CN114419458A - Bare soil monitoring method, device and equipment based on high-resolution satellite remote sensing - Google Patents
Bare soil monitoring method, device and equipment based on high-resolution satellite remote sensing Download PDFInfo
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Abstract
The invention relates to a bare soil monitoring method based on high-resolution satellite remote sensing, which comprises the steps of collecting remote sensing images of areas to be monitored, preprocessing the remote sensing images, then segmenting the remote sensing images, and extracting target characteristics of each segmented area; determining the bare soil area of the segmentation area according to the target characteristics of the segmentation area, the target characteristics of a preset bare soil terrain and a bare soil monitoring model, wherein the bare soil monitoring model is obtained based on the training of a U-net neural network model; and superposing the remote sensing image of the bare soil area and the color synthetic image of the remote sensing image of the area to be monitored to obtain the bare soil area of the area to be monitored. The invention is suitable for monitoring the change of the bare soil in a large range, has strong space-time continuity and does not need to extract the bare soil in advance. The differences of different ground object types in different remote sensing indexes are fully considered, whether bare soil changes occur or not is judged, and the accuracy of the identification result can be improved. The invention also relates to a bare soil monitoring device and equipment based on the high-resolution satellite remote sensing.
Description
Technical Field
The invention relates to the technical field of information processing, in particular to a bare soil monitoring method, device and equipment based on high-resolution satellite remote sensing.
Background
Soil erosion is a serious ecological environment problem facing the world at present, and various disasters induced by the soil erosion also threaten and damage the production and life of people, wherein bare soil is a main surface landscape of a soil erosion area. Therefore, the bare soil area is quickly and accurately positioned, the time-space change analysis of the bare soil on the earth surface is carried out, and the method is particularly important for the treatment work of water and soil loss.
Disclosure of Invention
The invention aims to solve the technical problem of the prior art and provides a bare soil monitoring method, a device and equipment based on high-resolution satellite remote sensing.
The technical scheme for solving the technical problems is as follows:
a bare soil monitoring method based on high-resolution satellite remote sensing, the method comprising:
acquiring a remote sensing image of a region to be monitored, preprocessing the remote sensing image, then segmenting the remote sensing image, and extracting target characteristics of each segmented region;
determining the bare soil area of the segmentation area according to the target characteristics of the segmentation area, the target characteristics of a preset bare soil terrain and a bare soil monitoring model, wherein the bare soil monitoring model is obtained based on U-net neural network model training;
and superposing the remote sensing images of the bare soil areas of all the segmentation areas and the color synthetic image of the remote sensing image of the area to be monitored to obtain the bare soil area of the area to be monitored.
On the basis of the technical scheme, the invention can be further improved as follows.
Further, the preprocessing the remote sensing image and then segmenting the remote sensing image to extract the target features of each segmented region specifically comprises:
carrying out radiometric calibration, atmospheric correction and cutting on the remote sensing image to obtain a plurality of segmentation areas;
respectively calculating the NVDI time series curve of the pixels in each divided area, and calculating the similarity between the NVDI time series curve of each pixel and the NVDI time series curve of the standard bare-soil terrain;
taking the segmentation areas with the similarity values larger than a preset threshold value and the number of the pixels larger than a preset number as segmentation areas to be researched;
performing binarization feature extraction on each segmented region to be researched by adopting a feature extraction network to obtain target features of each segmented region to be researched; the characteristic extraction network is constructed based on a hyperbolic function and is obtained by utilizing a floating point characteristic extraction network for training.
Further, the determining the bare soil area of the segmented area according to the target feature of the segmented area, the target feature of the preset bare soil terrain and the bare soil monitoring model specifically includes:
and inputting the target characteristics of the segmentation areas and the target characteristics of the preset bare soil terrain into the bare soil monitoring model to obtain the bare soil areas in the segmentation areas.
Further, the radiometric calibration, the atmospheric correction and the cutting are performed on the remote sensing image to obtain a plurality of segmentation areas, and the method specifically includes:
labeling the remote sensing image, wherein the labeling comprises farmland, woodland, bare soil, rivers, towns and roads;
randomly cutting, turning, rotating, changing chromaticity, changing brightness and disturbing noise to the remote sensing image;
and performing superpixel calculation on the remote sensing image to obtain a plurality of adjacent segmentation areas.
