CN117994668B - Remote sensing image calculation method, system, equipment and medium for suaeda ptera coverage area - Google Patents
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Abstract
The invention discloses a remote sensing image calculation method, a system, equipment and a medium for a suaeda heteroptera coverage area, and relates to the technical field of remote sensing image processing. The method comprises the following steps: acquiring remote sensing image data of a target area; calculating a ratio vegetation index of the remote sensing image data, and performing assignment extraction on image pixels with the ratio vegetation index being greater than or equal to 1.68 to obtain preliminary screening image data; calculating CIE chromaticity angle alpha of the preliminary screening image data, and carrying out assignment extraction on image pixels with CIE chromaticity angle alpha being more than or equal to 210 degrees to obtain image data of a suaeda heteroptera coverage area; and carrying out statistical calculation on the image data of the suaeda salsa coverage area to obtain the suaeda salsa coverage area. The invention can improve the extraction precision of the existing suaeda heteroptera coverage area.
Description
Technical Field
The invention relates to the technical field of remote sensing image processing, in particular to a remote sensing image calculation method, a remote sensing image calculation system, remote sensing image calculation equipment and a remote sensing image calculation medium for a suaeda heteroptera coverage area.
Background
Suaeda salsa (Suaeda salsa) is one of typical vegetation of coastal wetland in northern China, is a dominant species for improving soil salinization, has a great effect on carbon circulation in coastal areas, and has various important functions of maintaining normal succession of wetland ecosystems, preventing wind, fixing dykes and the like. In recent years, liaoning province has developed a number of corrective actions against Liaohua ecological environment problems, including the ecological restoration project of Suaeda ptera. Therefore, the development of the normalized monitoring of the suaeda heteroptera coverage area becomes one of the main tasks of the ecological environment supervision department.
The coastal wetland has wide distribution area and complex landform, and many areas are difficult to reach by manpower, and the traditional manual monitoring method (an eye estimation method, a probability method, a grid method and the like) cannot meet the monitoring requirement. The remote sensing technology can realize the large-scale and dynamic continuous monitoring capability of the suaeda heteroptera, save time and cost and make up the defects of the traditional measuring method to a great extent. The suaeda heteroptera in the mature stage presents obvious mauve characteristics, is very obvious on a remote sensing image, and some researchers usually adopt a manual interpretation method to draw the distribution range of the suaeda heteroptera, but cannot realize the fine extraction of the coverage area.
Disclosure of Invention
The invention aims to provide a remote sensing image calculation method, a remote sensing image calculation system, remote sensing image calculation equipment and a remote sensing image calculation medium for a suaeda salsa coverage area, which can improve the extraction precision of the existing suaeda salsa coverage area.
In order to achieve the above object, the present invention provides the following solutions:
A remote sensing image calculation method of a suaeda heteroptera coverage area comprises the following steps:
Acquiring remote sensing image data of a target area;
Calculating a ratio vegetation index of the remote sensing image data, and performing assignment extraction on image pixels with the ratio vegetation index being greater than or equal to 1.68 to obtain preliminary screening image data;
Calculating CIE chromaticity angle alpha of the preliminary screening image data, and carrying out assignment extraction on image pixels with CIE chromaticity angle alpha being more than or equal to 210 degrees to obtain image data of a suaeda heteroptera coverage area;
And carrying out statistical calculation on the image data of the suaeda salsa coverage area to obtain the suaeda salsa coverage area.
Optionally, calculating a ratio vegetation index of the remote sensing image data, and performing assignment extraction on image pixels with the ratio vegetation index being greater than or equal to 1.68 to obtain preliminary screening image data, which specifically comprises the following steps:
Calculating the ratio vegetation index of the remote sensing image data by using a ratio vegetation index RVI calculation formula to obtain a ratio vegetation index RVI;
Extracting image pixels meeting the condition according to a formula if RVI is more than or equal to 1.68 then 1 else 0, wherein if, then, else is a condition function, namely assigning 1 to the image pixels meeting the condition threshold, assigning 0 to the image pixels not meeting the condition threshold, and obtaining the extracted preliminary screening image data according to the region with the value of 1.
