegetation area change information indicating whether the area of ​​the vegetation area has increased or decreased, information on vegetation degradation areas, and information on vegetation expansion areas.

2. The method according to claim 1, characterized in that The operation of determining, in the first pixel, a third pixel corresponding to a vegetation area and a fourth pixel corresponding to a non-vegetation area according to the vegetation abundance value, further includes: When the endmember with the largest abundance value in the first pixel is an open space endmember, obtaining historical statistical information related to the vegetation abundance value of the first pixel; and According to the historical statistical information, it is determined that the first pixel is the third pixel or the fourth pixel.

3. The method according to claim 2, characterized in that The operation of determining vegetation change state information in the predetermined area according to the determined vegetation area and the preset reference area information also includes: Determining a degraded area of ​​green vegetation degradation based on the determined vegetation area and pre-set reference area information; and The cause of the degradation of the green vegetation in the degraded area is determined according to the land feature type of the end member with the largest abundance value in the fifth pixel corresponding to the degraded area.

4. A storage medium, characterized in that: The storage medium includes a stored program, wherein when the program is run, the processor executes the method according to any one of claims 1 to 3.

5. A vegetation status monitoring device based on abundance value, characterized in that: include: A first pixel determination module, used to determine a plurality of first pixels corresponding to a predetermined area on the ground according to a satellite remote sensing reflection image generated based on a ground reflection spectrum signal; A vegetation abundance value determination module, used to determine the vegetation abundance value of the end member corresponding to the vegetation feature type in the first pixel according to the frequency spectrum characteristics corresponding to the first pixel; The second pixel determination module is used to determine the second pixel corresponding to the edge of the vegetation area in the predetermined area according to the determined vegetation abundance value, wherein The operation of determining the vegetation abundance value of the endmember corresponding to the vegetation feature type in the first pixel according to the spectrum feature corresponding to the first pixel includes: obtaining reference spectrum features corresponding to the endmembers of different feature types; and determining the abundance values ​​of the endmembers of different feature types in the first pixel according to the reference spectrum features and the spectrum features corresponding to the first pixel based on the following formula: ,in F is the spectrum characteristic of the first pixel; F 1 is the reference spectrum characteristic of the green vegetation end member corresponding to the vegetation feature type; k 1 is the abundance value of the green vegetation end member in the first pixel; F 2 is the reference spectrum characteristic of the building end element corresponding to the building feature type; k 2 is the abundance value of the building end member in the first pixel; F 3 is the reference spectrum characteristic of the air-ground end element corresponding to the air-ground object type; k 3 is the abundance value of the open space end member in the first pixel; F 4 is the reference spectrum characteristics of the agricultural land end element corresponding to the agricultural land feature type; k 4 is the abundance value of the agricultural land end member in the first pixel; F 5 is the reference spectrum characteristic of the water body end member corresponding to the water body feature type; k 5 is the abundance value of the water body end member in the first pixel; and k 0 is the error term to be determined, where The operation of determining the second pixel corresponding to the edge of the vegetation area in the predetermined area according to the determined vegetation abundance value includes: determining the third pixel corresponding to the vegetation area and the fourth pixel corresponding to the non-vegetation area in the first pixel according to the vegetation abundance value; and determining the second pixel corresponding to the edge of the vegetation image area according to the pixel whose abundance value of the green vegetation end member is lower than the predetermined threshold, wherein The operation of determining, in the first pixel, a third pixel corresponding to a vegetation area and a fourth pixel corresponding to a non-vegetation area according to the vegetation abundance value includes: determining that the first pixel is a third pixel when the vegetation abundance value of the first pixel is greater than the abundance value of an end member of another type of land object in the first pixel, wherein The operation of determining, in the first pixel, a third pixel corresponding to a vegetation area and a fourth pixel corresponding to a non-vegetation area according to the vegetation abundance value, further includes: when the end member with the largest abundance value in the first pixel is a building end member, an agricultural land end member or a water body end member, determining that the first pixel is the fourth pixel; a vegetation area determination module, configured to determine the vegetation area according to the second pixel; and A vegetation change state determination module is used to determine the vegetation change state information in the predetermined area based on the determined vegetation area and pre-set reference area information, wherein the reference area is an area pre-determined in the predetermined area for planting vegetation, and the reference area information is land planning information, which specifies the position, shape and area information of the vegetation area in the predetermined area where vegetation should be planted, and the vegetation change state information at least includes: vegetation area change information indicating whether the area of ​​the vegetation area has increased or decreased, vegetation degradation area information, and vegetation expansion area information.

