Water body area extraction method based on satellite remote sensing image

Abstract

The invention discloses a satellite remote sensing image-based water body area extraction method, which comprises the following steps of: on the basis of processing satellite remote sensing image data to obtain satellite surface reflectance data, a normalized difference water body index and an improved normalized difference water body index, extracting a water body object by adopting a multi-threshold segmentation method; and the water body area is calculated. The method is less affected by the space-time environment, can obtain a more accurate water body area extraction result, is convenient and reliable, has strong applicability, and can be suitable for large-scale surface water body high-precision mapping.

Description

Technical Field

[0001] The invention belongs to the technical field of remote sensing image recognition, and particularly relates to the design of a water body area extraction method based on satellite remote sensing images. Background Art

[0002] Water bodies, typically including rivers, lakes, and reservoirs, are a vital component of the global water cycle and play an irreplaceable role in global ecological and climate systems. Water area is a key indicator for evaluating surface water resources. Accurately capturing the dynamic changes in water area is crucial for surface water resource surveys and assessments, water conservancy planning, flood and drought monitoring, and disaster assessments, providing decision-making support for the rational use and protection of water resources.

[0003] Water body area is difficult to measure using traditional manual measurement methods. Remote sensing, as a regional monitoring method, can quickly capture the spatiotemporal distribution of water area and has become a primary means of water area monitoring. Existing water area extraction methods mostly rely on manually set water extraction thresholds. However, using a single threshold for water area extraction is often affected by various factors such as season, spatial distance, and water flow patterns, resulting in low water area extraction accuracy. Summary of the Invention

[0004] The purpose of the present invention is to solve the problem of low extraction accuracy of the existing water body area extraction method using a single threshold, and proposes a water body area extraction method based on satellite remote sensing images.

[0005] The technical solution of the present invention is: a method for extracting water area based on satellite remote sensing images, comprising the following steps:

[0006] S1. Obtain satellite remote sensing image data of water areas.

[0007] S2. Perform geometric correction and radiometric calibration on each scene of satellite remote sensing image data to obtain satellite radiometric brightness data.

[0008] S3. Perform FLAASH atmospheric correction on the satellite radiation brightness data to obtain satellite surface reflectance data.

[0009] S4. Calculate the normalized difference water index and improved normalized difference water index based on satellite surface reflectance data.

[0010] S5. Based on satellite surface reflectance data, normalized difference water index and improved normalized difference water index, a multi-threshold segmentation method is used to extract water objects.

[0011] S6. Count the number of water body pixels based on the extracted water body objects.

[0012] S7. Calculate the water body area based on the number of water body pixels.

[0013] Furthermore, the satellite remote sensing image data acquired in step S1 includes Landsat7-ETM+, HJ1A / B-CCD and GF1-WFV.

[0014] Furthermore, the calculation formula of satellite radiation brightness data in step S2 is:

[0015] L=gain·DN+bais

[0016] Where L represents the satellite radiation brightness data, gain represents the radiation gain coefficient of the satellite remote sensing image, DN represents the DN data of the satellite remote sensing image, and bais represents the deviation coefficient of the satellite remote sensing image.

[0017] Furthermore, the satellite surface reflectance data obtained in step S3 includes the surface reflectance ρ of the satellite remote sensing image in the green light band. green , surface reflectivity ρ of satellite remote sensing images in the near-infrared band NIR And the surface reflectivity ρ of satellite remote sensing images in the mid-infrared band MIR .

[0018] Furthermore, the calculation formula of the normalized difference water index in step S4 is:

[0019] NDWI=(ρ green -ρ NIR ) / (ρ green +ρ NIR )

[0020] NDWI stands for Normalized Difference Water Index.

[0021] Furthermore, the calculation formula of the improved normalized difference water index in step S4 is:

[0022] MNDWI=(ρ green -ρ MIR ) / (ρ green +ρ MIR )

[0023] Where MNDWI stands for modified normalized difference water index.