Optionally, calculating a CIE chromaticity angle α of the preliminary screening image data, and performing assignment extraction on image pixels with the CIE chromaticity angle α being greater than or equal to 210 ° to obtain image data of a suaeda heteroptera coverage area, which specifically includes:
calculating chromaticity coordinates of the preliminary screening image data by using the reflectivity of the selected visible light wave band to obtain chromaticity coordinate values;
According to the formula And calculating a CIE chromaticity angle α from the chromaticity coordinate values; wherein arctan2 represents a bivariate arctangent function, and x and y represent chromaticity coordinate values;
Extracting image pixels meeting the condition according to a formula if alpha is more than or equal to 210 then 2 else 3, wherein if, then, else is a conditional function, the chromaticity angle alpha pixels meeting the condition threshold value are assigned to 2, the chromaticity angle alpha pixels not meeting the condition are assigned to 3, and the image data of the coverage area of the suaeda heteroptera is obtained according to the area assigned to 2.
Optionally, the calculating the chromaticity coordinate of the preliminary screening image data by using the reflectivity of the selected visible light wave band to obtain the chromaticity coordinate value specifically includes:
calculating the tri-primary stimulus value by using a calculation formula of the tri-primary stimulus value and the reflectivity of the selected visible light wave band; the calculation formula of the tri-stimulus value is expressed as follows:
，
wherein X, Y, Z represents a tristimulus value; b2, B3 and B4 respectively represent the reflectivities of the 2 nd, 3 rd and 4 th wave bands in the Landsat 8-9 OLI C2 L2 level remote sensing image;
Calculating a chromaticity coordinate value by using a chromaticity coordinate calculation formula and the tri-primary stimulus value; the calculation formula of the chromaticity coordinates is expressed as follows:
，
wherein x and y are chromaticity coordinate values.
Optionally, performing statistical calculation on the image data of the suaeda salsa coverage area to obtain the suaeda salsa coverage area, which specifically includes:
And counting the number of pixels according to the image data of the suaeda salsa coverage area, calculating to obtain the suaeda salsa coverage area by multiplying the number of pixels by the area of a single pixel, and drawing a corresponding thematic map.
The invention also provides a remote sensing image computing system of the suaeda heteroptera coverage area, which comprises:
The remote sensing image acquisition unit is used for acquiring remote sensing image data of the target area;
The ratio vegetation index calculation unit is used for calculating the ratio vegetation index of the remote sensing image data, and carrying out assignment extraction on image pixels with the ratio vegetation index being more than or equal to 1.68 to obtain preliminary screening image data;
The chromaticity angle calculation unit is used for calculating the CIE chromaticity angle alpha of the preliminary screening image data, and carrying out assignment extraction on image pixels with the CIE chromaticity angle alpha being more than or equal to 210 degrees to obtain the image data of the suaeda heteroptera covering area;
and the suaeda heteroptera coverage area calculation unit is used for carrying out statistical calculation on the image data of the suaeda heteroptera coverage area to obtain the suaeda heteroptera coverage area.
The invention also provides electronic equipment, which comprises a memory and a processor, wherein the memory is used for storing a computer program, and the processor runs the computer program to enable the electronic equipment to execute the remote sensing image calculation method of the suaeda heteroptera coverage area.
The invention also provides a computer readable storage medium storing a computer program which when executed by a processor implements a remote sensing image calculation method of a suaeda heteroptera coverage area as described above.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
The invention discloses a remote sensing image calculation method, a system, equipment and a medium of a suaeda heteroptera coverage area, wherein the method comprises the steps of obtaining remote sensing image data of a target area; calculating a ratio vegetation index of the remote sensing image data, and performing assignment extraction on image pixels with the ratio vegetation index being greater than or equal to 1.68 to obtain preliminary screening image data; calculating CIE chromaticity angle alpha of the preliminary screening image data, and carrying out assignment extraction on image pixels with CIE chromaticity angle alpha being more than or equal to 210 degrees to obtain image data of a suaeda heteroptera coverage area; and carrying out statistical calculation on the image data of the suaeda salsa coverage area to obtain the suaeda salsa coverage area. The invention can improve the extraction precision of the existing suaeda heteroptera coverage area.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the drawings that are needed in the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a remote sensing image calculation method of a suaeda heteroptera coverage area;
FIG. 2 is a schematic diagram of an original true color remote sensing image in embodiment 1;
FIG. 3 is a remote sensing extraction thematic map of the coverage status of suaeda heteroptera in the embodiment 1;
FIG. 4 is a schematic diagram of an original true color remote sensing image in embodiment 2;
FIG. 5 is a remote sensing extraction thematic map of the coverage status of suaeda heteroptera in example 2;
FIG. 6 is a schematic diagram of an original true color remote sensing image in embodiment 3;
fig. 7 is a remote sensing extraction thematic map of the coverage condition of suaeda heteroptera in this example 3.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention aims to provide a remote sensing image calculation method, a remote sensing image calculation system, remote sensing image calculation equipment and a remote sensing image calculation medium for a suaeda salsa coverage area, which can improve the extraction precision of the existing suaeda salsa coverage area.
