Method for monitoring duckweed type eutrophication water body based on sentinel-2 satellite image

Abstract

The application discloses a kind of based on sentinel-2 satellite image's duckweed type eutrophication water monitoring method, it is related to water monitoring technical field, including the following steps: after the atmospheric correction processing of sentinel-2 L1 C level satellite image of non-duckweed growing season and duckweed growing season, all wavebands are resampled to the same resolution, after mean filtering to the blue band, green band, red band, near infrared band, narrow near infrared band of multi-band surface reflectance image after resampling of non-duckweed growing season and duckweed growing season, then band synthesis is carried out, obtain non-duckweed growing season band synthesis image and duckweed growing season band synthesis image;The proportion of duckweed growing range in water range is calculated using non-duckweed growing season band synthesis image and duckweed growing season band synthesis image.The present application can realize the fast, large-scale, low-cost duckweed type eutrophication water monitoring.

Description

Technical Field

[0001] This invention relates to the field of water body monitoring technology, and more specifically to a method for monitoring duckweed-type eutrophic water bodies based on Sentinel-2 satellite imagery. Background Technology

[0002] Currently, in the supervision of rural water ecological environment, the main methods used are manual ground investigation and remote sensing monitoring based on deep learning to identify duckweed-type eutrophic water bodies in order to understand the eutrophication of water bodies and the coverage of duckweed.

[0003] However, manual investigation is inefficient and has limited coverage, making it difficult to deal with the widely distributed and scattered rural water bodies, especially in areas with inconvenient transportation, and it consumes a lot of manpower and resources. While remote sensing monitoring methods based on deep learning have a certain degree of automation, the model building, sample training and technical maintenance have high thresholds, which are not conducive to grassroots environmental protection workers to directly master and apply them.

[0004] Therefore, how to provide a monitoring method for duckweed-type eutrophic water bodies that can achieve rapid, large-scale, and low-cost monitoring of duckweed-type eutrophic water bodies, while also being easy to operate, highly repeatable, and convenient for grassroots operational applications, has become an urgent problem for those skilled in the art to solve. Summary of the Invention

[0005] In view of the above problems, the present invention is proposed to provide a method for monitoring duckweed-type eutrophic water bodies based on Sentinel-2 satellite imagery that overcomes or at least partially solves the above problems.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] A method for monitoring duckweed-type eutrophic water bodies based on Sentinel-2 satellite imagery includes the following steps:

[0008] Acquire Sentinel-2 L1 C satellite images of the monitoring area during the non-duckweed growing season and during the duckweed growing season;

[0009] Atmospheric correction processing was performed on the Sentinel-2 L1 C satellite images during the non-duckweed growing season and the Sentinel-2 L1 C satellite images during the duckweed growing season to obtain multi-band surface reflectance images during the non-duckweed growing season and multi-band surface reflectance images during the duckweed growing season.

[0010] All bands in the multi-band surface reflectance image of the non-duckweed growing season and the multi-band surface reflectance image of the duckweed growing season are resampled to the same resolution to obtain the multi-band surface reflectance image of the non-duckweed growing season and the multi-band surface reflectance image of the duckweed growing season.

[0011] The blue band, green band, red band, near-infrared band, and narrow near-infrared band of the multi-band surface reflectance image after resampling during the non-duckweed growing season are subjected to mean filtering and then band synthesis to obtain a band synthesis image of the non-duckweed growing season.

[0012] The blue band, green band, red band, near-infrared band, and narrow near-infrared band of the multi-band surface reflectance image after resampling during the duckweed growing season are subjected to mean filtering and then band synthesis to obtain a composite image of the duckweed growing season.

[0013] The proportion of the water body covered by duckweed growth range is calculated using the composite image of the non-duckweed growth season and the composite image of the duckweed growth season.

[0014] Preferably, the calculation of the proportion of the duckweed growth area to the water body area using the composite image of the non-duckweed growth season and the composite image of the duckweed growth season specifically includes the following steps:

[0015] Calculate the water index of each pixel in the composite image of the non-duckweed growth season;

[0016] The water index of each pixel is compared with a preset water index threshold to obtain a first binary image; wherein, the first binary image is a binary image that distinguishes between water bodies and non-water bodies;

[0017] Convert the first binary image into water body range vector data;

[0018] The cropped image is obtained by cropping the duckweed growth seasonal band composite image based on the water body range vector data; wherein, the cropped image is a duckweed growth seasonal band composite image that only includes the water body area;

[0019] Calculate the duckweed recognition index of each pixel in the cropped image;

[0020] The duckweed recognition index of each pixel is compared with a preset duckweed recognition index threshold to obtain a second binary image; wherein, the second binary image is a binary image that distinguishes between duckweed and non-duckweed.