Further, the calculating the NVDI time series curves of the pixels in each of the divided areas, and the calculating the similarity between the NVDI time series curve of each of the pixels and the standard NVDI time series curve of the bare-earth terrain specifically include:
the standard NVDI time series curve of the bare soil terrain is obtained by recording the average value of NVDI coefficients of the bare soil terrain at a certain time point;
acquiring a normalized vegetation index NDVI of the pixels in the partitioned area, and acquiring an NDVI time sequence curve of the pixels in the partitioned area through wave band synthesis and SG filtering;
and calculating the similarity between the NVDI time series curve of the pixel and the standard NVDI time series curve of the bare-soil terrain by adopting a Frecher distance algorithm.
Further, the overlaying the remote sensing images of the bare soil areas of all the divided areas and the color composite image of the remote sensing image of the area to be monitored to obtain the bare soil area of the area to be monitored specifically comprises:
performing first waveband calculation on the remote sensing image of the bare soil area of the segmentation area and the color synthetic image of the remote sensing image of the area to be monitored in a remote sensing image processing platform ENVI, wherein the image which meets a first preset condition is a bare soil terrain, and otherwise, removing the image to obtain a first binary image;
performing second band operation on the remote sensing image of the bare soil area of the segmented area and the color synthetic image of the remote sensing image of the area to be monitored in a remote sensing image processing platform ENVI, wherein the remote sensing image meets a second preset condition and is a bare soil terrain, and otherwise, removing the remote sensing image to obtain a second binary image;
and performing logic intersection operation on the first binary image and the second binary image to obtain the bare soil area of the area to be monitored.
The method has the beneficial effects that: the bare soil monitoring method based on high-resolution satellite remote sensing comprises the steps of collecting remote sensing images of areas to be monitored, preprocessing the remote sensing images, then segmenting the remote sensing images, and extracting target features of all segmented areas; determining the bare soil area of the segmentation area according to the target characteristics of the segmentation area, the target characteristics of a preset bare soil terrain and a bare soil monitoring model, wherein the bare soil monitoring model is obtained based on U-net neural network model training; and superposing the remote sensing images of the bare soil areas of all the segmentation areas and the color synthetic image of the remote sensing image of the area to be monitored to obtain the bare soil area of the area to be monitored. The invention is suitable for monitoring the change of the bare soil in a large range, has strong space-time continuity and does not need to extract the bare soil in advance. The differences of different ground object types in different remote sensing indexes are fully considered, whether bare soil changes occur or not is judged, and the accuracy of the identification result can be improved.
The invention also solves another technical scheme of the technical problems as follows:
a bare earth monitoring device based on high-resolution satellite remote sensing, the device comprising:
the acquisition module is used for acquiring a remote sensing image of a region to be monitored, preprocessing the remote sensing image, then segmenting the remote sensing image, and extracting target characteristics of each segmented region;
the extracting module is used for extracting the bare soil area of the segmentation area according to the target characteristics of the segmentation area, the target characteristics of a preset bare soil terrain and a bare soil monitoring model, wherein the bare soil monitoring model is obtained based on U-net neural network model training;
and the synthesis module is used for superposing the extracted images of the bare soil areas of all the segmentation areas and the color synthesis image of the remote sensing image of the area to be monitored to obtain the bare soil area of the area to be monitored.
Further, the acquisition module is specifically configured to perform radiometric calibration, atmospheric correction and cutting on the remote sensing image to obtain a plurality of segmented regions;
respectively calculating the NVDI time series curve of the pixels in each divided area, and calculating the similarity between the NVDI time series curve of each pixel and the NVDI time series curve of the standard bare-soil terrain;
taking the segmentation areas with the similarity values larger than a preset threshold value and the number of the pixels larger than a preset number as segmentation areas to be researched;
performing binarization feature extraction on each segmented region to be researched by adopting a feature extraction network to obtain target features of each segmented region to be researched; the characteristic extraction network is constructed based on a hyperbolic function and is obtained by utilizing a floating point characteristic extraction network for training.
Furthermore, the present invention provides a computer-readable storage medium, on which a computer program is stored, which when executed by a processor implements the steps of the bare soil monitoring method based on high resolution satellite remote sensing according to any one of the above-mentioned technical solutions.
The invention also provides an electronic device, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor executes the program to realize the steps of the bare soil monitoring method based on the high-resolution satellite remote sensing according to any one of the above technical schemes.
Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments of the present invention or in the description of the prior art will be briefly described below, and it is obvious that the drawings described below are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flow chart of a bare soil monitoring method based on high-resolution satellite remote sensing according to an embodiment of the present invention;
fig. 2 is a schematic block diagram of a bare soil monitoring model device based on high-resolution satellite remote sensing according to another embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, shall fall within the scope of protection of the present invention.