[0024] Furthermore, the formula for extracting the water body object using the multi-threshold segmentation method in step S5 is:

[0025]

[0026] Where c1 represents the surface reflectance threshold, and c2 represents the normalized difference water index threshold.

[0027] Furthermore, the calculation formula for the water body area in step S7 is:

[0028] A water =N water SR 2

[0029] Among them A water Represents the water area, N water It represents the number of water body pixels, and SR represents the spatial resolution of satellite remote sensing images.

[0030] The beneficial effects of the present invention are:

[0031] (1) The present invention adopts a multi-threshold segmentation method to extract water body objects, which is less affected by the temporal and spatial environment and can obtain more accurate water body area extraction results.

[0032] (2) The present invention extracts water area based on satellite surface reflectance data obtained from satellite remote sensing images, and the method is convenient and reliable.

[0033] (3) The present invention has strong applicability and can be applied to high-precision mapping of large-scale surface water bodies. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 Shown is a flow chart of a water area extraction method based on satellite remote sensing images. DETAILED DESCRIPTION

[0035] The exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be understood that the embodiments shown and described in the accompanying drawings are merely exemplary and are intended to illustrate the principles and spirit of the present invention, rather than to limit the scope of the present invention.

[0036] The embodiment of the present invention provides a method for extracting water area based on satellite remote sensing images. Figure 1 As shown, the following steps S1 to S7 are included:

[0037] S1. Obtain satellite remote sensing image data of water areas.

[0038] In the embodiments of the present invention, satellite remote sensing image data includes Landsat7-ETM+, HJ1A / B-CCD, and GF1-WFV. Landsat7-ETM+ satellite images are downloaded from the United States Geological Survey (USGS; https: / / www.usgs.gov / ), while HJ1A / B-CCD and GF1-WFV satellite images are downloaded from the National Resource Satellite Application Center (https: / / data.cresda.cn / # / home).

[0039] S2. Perform geometric correction and radiometric calibration on each scene of satellite remote sensing image data to obtain satellite radiometric brightness data. In the embodiment of the present invention, the calculation formula for satellite radiometric brightness data is:

[0040] L=gain·DN+bais

[0041] Where L represents the satellite radiation brightness data, gain represents the radiation gain coefficient of the satellite remote sensing image, DN represents the DN data of the satellite remote sensing image, and bais represents the deviation coefficient of the satellite remote sensing image.

[0042] S3. Perform FLAASH atmospheric correction on the satellite radiation brightness data to obtain satellite surface reflectance data.

[0043] In the embodiment of the present invention, the satellite surface reflectance data includes the surface reflectance ρ of the satellite remote sensing image in the green light band green , surface reflectivity ρ of satellite remote sensing images in the near-infrared band NIR And the surface reflectivity ρ of satellite remote sensing images in the mid-infrared band MIR .

[0044] S4. Calculate the Normalized Difference Water Index (NDWI) and the Modified NDWI (MNDWI) based on satellite surface reflectance data.

[0045] In the embodiment of the present invention, the calculation formula of the normalized difference water index is:

[0046] NDWI=(ρ green -ρ NIR ) / (ρ green +ρ NIR )

[0047] NDWI stands for Normalized Difference Water Index.

[0048] The calculation formula of the improved normalized difference water index is:

[0049] MNDWI=(ρ green -ρ MIR ) / (ρ green +ρ MIR )

[0050] Where MNDWI stands for modified normalized difference water index.

[0051] S5. Based on satellite surface reflectance data, normalized difference water index and improved normalized difference water index, a multi-threshold segmentation method is used to extract water objects.

[0052] In the embodiment of the present invention, by analyzing the spectral characteristics of water and non-water bodies, it is found that there are certain differences between water and non-water body pixels in the near-infrared band. Therefore, the ρ in the satellite surface reflectance data is comprehensively used. NIR , Normalized Difference Water Index NDWI and Improved Normalized Difference Water Index MNDWI, and the multi-threshold segmentation method is used to extract water objects:

[0053]

[0054] Where c1 represents the surface reflectance threshold, and c2 represents the normalized difference water index threshold.