[0021] Calculate the water area and duckweed area in the second binary image;

[0022] The proportion of the duckweed's growth area to the water body area is calculated using the duckweed's area and the water body area.

[0023] Preferably, the water index of each pixel in the composite image of the non-duckweed growth season is calculated based on the following formula:

[0024] NDWI i =(R i (Green)-R i (Nir)) / (R i (Green)+R i (Nir));

[0025] In the formula, NDWI i R represents the water index of the i-th pixel in the composite image of the non-duckweed growth season; i = 1, 2, ..., I; I represents the number of pixels included in the composite image of the non-duckweed growth season; i (Green) represents the green band reflectance of the i-th pixel in the composite image of the non-duckweed growth season; R i (Nir) represents the near-infrared reflectance of the i-th pixel in the composite image of the non-duckweed growth season.

[0026] Preferably, the water index of each pixel is compared with a preset water index threshold to obtain a first binary image, specifically including the following steps:

[0027] Determine whether the water index of each pixel in the composite image of the non-duckweed growth season is greater than the preset water index threshold: if it is greater, set the pixel value of the corresponding pixel to 1, otherwise set it to 0.

[0028] Preferably, the duckweed recognition index of each pixel in the cropped image is calculated based on the following formula:

[0029] ;

[0030] In the formula, DKI (j) R represents the duckweed recognition index of the j-th pixel in the cropped image; j = 1, 2, ..., J; J represents the number of pixels included in the cropped image; (j) (Nir) represents the near-infrared reflectance of the j-th pixel in the cropped image; R (j) (Narrow Nir) represents the narrow near-infrared reflectance of the j-th pixel in the cropped image; R (j) (Red) represents the red band reflectance of the j-th pixel in the cropped image; R (j) (Blue) represents the blue band reflectance of the j-th pixel in the cropped image.

[0031] Preferably, the duckweed recognition index of each pixel is compared with a preset duckweed recognition index threshold to obtain a second binary image, specifically including the following steps:

[0032] Determine whether the duckweed recognition index of each pixel in the cropped image is greater than the preset duckweed recognition index threshold: if it is greater, set the pixel value of the corresponding pixel to 1, otherwise set it to 0.

[0033] Preferably, the proportion of the duckweed's growth area to the water body area is calculated based on the following formula:

[0034] φ = S1 / S2 × 100%;

[0035] In the formula, φ represents the proportion of the duckweed's growth area to the water body area; S1 represents the duckweed area; and S2 represents the water body area.

[0036] Preferably, the SEN2COR tool is used to perform atmospheric correction processing on the Sentinel-2 L1 C satellite images during the non-duckweed growing season and the Sentinel-2 L1 C satellite images during the duckweed growing season.

[0037] Preferably, the same resolution is a 10-meter resolution.

[0038] As can be seen from the above technical solution, compared with the prior art, the present invention discloses a method for monitoring duckweed-type eutrophic water bodies based on Sentinel-2 satellite imagery, which can realize rapid, large-scale, and low-cost monitoring of duckweed-type eutrophic water bodies, and has the characteristics of simple operation, strong repeatability, and easy application at the grassroots level. Attached Figure Description

[0039] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0040] Figure 1 This is a flowchart illustrating a method for monitoring duckweed-type eutrophic water bodies based on Sentinel-2 satellite imagery, provided in an embodiment of the present invention. Detailed Implementation

[0041] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0042] like Figure 1 As shown in the figure, this invention discloses a method for monitoring duckweed-type eutrophic water bodies based on Sentinel-2 satellite imagery, comprising the following steps:

[0043] Acquire Sentinel-2 L1 C satellite images of the monitoring area during the non-duckweed growing season and during the duckweed growing season;

[0044] Atmospheric correction processing was performed on the Sentinel-2 L1 C satellite images during the non-duckweed growing season and the Sentinel-2 L1 C satellite images during the duckweed growing season to obtain multi-band surface reflectance images during the non-duckweed growing season and multi-band surface reflectance images during the duckweed growing season.

[0045] In one or more embodiments, the SEN2COR tool is used to perform atmospheric correction processing on Sentinel-2 L1 C satellite images during the non-duckweed growing season and Sentinel-2 L1 C satellite images during the duckweed growing season.

