Coal mining subsidence ponding area water environment monitoring method based on water body color

Abstract

The invention discloses a water environment monitoring method for a coal mining subsidence ponding area based on a water body color. The water environment monitoring method comprises the following operation steps: step 1, sampling and shooting the coal mining subsidence ponding area; 2, identifying the sampling and shooting samples of the ponding area in the step 1, extracting water body information by utilizing a relational expression of a vegetation index and a water body index based on the difference of the vegetation index and the water body index in the water body, and removing a water area with the surface covered with a large amount of vegetation, the method specifically comprises the following steps: regarding pixels of water body signals stronger than vegetation signals as actual water body pixels, and eliminating abnormal values by adopting EVI. Compared with the prior art, the method has the advantages of accurate dynamic range extraction and water color-water quality correlation analysis.

Description

Technical Field

[0001] The present invention relates to the field of water environment monitoring methods, and specifically to a water environment monitoring method for coal mining subsidence water areas based on water body color. Background Art

[0002] The water environment monitoring of coal mining subsidence water areas is a key link in mine ecological restoration and environmental protection. With the expansion of coal resource development scale, large areas of subsidence waters are formed in high water table mining areas (such as the subsidence area in the Huaihai area reaches 580 km 2 , and the water accumulation accounts for 60%-70%), and the dynamic changes in its water environment have a significant impact on the ecosystem and human settlement environment.

[0003] Insufficient monitoring of the dynamic range: The boundaries of subsidence water areas change dynamically with the groundwater level, rainfall, and mining activities. Conventional remote sensing or manual surveys are difficult to accurately capture the spatio-temporal evolution law.

[0004] Simplification of water quality parameters: Existing technologies mostly rely on chemical indicators (such as COD, ammonia nitrogen) or single remote sensing parameters (such as NDWI), lacking the correlation analysis of the comprehensive ecological indicator of water color.

[0005] Lack of real-time and automation: Traditional methods rely on manual sampling or fixed sensors, unable to achieve high-frequency, large-scale continuous monitoring, and are easily restricted by weather and equipment maintenance.

[0006] As an intuitive representation of water environment quality, water body color is closely related to pollutant concentration, algal abundance, etc. For example, the Forel-Ule index (FUI) can indirectly reflect the water quality state through water color grading, but existing applications are mostly limited to static waters and not combined with the technology for extracting the dynamic range of subsidence areas.

[0007] However, the patents in the existing technologies have the following several disadvantages:

[0008] Subsidence area monitoring technology based on remote sensing: The spatio-temporal resolution is limited, making it difficult to capture the high-frequency dynamic changes in the subsidence area (such as the sudden rise in water level during the rainy season);

[0009] The spectral information is easily interfered by the atmosphere, and there is a lack of optimized algorithms for water color indices.

[0010] Ground water quality monitoring technology: The coverage range is small, unable to adapt to the large-scale and heterogeneous waters in the subsidence area, with high maintenance costs, and is easily affected by the complex terrain in the subsidence area (such as floating objects blocking, equipment damage).

[0011] Traditional water color index analysis technology: Relying on manual interpretation, it is inefficient and subjective; not combined with the technology for extracting the dynamic water area range, resulting in data spatial matching errors. Summary of the Invention

[0012] The technical problem to be solved by the present invention is to overcome the above technical defects.

[0013] To solve the above problems, the technical solution of the present invention is: A water environment monitoring method for coal mining subsidence water accumulation areas based on water body color, the water environment monitoring method includes the following operating steps:

[0014] Step 1: Sampling and photographing the coal mining subsidence water accumulation area;

[0015] Step 2: Identify the sampling and photographing samples of the water accumulation area in Step 1, and based on the differences between the vegetation index and the water body index in the water body, use the relational formula of the vegetation index and the water body index to extract water body information, and exclude the waters covered with a large amount of vegetation on the surface. Specifically, the pixels with stronger water body signals than vegetation signals are considered actual water body pixels, and the EVI is used to exclude outliers;

[0016]

[0017] In the above formula, Red, Green, Blue, NIR, and SWIR respectively represent the reflectance of the ground object in the red band, green band, blue band, near-infrared, and short-wave infrared bands;

[0018] Step 3: Based on the results of the above formula and by calculating the frequency of the water body appearing in all images within one year, to quantify the annual water body change of the pixels, that is, the Annual Water Frequency Index (AWFI). Among them, the range of AWFI is 0 to 1. According to the continuous water accumulation time of the water body within the year, the annual water body is divided into seasonal water accumulation and perennial water accumulation;