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description.
As shown in fig. 1, the invention provides a remote sensing image calculation method of a suaeda heteroptera coverage area, which comprises the following steps:
step 100: acquiring remote sensing image data of a target area;
step 200: calculating a ratio vegetation index of the remote sensing image data, and performing assignment extraction on image pixels with the ratio vegetation index being greater than or equal to 1.68 to obtain preliminary screening image data;
Step 300: calculating CIE chromaticity angle alpha of the preliminary screening image data, and carrying out assignment extraction on image pixels with CIE chromaticity angle alpha being more than or equal to 210 degrees to obtain image data of a suaeda heteroptera coverage area;
step 400: and carrying out statistical calculation on the image data of the suaeda salsa coverage area to obtain the suaeda salsa coverage area.
Based on the above technical solution, a more detailed procedure is provided.
As a specific embodiment of step 100, specifically including:
the Landsat 8-9 OLI C2 L2 level remote sensing image data is downloaded over EarthExplorer-functional networks (https:// earthoxplorer. Usgs. Gov /). Considering that green vegetation such as reed turns yellow in autumn and winter, the green vegetation is difficult to distinguish from suaeda heteroptera, and a remote sensing image in a period of 5-9 months is preferably selected.
As a specific embodiment of step 200, it includes:
Calculating the ratio vegetation index of the remote sensing image data by using a ratio vegetation index RVI calculation formula to obtain a ratio vegetation index RVI; the ratio vegetation index RVI calculation formula:
，
wherein RVI represents the ratio vegetation index; b5 The (near infrared band) and the B4 (red band) respectively show the reflectivities of the 5 th and 4 th bands in the Landsat 8-9 OLI C2 L2 level remote sensing image.
The vegetation information is determined when RVI is more than or equal to 1.68 through early-stage research, and the research process is as follows:
And downloading a multi-view satellite image of the suaeda heteroptera distribution area, carrying out histogram equalization stretching treatment on the original true color image, screening out characteristic images of vegetation (green vegetation, suaeda heteroptera and the like) and water body tidal flat respectively, and calculating RVI of each pixel of the characteristic images. Because of the huge number of image pixels, in order to display the distribution situation of RVI values in a refined manner and further determine an RVI threshold more accurately, "(b1 LE C0)*(b1/b1*C0) + (b1 GT C0)*(b1 LE C1)*(b1/b1*C1) + (b1 GT C1)*(b1 LE C2)*(b1/b1*C2) + (b1 GT C2)*(b1 LE C3)*(b1/b1*C3) + (b1 GT C3)*(b1 LE C4)*(b1/b1*C4) + (b1 GT C4)*(b1 LE C5)*(b1/b1*C5) + ∙∙∙∙∙∙ + (b1 GT Cx-2)*(b1 LE Cx-1)*(b1/b1*Cx-1) + (b1 GT Cx-1)*(b1/b1*Cx)"（b1 is adopted in the patent to calculate a default variable form for values in ENVI software, and the variable form represents RVI; c 0、C1、∙∙∙∙∙∙、Cx-1、Cx represents a boundary constant set in an RVI numerical value statistical interval, the value is 1.0-2.0), and the boundary constant is used as an extraction algorithm to more finely distinguish a possible overlapping area of vegetation and a water body beach RVI numerical value, so that the RVI numerical value after the refinement treatment and the corresponding pixel number are obtained, a scatter diagram of the RVI and pixel number distribution is drawn, the vegetation identification accuracy is analyzed, the vegetation can be effectively distinguished from the water body beach when the RVI is more than or equal to 1.68, and the identification accuracy is highest, namely the vegetation information is determined when the RVI is more than or equal to 1.68.