[0046] Specifically: The SEN2COR tool was used to perform atmospheric correction processing on the Sentinel-2 L1 C-class satellite imagery during the non-duckweed growing season to obtain multi-band surface reflectance images during the non-duckweed growing season.

[0047] The SEN2COR tool was used to perform atmospheric correction on the Sentinel-2 L1 C satellite imagery of the duckweed growing season to obtain multi-band surface reflectance images of the duckweed growing season.

[0048] All bands in the multi-band surface reflectance image of the non-duckweed growing season and the multi-band surface reflectance image of the duckweed growing season are resampled to the same resolution to obtain the multi-band surface reflectance image of the non-duckweed growing season and the multi-band surface reflectance image of the duckweed growing season.

[0049] In one or more embodiments, all bands of the multi-band surface reflectance image during the non-duckweed growing season are resampled to 10-meter resolution to obtain a multi-band surface reflectance image after resampling during the non-duckweed growing season.

[0050] All bands in the multi-band surface reflectance image of the duckweed growing season are resampled to 10-meter resolution to obtain the resampled multi-band surface reflectance image of the duckweed growing season.

[0051] The blue band, green band, red band, near-infrared band, and narrow near-infrared band of the multi-band surface reflectance image after resampling during the non-duckweed growing season are subjected to mean filtering and then band synthesis to obtain a band synthesis image of the non-duckweed growing season.

[0052] Specifically: the blue band, green band, red band, near-infrared band, and narrow near-infrared band of the multi-band surface reflectance image after resampling during the non-duckweed growing season are subjected to mean filtering. Then, the mean-filtered blue band, green band, red band, near-infrared band, and narrow near-infrared band are combined to obtain a band composite image of the non-duckweed growing season.

[0053] In one or more embodiments, the mean filtering is performed using a 3 (pixel) * 3 (pixel) rectangular window (i.e., corresponding to 30m * 30m).

[0054] The expression for the mean filtering is: Rnew = ;

[0055] Rnew represents the reflectance of a pixel after filtering in the blue band (or green band, or red band, or near-infrared band, or narrow near-infrared band); It represents the blue band (or green band, or red band, or near-infrared band, or narrow near-infrared band) reflectance of the i-th pixel in a 3*3 pixel block centered on the aforementioned pixel.

[0056] The blue band, green band, red band, near-infrared band, and narrow near-infrared band of the multi-band surface reflectance image after resampling during the duckweed growing season are subjected to mean filtering and then band synthesis to obtain a composite image of the duckweed growing season.

[0057] Specifically: the blue band, green band, red band, near-infrared band, and narrow near-infrared band of the multi-band surface reflectance image after resampling during the duckweed growing season are subjected to mean filtering. Then, the mean-filtered blue band, green band, red band, near-infrared band, and narrow near-infrared band are combined to obtain a composite image of the duckweed growing season.

[0058] In one or more embodiments, the mean filtering is performed using a 3*3 rectangular window;

[0059] The expression for the mean filtering is: Rnew = ;

[0060] Rnew represents the reflectance of a pixel after filtering in the blue band (or green band, or red band, or near-infrared band, or narrow near-infrared band); It represents the blue band (or green band, or red band, or near-infrared band, or narrow near-infrared band) reflectance of the i-th pixel in a 3*3 pixel block centered on the aforementioned pixel.

[0061] The proportion of the water body covered by duckweed growth range is calculated using the composite image of the non-duckweed growth season and the composite image of the duckweed growth season.

[0062] In one or more embodiments, the proportion of the duckweed growth area to the water body area is calculated using the composite image of the non-duckweed growth seasonal band and the composite image of the duckweed growth seasonal band, specifically including the following steps:

[0063] Calculate the water index of each pixel in the composite image of the non-duckweed growth season;

[0064] In one or more embodiments, the water index of each pixel in the non-duckweed growth monsoon composite image is calculated based on the following formula:

[0065] NDWI i =(R i (Green)-R i (Nir)) / (R i (Green)+R i (Nir));

[0066] In the formula, NDWI i R represents the water index of the i-th pixel in the composite image of the non-duckweed growth season; i = 1, 2, ..., I; I represents the number of pixels included in the composite image of the non-duckweed growth season; i (Green) represents the green band reflectance of the i-th pixel in the composite image of the non-duckweed growth season; R i (Nir) represents the near-infrared reflectance of the i-th pixel in the composite image of the non-duckweed growth season.