6. A vegetation status monitoring device based on abundance value, characterized in that: include: processor; as well as A memory, connected to the processor, configured to provide the processor with instructions for processing the following processing steps: Determining a plurality of first pixels corresponding to a predetermined area on the ground according to a satellite remote sensing reflection image generated based on a ground reflection spectrum signal; Determining the vegetation abundance value of the end member corresponding to the vegetation feature type in the first pixel according to the frequency spectrum feature corresponding to the first pixel; According to the determined vegetation abundance value, a second pixel corresponding to the edge of the vegetation area in the predetermined area is determined, wherein The operation of determining the vegetation abundance value of the endmember corresponding to the vegetation feature type in the first pixel according to the spectrum feature corresponding to the first pixel includes: obtaining reference spectrum features corresponding to the endmembers of different feature types; and determining the abundance values ​​of the endmembers of different feature types in the first pixel according to the reference spectrum features and the spectrum features corresponding to the first pixel based on the following formula: ,in F is the spectrum characteristic of the first pixel; F 1 is the reference spectrum characteristic of the green vegetation end member corresponding to the vegetation feature type; k 1 is the abundance value of the green vegetation end member in the first pixel; F 2 is the reference spectrum characteristic of the building end element corresponding to the building feature type; k 2 is the abundance value of the building end member in the first pixel; F 3 is the reference spectrum characteristic of the air-ground end element corresponding to the air-ground object type; k 3 is the abundance value of the open space end member in the first pixel; F 4 is the reference spectrum characteristics of the agricultural land end element corresponding to the agricultural land feature type; k 4 is the abundance value of the agricultural land end member in the first pixel; F 5 is the reference spectrum characteristic of the water body end member corresponding to the water body feature type; k 5 is the abundance value of the water body end member in the first pixel; and k 0 is the error term to be determined, where The operation of determining the second pixel corresponding to the edge of the vegetation area in the predetermined area according to the determined vegetation abundance value includes: determining the third pixel corresponding to the vegetation area and the fourth pixel corresponding to the non-vegetation area in the first pixel according to the vegetation abundance value; and determining the second pixel corresponding to the edge of the vegetation image area according to the pixel whose abundance value of the green vegetation end member is lower than the predetermined threshold value, wherein The operation of determining, in the first pixel, a third pixel corresponding to a vegetation area and a fourth pixel corresponding to a non-vegetation area according to the vegetation abundance value includes: determining that the first pixel is a third pixel when the vegetation abundance value of the first pixel is greater than the abundance value of an end member of another type of land object in the first pixel, wherein The operation of determining, in the first pixel, a third pixel corresponding to a vegetation area and a fourth pixel corresponding to a non-vegetation area according to the vegetation abundance value, further includes: when the end member with the largest abundance value in the first pixel is a building end member, an agricultural land end member or a water body end member, determining that the first pixel is the fourth pixel; Determining the vegetation area according to the second pixel; and Based on the determined vegetation area and pre-set reference area information, the vegetation change status information in the predetermined area is determined, wherein the reference area is an area pre-determined in the predetermined area for planting vegetation, and the reference area information is land planning information, which specifies the position, shape and area information of the vegetation area in the predetermined area where vegetation should be planted, and the vegetation change status information at least includes: vegetation area change information indicating whether the area of ​​the vegetation area has increased or decreased, information on vegetation degradation areas, and information on vegetation expansion areas.

Images