The result after vegetation information extraction is represented by result_ vegetation, and the extraction algorithm is as follows:
Extracting image pixels meeting the condition according to a formula if RVI is more than or equal to 1.68 then 1 else 0, wherein if, then, else is a condition function, the image pixels meeting the condition threshold are assigned to 1, representing vegetation (suaeda heteroptera, reed and the like), the image pixels not meeting the condition threshold are assigned to 0, representing water body beach and the like, and the extracted preliminary screening image data is obtained according to the area with the assigned value of 1.
As a specific embodiment of step 300, it includes:
First, X, Y, Z tristimulus values were calculated:
Aiming at Landsat 8-9 OLI C2 L2 level remote sensing images, the calculation formula of the X, Y, Z three primary color stimulus values is as follows:
，
wherein X, Y, Z represents a tristimulus value; b2, B3 and B4 respectively represent the reflectivities of the 2 nd, 3 rd and 4 th wave bands (visible light wave bands) in the Landsat 8-9 OLI C2 L2 level remote sensing image.
Secondly, chromaticity coordinates x and y are calculated:
the calculation formula of the x and y chromaticity coordinates is as follows:
，
wherein x and y represent chromaticity coordinate values.
Then, CIE chromaticity angle α calculation is performed:
the chromaticity angle α is calculated as follows:
，
Wherein α represents a chromaticity angle; arctan2 represents a bivariate arctangent function.
Finally, extracting suaeda heteroptera information:
And removing non-vegetation (water, mud flat, and the like) pixels in the CIE chromaticity angle image by using a result of extraction of vegetation information, namely result_ vegetation, and only preserving the CIE chromaticity angle of the vegetation (suaeda heteroptera, reed, and the like) pixels.
The early research shows that the Suaeda ptera information is determined when the CIE chromaticity angle alpha is more than or equal to 210 DEG, and the research process is as follows:
And downloading a multi-view satellite image of the suaeda salsa distribution area, carrying out histogram equalization stretching treatment on the original true color image, screening out characteristic images of the green vegetation and the suaeda salsa respectively, and calculating CIE chromaticity angle alpha of each pixel of the characteristic images. Because of the huge number of image pixels, in order to finely display the distribution situation of the CIE chromaticity angle alpha and further accurately determine the CIE chromaticity angle alpha threshold value, "(b1 LE α0)*(b1/b1*α0) + (b1 GT α0)*(b1 LE α1)*(b1/b1*α1) + (b1 GT α1)*(b1 LE α2)*(b1/b1*α2) + (b1 GT α2)*(b1 LE α3)*(b1/b1*α3) + (b1 GT α3)*(b1 LE α4)*(b1/b1*α4) + (b1 GT α4)*(b1 LE α5)*(b1/b1*α5) + ∙∙∙∙∙∙ + (b1 GT αx-2)*(b1 LE αx-1)*(b1/b1*αx-1) + (b1 GT αx-1)*(b1/b1*αx)"（b1 is adopted in the patent to calculate a default variable form for numerical value in ENVI software, and the default variable form represents the CIE chromaticity angle alpha; alpha 0、α1、∙∙∙∙∙∙、αx-1、αx represents a boundary constant set in a statistical interval of a CIE chromaticity angle alpha numerical value, the value is between 200 and 220 degrees), and the possible overlapping area of the green vegetation and the Suaeda ptera CIE chromaticity angle alpha is further finely distinguished by taking the boundary constant as an extraction algorithm, so that the CIE chromaticity angle alpha after fine processing and the corresponding pixel number are obtained, a scatter diagram of the CIE chromaticity angle alpha and the pixel number distribution is drawn, the accuracy of Suaeda ptera identification is analyzed, the green vegetation and the Suaeda ptera can be effectively distinguished when the CIE chromaticity angle alpha is more than or equal to 210 degrees, and the identification accuracy is the highest, namely, the Suaeda ptera information is determined when the CIE chromaticity angle alpha is more than or equal to 210 degrees.