[0019] Step 4: Based on the above Steps 1 to 3, perform color verification on the sampling and photographing samples, and adopt a color overlay model. The color overlay model is the CIE-XYZ color system, and the conversion relationship between XYZ and RGB is:

[0020] X = 2.7689Red + 1.7517Green + 1.1302Blue

[0021] Y = 1.0000Red + 4.5907Green + 0.0601Blue

[0022] Z = 0.0000Red + 0.0565Green + 5.5943Blue;

[0023] According to X, Y, and Z, calculate the two-dimensional coordinates x and y on the two-dimensional chromaticity diagram;

[0024] x = X / (X + Y + Z)

[0025] y = Y(X + Y + Z);

[0026] Each color corresponds to a chromaticity coordinate (x, y) on a two-dimensional chromaticity diagram. Subsequently, the chromaticity coordinates (x, y) are substituted into Equation (7) to calculate the chromaticity angle:

[0027] α = arctan 2(x - 0.3333, y - 0.3333) * 180 / π + 180;

[0028] Due to the small number of bands and the discreteness of multispectral satellite sensors, there is a deviation from the true colors perceived by the human eye (equivalent to a hyperspectral sensor). Correction is required to eliminate the deviation. Therefore, a polynomial correction formula needs to be adopted for correction.

[0029] Δ = 33.086a 5 -221.6a 4 +512.65a 3 -468.4a 2 +137.27a + 4.6374, R 2 = 0.5.

[0030] Furthermore, pixels where the water body signal is stronger than the vegetation signal are considered actual water body pixels, and the conditions are: Modified Normalized Difference Water Index (MNDWI) is greater than Normalized Difference Vegetation Index (NDVI), and MNDWI is greater than Enhanced Vegetation Index (EVI).

[0031] Furthermore, the perennial water accumulation area described in step 3 indicates that water bodies exist in most of the time of a year for pixels, including the central areas of lakes and rivers. The remaining water bodies are defined as seasonal water bodies. The AWF I is divided into three categories according to the threshold. 0 ≤ AWF I < 0.3 means no water accumulation, 0.3 ≤ AWF I < 0.75 means seasonal water accumulation, and AWF I ≥ 0.75 means perennial water accumulation area. The area range of the seasonal water accumulation area will fluctuate due to multiple factors such as seasonal climate and rainfall.

[0032] Furthermore, in the CIE-XYZ system described in step 4, X, Y, and Z are used to replace R, G, and B, making all the spectral tristimulus values X, Y, and Z in the chromaticity system positive.

[0033] The advantages of the present invention compared with the existing technologies are as follows:

[0034] The present invention achieves the following breakthroughs in view of the deficiencies of the existing technologies:

[0035] AWFI Index: By integrating multi-temporal remote sensing data through the Annual Water Frequency Index (AWFI), identify stable and seasonally changing areas of subsidence waterlogging areas, and solve the problem of boundary misjudgment caused by single-temporal data in traditional NDWI / MNDWI;

[0036] FUI Index Optimization: Combine the optical characteristics of water bodies in subsidence areas (such as suspended solids and dominant algae species) to construct an FUI inversion model suitable for the mining area environment, and improve the correlation accuracy between water color and pollutants (such as total phosphorus and chlorophyll a). Brief Description of the Drawings

[0037] Figure 1 It shows the waterlogging distribution in Huainan Mining Area from 2016 to 2024 of a water environment monitoring method for coal mining subsidence waterlogging areas based on water body color according to the present invention.

[0038] Figure 2 It shows the water color distribution of waterlogging in Huainan Mining Area from 2016 to 2024 of a water environment monitoring method for coal mining subsidence waterlogging areas based on water body color according to the present invention. Detailed Embodiment

[0039] The following further describes the detailed embodiment of the present invention with reference to the drawings. Among them, the same components are represented by the same reference numerals.

[0040] In order to make the content of the present invention more clearly understood, 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.

[0041] As Figures 1 to 2 shown, a water environment monitoring method for coal mining subsidence waterlogging areas based on water body color, the water environment monitoring method includes the following operating steps:

[0042] Step 1: Sampling and photographing the coal mining subsidence waterlogging area;

[0043] Step 2: Identify the sampling and photographing samples of the waterlogging area in Step 1, and based on the differences between vegetation indices and water body indices in water bodies, use the relational formula of vegetation indices and water body indices to extract water body information, and exclude waters with a large amount of vegetation on the surface. Specifically, pixels with stronger water body signals than vegetation signals are considered actual water body pixels, and EVI is used to exclude outliers;

[0044]

[0045] In the above formula, Red, Green, Blue, NIR, and SWIR respectively represent the reflectance of the ground object in the red band, green band, blue band, near-infrared, and short-wave infrared bands;