As shown in fig. 1, the bare soil monitoring method based on high-resolution satellite remote sensing according to the embodiment of the present invention includes the following steps:
110. the method comprises the steps of collecting remote sensing images of areas to be monitored, preprocessing the remote sensing images, then segmenting the remote sensing images, and extracting target features of all segmented areas.
120. And determining the bare soil area of the segmentation area according to the target characteristics of the segmentation area, the target characteristics of a preset bare soil terrain and a bare soil monitoring model, wherein the bare soil monitoring model is obtained based on the training of a U-net neural network model.
130. And superposing the remote sensing images of the bare soil areas of all the segmentation areas and the color synthetic image of the remote sensing image of the area to be monitored to obtain the bare soil area of the area to be monitored.
Further, in step 110, the remote sensing image is preprocessed and then segmented, and the target features of each segmented region are extracted, which specifically includes:
111. and carrying out radiometric calibration, atmospheric correction and cutting on the remote sensing image to obtain a plurality of segmentation areas.
112. And respectively calculating the NVDI time series curve of the pixels in each partition area, and calculating the similarity between the NVDI time series curve of each pixel and the NVDI time series curve of the standard bare-soil terrain.
113. And taking the segmentation regions with the similarity value larger than a preset threshold value and the number of the pixels larger than a preset number as segmentation regions to be researched.
114. Performing binarization feature extraction on each segmented region to be researched by adopting a feature extraction network to obtain target features of each segmented region to be researched; the characteristic extraction network is constructed based on a hyperbolic function and is obtained by utilizing a floating point characteristic extraction network for training.
Further, step 120 specifically includes:
and inputting the target characteristics of the segmentation areas and the target characteristics of the preset bare soil terrain into the bare soil monitoring model to obtain the bare soil areas in the segmentation areas.
Further, step 111 specifically includes:
and labeling the remote sensing image, wherein the labeling comprises farmland, woodland, bare soil, rivers, towns and roads.
And the remote sensing image is subjected to random cutting, overturning, rotating, chrominance change, light and shade change and noise interference.
And performing superpixel calculation on the remote sensing image to obtain a plurality of adjacent segmentation areas.
Further, step 112 specifically includes:
the standard NVDI time series curve of the bare soil terrain is obtained by recording the average value of NVDI coefficients of the bare soil terrain at a certain time point.
And acquiring the normalized vegetation index NDVI of the pixels in the partitioned area, and acquiring an NDVI time sequence curve of the pixels in the partitioned area through wave band synthesis and SG filtering.
And calculating the similarity between the NVDI time series curve of the pixel and the standard NVDI time series curve of the bare-soil terrain by adopting a Frecher distance algorithm.
Further, step 130 specifically includes:
and performing first waveband calculation on the remote sensing image of the bare soil area of the segmentation area and the color synthetic image of the remote sensing image of the area to be monitored in a remote sensing image processing platform ENVI, wherein the bare soil terrain meeting a first preset condition is the bare soil terrain, and otherwise, removing the bare soil terrain to obtain a first binary image.
And performing second waveband calculation on the remote sensing image of the bare soil area of the segmented area and the color synthetic image of the remote sensing image of the area to be monitored in a remote sensing image processing platform ENVI, wherein the bare soil terrain meeting a second preset condition is the bare soil terrain, and otherwise, removing the bare soil terrain to obtain a second binary image.
And performing logic intersection operation on the first binary image and the second binary image to obtain the bare soil area of the area to be monitored.
It should be understood that the Normalized Difference Vegetation Index (NDVI) refers to the sum of the reflection values in the near infrared band and the reflection values in the red infrared band in the remote sensing image.
The bare soil monitoring method based on the high-resolution satellite remote sensing provided by the embodiment comprises the steps of collecting a remote sensing image of a region to be monitored, preprocessing the remote sensing image, segmenting the remote sensing image, and extracting target features of each segmented region; determining the bare soil area of the segmentation area according to the target characteristics of the segmentation area, the target characteristics of a preset bare soil terrain and a bare soil monitoring model, wherein the bare soil monitoring model is obtained based on U-net neural network model training; and superposing the remote sensing images of the bare soil areas of all the segmentation areas and the color synthetic image of the remote sensing image of the area to be monitored to obtain the bare soil area of the area to be monitored. The invention is suitable for monitoring the change of the bare soil in a large range, has strong space-time continuity and does not need to extract the bare soil in advance. The differences of different ground object types in different remote sensing indexes are fully considered, whether bare soil changes occur or not is judged, and the accuracy of the identification result can be improved.