The result after the Suaeda heteroptera information extraction is expressed as 'result_suaeda salsa', and the extraction algorithm is as follows:
if α ≥ 210 then 2 else 3
Wherein if, then, else denotes a conditional function, i.e. a chromaticity angle alpha pixel meeting the condition is assigned to 2, which represents the suaeda heteroptera, and a chromaticity angle alpha pixel not meeting the condition is assigned to 3, which represents green vegetation such as reed.
As a specific embodiment of step 300, it includes:
And respectively counting the pixel numbers of which the pixel values are 0 (water body beach), 2 (Suaeda ptera) and 3 (green vegetation such as reed) in the research area by using the information extraction results of result_ vegetation and result_suaeda salsa, and calculating the coverage area and the duty ratio. The "number of pels" can be statistically derived by the ENVI software, and the "area" is calculated from the number of pels times the area of a single pel (0.0009 square kilometer).
The result of the information extraction of result_ vegetation and result_Suaeda salsa is made into a remote sensing thematic map, so that the coverage condition of the Suaeda heteroptera can be displayed more intuitively. When the thematic map is drawn, the pixel value 0 is represented by light gray, and represents the water body beach; the pixel value 2 is represented by black and represents suaeda heteroptera; the pixel value 3 is represented by dark gray, and represents green vegetation such as reed and the like.
Based on the above steps, the following examples are provided.
Example 1
Downloading 2023, 8, 23 Liaokou coastal wetland Landsat 8 OLI C2 L2 level remote sensing image 'L08_L2SP_120032_20230823_20230826_02_T1', wherein the original true color remote sensing image is shown in figure 2, and a detailed remote sensing map of the coverage condition of the suaeda heteroptera, which is drawn by the method disclosed by the patent, is shown in figure 3. It can be found that the remote sensing image extraction result of the suaeda salsa coverage condition has very good consistency with the suaeda salsa coverage condition in the true color image, and the area and the duty ratio calculation result of the suaeda salsa and other land object types are shown in table 1.
Table 1 calculation results
，
Example 2
Downloading a remote sensing image of 'L08_L2SP_120032_20220820_202209223_02_T1' of the Landsat 8 months 20 days Liaokou coastal wetland Landsat 8 OLI C2 L2, wherein an original true color remote sensing image is shown in fig. 4, and a remote sensing thematic map of the coverage condition of the suaeda heteroptera, which is drawn by the method disclosed by the patent, is shown in fig. 5. It can also be found that the remote sensing image extraction result of the suaeda salsa coverage condition has very good consistency with the suaeda salsa coverage condition in the true color image, and the area and the duty ratio calculation result of the land object types such as the suaeda salsa are shown in table 2.
Table 2 calculation results
，
Example 3
Downloading a grade remote sensing image "L08_L2SP_120032_20210902_20210909_02_T1" of the Landsat 8 OLI C2 L2 of the coastal wetland of 9 months of 2021, wherein an original true color remote sensing image is shown in FIG. 6, and a remote sensing thematic map of the coverage condition of the suaeda heteroptera, which is drawn by the method disclosed by the patent, is shown in FIG. 7. It can also be found that the remote sensing image extraction result of the suaeda salsa coverage condition has very good consistency with the suaeda salsa coverage condition in the true color image, and the area and the duty ratio calculation result of the land object types such as the suaeda salsa are shown in table 3.
TABLE 3 calculation results
，
Therefore, the reflection spectrum of the suaeda salt marsh vegetation has obvious red edge characteristic, and the remote sensing extraction of suaeda information can be carried out by utilizing various vegetation indexes, such as normalized vegetation indexes (Normalized Difference Vegetation Index, NDVI), ratio vegetation indexes (Ratio Vegetation Index, RVI), enhanced vegetation indexes (Enhanced Vegetation Index, EVI) and the like. However, the threshold value of the indexes is a key point of whether the coverage area calculation of the suaeda heteroptera is accurate or not, and is related to the quality of remote sensing images, the distribution characteristics of ground objects in a research area and the like. Normally, the vegetation indexes of the suaeda heteroptera and the reed are obviously larger than those of water bodies and beaches, the vegetation indexes of the suaeda heteroptera are slightly lower than those of green vegetation such as the reed, but the threshold intervals are overlapped, so that the false judgment probability of the green vegetation with low coverage is higher, and the extraction precision is greatly reduced.