[0067] The water index of each pixel is compared with a preset water index threshold to obtain a first binary image; wherein, the first binary image is a binary image that distinguishes between water bodies and non-water bodies;

[0068] In one embodiment, the water index of each pixel is compared with a preset water index threshold to obtain a first binary image, specifically including the following steps:

[0069] Determine whether the water index of each pixel in the composite image of the non-duckweed growth season is greater than the preset water index threshold: if it is greater, set the pixel value of the corresponding pixel to 1, otherwise set it to 0.

[0070] In another embodiment, the water index of each pixel is compared with a preset water index threshold to obtain a first binary image, specifically including the following steps:

[0071] Determine whether the water index of each pixel in the composite image of the non-duckweed growth season is greater than the preset water index threshold: if it is greater, set the pixel value of the corresponding pixel to 0, otherwise set it to 1.

[0072] Convert the first binary image into water body range vector data;

[0073] The cropped image is obtained by cropping the duckweed growth seasonal band composite image based on the water body range vector data; wherein, the cropped image is a duckweed growth seasonal band composite image that only includes the water body area;

[0074] Calculate the duckweed recognition index of each pixel in the cropped image;

[0075] In one or more embodiments, the duckweed recognition index of each pixel in the cropped image is calculated based on the following formula:

[0076] ;

[0077] In the formula, DKI (j) R represents the duckweed recognition index of the j-th pixel in the cropped image; j = 1, 2, ..., J; J represents the number of pixels included in the cropped image; (j) (Nir) represents the near-infrared reflectance of the j-th pixel in the cropped image; R (j) (Narrow Nir) represents the narrow near-infrared reflectance of the j-th pixel in the cropped image; R (j) (Red) represents the red band reflectance of the j-th pixel in the cropped image; R (j) (Blue) represents the blue band reflectance of the j-th pixel in the cropped image.

[0078] The duckweed recognition index of each pixel is compared with a preset duckweed recognition index threshold to obtain a second binary image; wherein, the second binary image is a binary image that distinguishes between duckweed and non-duckweed.

[0079] In one embodiment, the duckweed recognition index of each pixel is compared with a preset duckweed recognition index threshold to obtain a second binary image, specifically including the following steps:

[0080] Determine whether the duckweed recognition index of each pixel in the cropped image is greater than the preset duckweed recognition index threshold: if it is greater, set the pixel value of the corresponding pixel to 1, otherwise set it to 0.

[0081] In another embodiment, the duckweed recognition index of each pixel is compared with a preset duckweed recognition index threshold to obtain a second binary image, specifically including the following steps:

[0082] Determine whether the duckweed recognition index of each pixel in the cropped image is greater than the preset duckweed recognition index threshold: if it is greater, set the pixel value of the corresponding pixel to 0, otherwise set it to 1.

[0083] Calculate the water area and duckweed area in the second binary image;

[0084] The proportion of the duckweed's growth area to the water body area is calculated using the duckweed's area and the water body area.

[0085] It is understood that the water area includes both the water area covered by duckweed and the water area not covered by duckweed.

[0086] In one or more embodiments, the proportion of the duckweed growth area to the water body area is calculated based on the following formula:

[0087] φ = S1 / S2 × 100%;

[0088] In the formula, φ represents the proportion of the duckweed's growth area to the water body area; S1 represents the duckweed area; and S2 represents the water body area.

[0089] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to the method section.

[0090] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for monitoring duckweed-type eutrophic water bodies based on Sentinel-2 satellite imagery, characterized in that, Includes the following steps: Acquire Sentinel-2 L1C satellite images of the monitoring area during the non-duckweed growing season and during the duckweed growing season; Atmospheric correction processing was performed on the Sentinel-2 L1 C satellite images during the non-duckweed growing season and the Sentinel-2 L1 C satellite images during the duckweed growing season to obtain multi-band surface reflectance images during the non-duckweed growing season and multi-band surface reflectance images during the duckweed growing season. All bands in the multi-band surface reflectance image of the non-duckweed growing season and the multi-band surface reflectance image of the duckweed growing season are resampled to the same resolution to obtain the multi-band surface reflectance image of the non-duckweed growing season and the multi-band surface reflectance image of the duckweed growing season. The blue band, green band, red band, near-infrared band, and narrow near-infrared band of the multi-band surface reflectance image after resampling during the non-duckweed growing season are subjected to mean filtering and then band synthesis to obtain a band synthesis image of the non-duckweed growing season. The blue band, green band, red band, near-infrared band, and narrow near-infrared band of the multi-band surface reflectance image after resampling during the duckweed growing season are subjected to mean filtering and then band synthesis to obtain a composite image of the duckweed growing season. The proportion of the water body area covered by duckweed growth range is calculated using the composite image of the non-duckweed growth season and the composite image of the duckweed growth season. The calculation of the proportion of the water body area covered by duckweed growth using the composite image of the non-duckweed growth season band and the composite image of the duckweed growth season band specifically includes the following steps: Calculate the water index of each pixel in the composite image of the non-duckweed growth season; The water index of each pixel is compared with a preset water index threshold to obtain a first binary image; wherein, the first binary image is a binary image that distinguishes between water bodies and non-water bodies; Convert the first binary image into water body range vector data; The cropped image is obtained by cropping the duckweed growth seasonal band composite image based on the water body range vector data; wherein, the cropped image is a duckweed growth seasonal band composite image that only includes the water body area; Calculate the duckweed recognition index of each pixel in the cropped image; The duckweed recognition index of each pixel is compared with a preset duckweed recognition index threshold to obtain a second binary image; wherein, the second binary image is a binary image that distinguishes between duckweed and non-duckweed. Calculate the water area and duckweed area in the second binary image; The proportion of the duckweed's growth area to the water body area is calculated using the duckweed's area and the water body area.