As shown in fig. 2, a bare soil monitoring device based on high-resolution satellite remote sensing includes:
and the acquisition module is used for acquiring the remote sensing image of the area to be monitored, preprocessing the remote sensing image, then segmenting the remote sensing image and extracting the target characteristics of each segmented area.
And the extracting module is used for extracting the bare soil area of the segmentation area according to the target characteristics of the segmentation area, the target characteristics of a preset bare soil terrain and a bare soil monitoring model, wherein the bare soil monitoring model is obtained based on the training of a U-net neural network model.
And the synthesis module is used for superposing the extracted images of the bare soil areas of all the segmentation areas and the color synthesis image of the remote sensing image of the area to be monitored to obtain the bare soil area of the area to be monitored.
Further, the acquisition module is specifically configured to perform radiometric calibration, atmospheric correction, and clipping on the remote sensing image to obtain a plurality of segmented regions.
And respectively calculating the NVDI time series curve of the pixels in each partition area, and calculating the similarity between the NVDI time series curve of each pixel and the NVDI time series curve of the standard bare-soil terrain.
And taking the segmentation regions with the similarity value larger than a preset threshold value and the number of the pixels larger than a preset number as segmentation regions to be researched.
Performing binarization feature extraction on each segmented region to be researched by adopting a feature extraction network to obtain target features of each segmented region to be researched; the characteristic extraction network is constructed based on a hyperbolic function and is obtained by utilizing a floating point characteristic extraction network for training.
Furthermore, the present invention provides a computer-readable storage medium, on which a computer program is stored, which when executed by a processor implements the steps of the bare soil monitoring method based on high resolution satellite remote sensing according to any one of the above-mentioned technical solutions.
The invention also provides an electronic device, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor executes the program to realize the steps of the bare soil monitoring method based on the high-resolution satellite remote sensing according to any one of the above technical schemes.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus/terminal device and method may be implemented in other ways. For example, the above-described embodiments of the apparatus/terminal device are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium.
Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method embodiments may be implemented. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain other components which may be suitably increased or decreased as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media which may not include electrical carrier signals and telecommunications signals in accordance with legislation and patent practice.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.
While the invention has been described with reference to specific embodiments, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A bare soil monitoring method based on high-resolution satellite remote sensing is characterized by comprising the following steps:
acquiring a remote sensing image of a region to be monitored, preprocessing the remote sensing image, then segmenting the remote sensing image, and extracting target characteristics of each segmented region;
determining the bare soil area of the segmentation area according to the target characteristics of the segmentation area, the target characteristics of a preset bare soil terrain and a bare soil monitoring model, wherein the bare soil monitoring model is obtained based on U-net neural network model training;
and superposing the remote sensing images of the bare soil areas of all the segmentation areas and the color synthetic image of the remote sensing image of the area to be monitored to obtain the bare soil area of the area to be monitored.
2. The bare soil monitoring method based on high-resolution satellite remote sensing according to claim 1, wherein the remote sensing image is preprocessed and then segmented, and the target features of each segmented region are extracted, specifically comprising:
carrying out radiometric calibration, atmospheric correction and cutting on the remote sensing image to obtain a plurality of segmentation areas;
respectively calculating the NVDI time series curve of the pixels in each divided area, and calculating the similarity between the NVDI time series curve of each pixel and the NVDI time series curve of the standard bare-soil terrain;
taking the segmentation areas with the similarity values larger than a preset threshold value and the number of the pixels larger than a preset number as segmentation areas to be researched;
performing binarization feature extraction on each segmented region to be researched by adopting a feature extraction network to obtain target features of each segmented region to be researched; the characteristic extraction network is constructed based on a hyperbolic function and is obtained by utilizing a floating point characteristic extraction network for training.
3. The bare soil monitoring method based on high-resolution satellite remote sensing according to claim 1, wherein the determining the bare soil area of the segmented area according to the target feature of the segmented area, the target feature of a preset bare soil terrain and the bare soil monitoring model specifically comprises:
and inputting the target characteristics of the segmentation areas and the target characteristics of the preset bare soil terrain into the bare soil monitoring model to obtain the bare soil areas in the segmentation areas.
4. The bare soil monitoring method based on high-resolution satellite remote sensing according to claim 2, wherein the radiometric calibration, atmospheric correction and cutting are performed on the remote sensing image to obtain a plurality of segmented regions, specifically comprising:
labeling the remote sensing image, wherein the labeling comprises farmland, woodland, bare soil, rivers, towns and roads;
randomly cutting, turning, rotating, changing chromaticity, changing brightness and disturbing noise to the remote sensing image;
and performing superpixel calculation on the remote sensing image to obtain a plurality of adjacent segmentation areas.