[0055] S6. Count the number of water body pixels based on the extracted water body objects.

[0056] S7. Calculate the water area based on the number of water pixels. The calculation formula is:

[0057] A water =N water SR 2

[0058] Among them A water Represents the water area, N water = represents the number of water pixels, and SR represents the spatial resolution of satellite remote sensing images. For Landsat7-ETM+ and HJ1A / B-CCD sensors, SR = 30m, and for GF1-WFV sensors, SR = 16m.

[0059] Those skilled in the art will appreciate that the embodiments described herein are intended to help readers understand the principles of the present invention, and it should be understood that the scope of protection of the present invention is not limited to such specific descriptions and embodiments. Those skilled in the art can make various other specific variations and combinations based on the technical teachings disclosed in the present invention without departing from the essence of the present invention, and such variations and combinations are still within the scope of protection of the present invention.

Claims

1. A method for extracting water area based on satellite remote sensing images, characterized in that: The following steps are involved: S1. Obtain satellite remote sensing image data of water areas; S2. Perform geometric correction and radiometric calibration on each scene of satellite remote sensing image data to obtain satellite radiometric brightness data; S3, perform FLAASH atmospheric correction on the satellite radiance data to obtain satellite surface reflectance data; S4. Calculating a normalized difference water index and an improved normalized difference water index based on satellite surface reflectance data; S5. Extracting water objects using a multi-threshold segmentation method based on satellite surface reflectance data, normalized difference water index, and improved normalized difference water index; S6. Counting the number of water body pixels according to the extracted water body objects; S7. Calculate the water body area based on the number of water body pixels.

2. The method for extracting water area based on satellite remote sensing images according to claim 1, characterized in that: The satellite remote sensing image data obtained in step S1 includes Landsat7-ETM+, HJ1A / B-CCD and GF1-WFV.

3. The method for extracting water area based on satellite remote sensing images according to claim 1, characterized in that: The calculation formula of satellite radiation brightness data in step S2 is: L=gain·DN+bais Where L represents the satellite radiation brightness data, gain represents the radiation gain coefficient of the satellite remote sensing image, DN represents the DN data of the satellite remote sensing image, and bais represents the deviation coefficient of the satellite remote sensing image.

4. The method for extracting water area based on satellite remote sensing images according to claim 1, characterized in that: The satellite surface reflectance data obtained in step S3 includes the surface reflectance ρ of the satellite remote sensing image in the green light band. green , surface reflectivity ρ of satellite remote sensing images in the near-infrared band NIR And the surface reflectivity ρ of satellite remote sensing images in the mid-infrared band MIR .

5. The method for extracting water area based on satellite remote sensing images according to claim 4, characterized in that: The calculation formula of the normalized difference water index in step S4 is: NDWI=(ρ green -r NIR ) / (ρ green +r NIR ) NDWI stands for Normalized Difference Water Index.

6. The method for extracting water area based on satellite remote sensing images according to claim 5, characterized in that: The calculation formula of the improved normalized difference water index in step S4 is: MNDWI=(ρ green -r MIR ) / (ρ green +r MIR ) Where MNDWI stands for modified normalized difference water index.

7. The method for extracting water area based on satellite remote sensing images according to claim 6, characterized in that: The formula for extracting the water body object using the multi-threshold segmentation method in step S5 is: Where c1 represents the surface reflectance threshold, and c2 represents the normalized difference water index threshold.

8. The method for extracting water area based on satellite remote sensing images according to claim 1, characterized in that: The calculation formula for the water body area in step S7 is: A water =N water ·SR 2 Among them A water Represents the water area, N water It represents the number of water body pixels, and SR represents the spatial resolution of satellite remote sensing images.

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