In the embodiment, the significant difference between the vegetation index RVI and the CIE chromaticity angle value range of the ratio of the suaeda heteroptera to the wetland objects such as water bodies, beaches, reeds and the like on the remote sensing image is utilized for extraction and coverage area calculation. The basic principle is as follows: (1) RVI of vegetation such as suaeda heteroptera and reed is obviously higher than 1.68, RVI of water and mud flat is obviously lower than 1.68, and based on the characteristics, vegetation information such as suaeda heteroptera and reed in the coastal wetland can be extracted in advance by utilizing an RVI threshold (RVI is more than or equal to 1.68), and the water and mud flat information is removed; (2) The value ranges of green vegetation RVI such as the suaeda heteroptera and the reed are overlapped, the two are not distinguished by RVI, but the purple suaeda heteroptera and the green reed are obviously different in color, the red suaeda heteroptera and the green reed can be perfectly distinguished by utilizing the CIE chromaticity angle, researches find that the chromaticity angle alpha of the suaeda heteroptera is obviously higher than 210 degrees, the green vegetation such as the reed is obviously lower than 210 degrees, and the green vegetation information such as the reed can be removed by utilizing the CIE chromaticity angle threshold value (alpha is more than or equal to 210 degrees) based on the characteristics.
In the embodiment, landsat 8-9 OLI C2 L2 level remote sensing images are taken as data sources, RVI and CIE chromaticity angles are calculated, remote sensing image extraction of suaeda salsa information is carried out based on the threshold conditions, and finally coverage areas of suaeda salsa are obtained. Compared with other extraction methods, the method of the embodiment can effectively improve the calculation efficiency and the accuracy of the suaeda heteroptera coverage area.
In addition, the invention also provides a remote sensing image computing system of the suaeda heteroptera coverage area, which comprises the following steps:
The remote sensing image acquisition unit is used for acquiring remote sensing image data of the target area;
The ratio vegetation index calculation unit is used for calculating the ratio vegetation index of the remote sensing image data, and carrying out assignment extraction on image pixels with the ratio vegetation index being more than or equal to 1.68 to obtain preliminary screening image data;
The chromaticity angle calculation unit is used for calculating the CIE chromaticity angle alpha of the preliminary screening image data, and carrying out assignment extraction on image pixels with the CIE chromaticity angle alpha being more than or equal to 210 degrees to obtain the image data of the suaeda heteroptera covering area;
and the suaeda heteroptera coverage area calculation unit is used for carrying out statistical calculation on the image data of the suaeda heteroptera coverage area to obtain the suaeda heteroptera coverage area.
The invention provides electronic equipment, which comprises a memory and a processor, wherein the memory is used for storing a computer program, and the processor runs the computer program to enable the electronic equipment to execute the remote sensing image calculation method of the suaeda heteroptera coverage area.
The present invention provides a computer readable storage medium storing a computer program which when executed by a processor implements a remote sensing image calculation method for a suaeda heteroptera coverage area as described above.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other.
The principles and embodiments of the present invention have been described herein with reference to specific examples, the description of which is intended only to assist in understanding the core concept of the invention; also, it is within the scope of the present invention to be modified by those of ordinary skill in the art in light of the present teachings. In view of the foregoing, this description should not be construed as limiting the invention.