2. The method for monitoring duckweed-type eutrophic water bodies based on Sentinel-2 satellite imagery as described in claim 1, characterized in that, The water index of each pixel in the composite image of the non-duckweed growth season is calculated based on the following formula: NDWI i =(R i (Green)-R i (Nir)) / (R i (Green)+R i (Nir)); In the formula, NDWI i R represents the water index of the i-th pixel in the composite image of the non-duckweed growth season; i = 1, 2, ..., I; I represents the number of pixels included in the composite image of the non-duckweed growth season; i (Green) represents the green band reflectance of the i-th pixel in the composite image of the non-duckweed growth season; R i (Nir) represents the near-infrared reflectance of the i-th pixel in the composite image of the non-duckweed growth season.

3. The method for monitoring duckweed-type eutrophic water bodies based on Sentinel-2 satellite imagery as described in claim 1, characterized in that, The water index of each pixel is compared with a preset water index threshold to obtain a first binary image, specifically including the following steps: Determine whether the water index of each pixel in the composite image of the non-duckweed growth season is greater than the preset water index threshold: if it is greater, set the pixel value of the corresponding pixel to 1, otherwise set it to 0.

4. The method for monitoring duckweed-type eutrophic water bodies based on Sentinel-2 satellite imagery as described in claim 1, characterized in that, The duckweed recognition index of each pixel in the cropped image is calculated based on the following formula: ； In the formula, DKI (j) R represents the duckweed recognition index of the j-th pixel in the cropped image; j = 1, 2, ..., J; J represents the number of pixels included in the cropped image; (j) (Nir) represents the near-infrared reflectance of the j-th pixel in the cropped image; R (j) (Narrow Nir) represents the narrow near-infrared reflectance of the j-th pixel in the cropped image; R (j) (Red) represents the red band reflectance of the j-th pixel in the cropped image; R (j) (Blue) represents the blue band reflectance of the j-th pixel in the cropped image.

5. The method for monitoring duckweed-type eutrophic water bodies based on Sentinel-2 satellite imagery as described in claim 1, characterized in that, The duckweed identification index of each pixel is compared with a preset duckweed identification index threshold to obtain a second binary image, specifically including the following steps: Determine whether the duckweed recognition index of each pixel in the cropped image is greater than the preset duckweed recognition index threshold: if it is greater, set the pixel value of the corresponding pixel to 1, otherwise set it to 0.

6. The method for monitoring duckweed-type eutrophic water bodies based on Sentinel-2 satellite imagery as described in claim 1, characterized in that, The proportion of the duckweed's growth area to the water body area is calculated based on the following formula: φ = S1 / S2 × 100%; In the formula, φ represents the proportion of the duckweed's growth area to the water body area; S1 represents the duckweed area; and S2 represents the water body area.

7. The method for monitoring duckweed-type eutrophic water bodies based on Sentinel-2 satellite imagery as described in claim 1, characterized in that, Atmospheric correction was performed on the Sentinel-2 L1 C satellite images during the non-duckweed growing season and the Sentinel-2 L1 C satellite images during the duckweed growing season using the SEN2COR tool.

8. The method for monitoring duckweed-type eutrophic water bodies based on Sentinel-2 satellite imagery as described in claim 1, characterized in that, The same resolution refers to a 10-meter resolution.

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