5. The bare soil monitoring method based on high-resolution satellite remote sensing according to claim 2, wherein the calculating of the NVDI time series curve of the pixels in each of the partitioned areas and the calculating of the similarity between the NVDI time series curve of each of the pixels and the standard NVDI time series curve of the bare soil terrain specifically comprises:
the standard NVDI time series curve of the bare soil terrain is obtained by recording the average value of NVDI coefficients of the bare soil terrain at a certain time point;
acquiring a normalized vegetation index NDVI of the pixels in the partitioned area, and acquiring an NDVI time sequence curve of the pixels in the partitioned area through wave band synthesis and SG filtering;
and calculating the similarity between the NVDI time series curve of the pixel and the standard NVDI time series curve of the bare-soil terrain by adopting a Frecher distance algorithm.
6. The bare soil monitoring method based on high-resolution satellite remote sensing according to claim 1, wherein the overlaying of the remote sensing images of the bare soil areas of all the segmented areas and the color composite image of the remote sensing image of the area to be monitored to obtain the bare soil area of the area to be monitored specifically comprises:
performing first waveband calculation on the remote sensing image of the bare soil area of the segmentation area and the color synthetic image of the remote sensing image of the area to be monitored in a remote sensing image processing platform ENVI, wherein the image which meets a first preset condition is a bare soil terrain, and otherwise, removing the image to obtain a first binary image;
performing second band operation on the remote sensing image of the bare soil area of the segmented area and the color synthetic image of the remote sensing image of the area to be monitored in a remote sensing image processing platform ENVI, wherein the remote sensing image meets a second preset condition and is a bare soil terrain, and otherwise, removing the remote sensing image to obtain a second binary image;
and performing logic intersection operation on the first binary image and the second binary image to obtain the bare soil area of the area to be monitored.
7. A bare soil monitoring device based on high-resolution satellite remote sensing, the device comprising:
the acquisition module is used for acquiring a remote sensing image of a region to be monitored, preprocessing the remote sensing image, then segmenting the remote sensing image, and extracting target characteristics of each segmented region;
the extracting module is used for extracting the bare soil area of the segmentation area according to the target characteristics of the segmentation area, the target characteristics of a preset bare soil terrain and a bare soil monitoring model, wherein the bare soil monitoring model is obtained based on U-net neural network model training;
and the synthesis module is used for superposing the extracted images of the bare soil areas of all the segmentation areas and the color synthesis image of the remote sensing image of the area to be monitored to obtain the bare soil area of the area to be monitored.
8. The bare soil monitoring device based on high-resolution satellite remote sensing according to claim 7, wherein:
the acquisition module is specifically used for carrying out radiometric calibration, atmospheric correction and cutting on the remote sensing image to obtain a plurality of segmentation areas;
respectively calculating the NVDI time series curve of the pixels in each divided area, and calculating the similarity between the NVDI time series curve of each pixel and the NVDI time series curve of the standard bare-soil terrain;
taking the segmentation areas with the similarity values larger than a preset threshold value and the number of the pixels larger than a preset number as segmentation areas to be researched;
performing binarization feature extraction on each segmented region to be researched by adopting a feature extraction network to obtain target features of each segmented region to be researched; the characteristic extraction network is constructed based on a hyperbolic function and is obtained by utilizing a floating point characteristic extraction network for training.
9. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method for bare earth monitoring based on high resolution satellite remote sensing according to any one of claims 1 to 6.
10. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor, when executing the program, implements the steps of the method for bare earth monitoring based on high resolution satellite remote sensing according to any one of claims 1 to 6.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116052017A (en) * | 2023-01-17 | 2023-05-02 | 二十一世纪空间技术应用股份有限公司 | Green network thatch cover information remote sensing monitoring method based on double index method and self-adaptive strategy |
| CN117830860A (en) * | 2024-03-06 | 2024-04-05 | 江苏省基础地理信息中心 | Remote sensing automatic extraction method of winter wheat planting structure |
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2021
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116052017A (en) * | 2023-01-17 | 2023-05-02 | 二十一世纪空间技术应用股份有限公司 | Green network thatch cover information remote sensing monitoring method based on double index method and self-adaptive strategy |
| CN116052017B (en) * | 2023-01-17 | 2023-11-10 | 二十一世纪空间技术应用股份有限公司 | Green network thatch cover information remote sensing monitoring method based on double index method and self-adaptive strategy |
| CN117830860A (en) * | 2024-03-06 | 2024-04-05 | 江苏省基础地理信息中心 | Remote sensing automatic extraction method of winter wheat planting structure |
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