Claims (6)
1. The method for calculating the remote sensing image of the suaeda heteroptera coverage area is characterized by comprising the following steps of:
Acquiring remote sensing image data of a target area;
Calculating a ratio vegetation index of the remote sensing image data, and performing assignment extraction on image pixels with the ratio vegetation index being greater than or equal to 1.68 to obtain preliminary screening image data;
Calculating CIE chromaticity angle alpha of the preliminary screening image data, and carrying out assignment extraction on image pixels with CIE chromaticity angle alpha being more than or equal to 210 degrees to obtain image data of a suaeda heteroptera coverage area;
carrying out statistical calculation on the image data of the suaeda salsa coverage area to obtain the suaeda salsa coverage area;
Calculating a ratio vegetation index of the remote sensing image data, and performing assignment extraction on image pixels with the ratio vegetation index being greater than or equal to 1.68 to obtain preliminary screening image data, wherein the method specifically comprises the following steps:
Calculating the ratio vegetation index of the remote sensing image data by using a ratio vegetation index RVI calculation formula to obtain a ratio vegetation index RVI;
Extracting image pixels meeting the condition according to a formula if RVI is more than or equal to 1.68 then 1 else 0, wherein if, then, else is a condition function, namely, assigning 1 to the image pixels meeting the condition threshold, assigning 0 to the image pixels not meeting the condition threshold, and obtaining extracted preliminary screening image data according to the region with the value of 1;
calculating CIE chromaticity angle alpha of the preliminary screening image data, and carrying out assignment extraction on image pixels with CIE chromaticity angle alpha being more than or equal to 210 degrees to obtain image data of a suaeda ptera coverage area, wherein the method specifically comprises the following steps:
calculating chromaticity coordinates of the preliminary screening image data by using the reflectivity of the selected visible light wave band to obtain chromaticity coordinate values;
According to the formula And calculating a CIE chromaticity angle α from the chromaticity coordinate values; wherein arctan2 represents a bivariate arctangent function, and x and y represent chromaticity coordinate values;
Extracting image pixels meeting the condition according to a formula if alpha is more than or equal to 210 then 2 else 3, wherein if, then, else is a conditional function, the chromaticity angle alpha pixels meeting the condition threshold value are assigned to 2, the chromaticity angle alpha pixels not meeting the condition are assigned to 3, and the image data of the coverage area of the suaeda heteroptera is obtained according to the area assigned to 2.
2. The method for calculating a remote sensing image of a coverage area of suaeda heteroptera according to claim 1, wherein the calculating the chromaticity coordinate of the preliminary screening image data by using the reflectivity of the selected visible light band to obtain the chromaticity coordinate value specifically comprises:
calculating the tri-primary stimulus value by using a calculation formula of the tri-primary stimulus value and the reflectivity of the selected visible light wave band; the calculation formula of the tri-stimulus value is expressed as follows:
，
wherein X, Y, Z represents a tristimulus value; b2, B3 and B4 respectively represent the reflectivities of the 2 nd, 3 rd and 4 th wave bands in the Landsat 8-9 OLI C2 L2 level remote sensing image;
Calculating a chromaticity coordinate value by using a chromaticity coordinate calculation formula and the tri-primary stimulus value; the calculation formula of the chromaticity coordinates is expressed as follows:
，
wherein x and y are chromaticity coordinate values.
3. The method for calculating a remote sensing image of a suaeda salsa coverage area according to claim 1, wherein the method for calculating the image data of the suaeda salsa coverage area to obtain the suaeda salsa coverage area comprises the following steps:
And counting the number of pixels according to the image data of the suaeda salsa coverage area, calculating to obtain the suaeda salsa coverage area by multiplying the number of pixels by the area of a single pixel, and drawing a corresponding thematic map.
4. A remote sensing image computing system of suaeda heteroptera coverage area, applied to the method of any one of claims 1-3, comprising:
The remote sensing image acquisition unit is used for acquiring remote sensing image data of the target area;
The ratio vegetation index calculation unit is used for calculating the ratio vegetation index of the remote sensing image data, and carrying out assignment extraction on image pixels with the ratio vegetation index being more than or equal to 1.68 to obtain preliminary screening image data;
The chromaticity angle calculation unit is used for calculating the CIE chromaticity angle alpha of the preliminary screening image data, and carrying out assignment extraction on image pixels with the CIE chromaticity angle alpha being more than or equal to 210 degrees to obtain the image data of the suaeda heteroptera covering area;
and the suaeda heteroptera coverage area calculation unit is used for carrying out statistical calculation on the image data of the suaeda heteroptera coverage area to obtain the suaeda heteroptera coverage area.
5. An electronic device comprising a memory for storing a computer program and a processor that runs the computer program to cause the electronic device to perform the method of remote sensing image calculation of suaeda heteroptera coverage area according to any one of claims 1-3.
6. A computer readable storage medium, characterized in that it stores a computer program, which when executed by a processor, implements a method of remote sensing image calculation of a suaeda heteroptera coverage area according to any one of claims 1-3.
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| CN114187538A (en) * | 2022-02-17 | 2022-03-15 | 航天宏图信息技术股份有限公司 | Multispectral vegetation monitoring interference information eliminating method and device |
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