[0046] Step 3: Based on the above formula results, calculate the frequency of water bodies appearing in all images within one year to quantify the annual water body change of pixels, which is the Annual Water Frequency Index (AWFI). Among them, the range of AWFI is from 0 to 1. According to the continuous water accumulation time of water bodies within the year, the annual water bodies are divided into seasonal water accumulation and perennial water accumulation;

[0047] Step 4: Based on the above Steps 1 to 3, conduct color verification on the sampled and photographed samples, and adopt a color overlay model. The color overlay model is the CIE-XYZ color system, and the conversion relationship between XYZ and RGB is:

[0048] X = 2.7689Red + 1.7517Green + 1.1302Blue

[0049] Y = 1.0000Red + 4.5907Green + 0.0601Blue

[0050] Z = 0.0000Red + 0.0565Green + 5.5943Blue;

[0051] Based on X, Y, and Z, calculate the two-dimensional coordinates x and y on the two-dimensional chromaticity diagram;

[0052] x = X / (X + Y + Z)

[0053] y = Y / (X + Y + Z);

[0054] Each color corresponds to a chromaticity coordinate (x, y) on the two-dimensional chromaticity diagram. Subsequently, substitute the chromaticity coordinate (x, y) into Equation 7 to calculate the chromaticity angle:

[0055] α = arctan2(x - 0.3333, y - 0.3333) * 180 / π + 180;

[0056] Due to the small number and discreteness of the bands of the multispectral satellite sensor, there is a deviation from the true color perceived by the human eye (equivalent to a hyperspectral sensor). Correction is required to eliminate the deviation. Therefore, a polynomial correction formula needs to be adopted for correction.

[0057] Δ = 33.086a 5 - 221.6a 4 + 512.65a 3 - 468.4a 2 + 137.27a + 4.6374, R 2 = 0.5.

[0058] Pixels where the water body signal is stronger than the vegetation signal are considered actual water body pixels, with the condition that the Modified Normalized Difference Water Index (MNDWI) is greater than the Normalized Difference Vegetation Index (NDVI), and MNDWI is greater than the Enhanced Vegetation Index (EVI).

[0059] The perennial waterlogging area described in step three indicates that water bodies exist in most of the time of the year for pixels, including the central areas of lakes and rivers. The rest of the water bodies are defined as seasonal water bodies. The AWF I is divided into three categories according to the threshold: 0 ≤ AWF I < 0.3 represents non-waterlogged, 0.3 ≤ AWF I < 0.75 represents seasonal waterlogging, and AWF I ≥ 0.75 represents the perennial waterlogging area. The seasonal waterlogging area is affected by multiple factors such as seasonal climate and rainfall, and the area range of the waterlogging area will fluctuate.

[0060] In the CIE-XYZ system described in step four, X, Y, and Z are used instead of R, G, and B, making all the spectral tristimulus values X, Y, and Z in the chromaticity system positive.

[0061] The above describes the present invention and its implementation manners. This description is not restrictive. What is shown in the drawings is only one of the implementation manners of the present invention, and the actual structure is not limited thereto. Generally speaking, if those of ordinary skill in the art are inspired by it and, without departing from the purpose of the present invention, design similar structural manners and embodiments to this technical solution without creative efforts, they shall fall within the protection scope of the present invention.

Claims

1. A water environment monitoring method for coal mining subsidence water accumulation areas based on water body color, characterized in that: The described water environment monitoring method includes the following operating steps: Step 1: Sampling and photographing the coal mining subsidence water area; Step 2: Identifying the sampling and photographing samples of the water area in Step 1, and based on the differences between the vegetation index and the water index in the water body, using the relationship formula of the vegetation index and the water index to extract water body information, and excluding the water areas covered with a large amount of vegetation on the surface. Specifically, the pixels with stronger water body signals than vegetation signals are considered actual water body pixels, and the EVI is used to exclude outliers; In the above formula, Red, Green, Blue, NIR, and SWIR respectively represent the reflectance of the ground object in the red band, green band, blue band, near-infrared, and short-wave infrared bands; Step 3: Based on the results of the above formula and by calculating the frequency of the water body appearing in all images within one year, to quantify the annual water body change of the pixels, that is, the Annual Water Frequency Index (AWFI). Among them, the range of AWFI is 0 to 1. According to the continuous water accumulation time of the water body within the year, the annual water body is divided into seasonal water accumulation and perennial water accumulation; Step 4: Based on the above Steps 1 to 3, perform color verification on the sampling and photographing samples, and adopt a color overlay model. The color overlay model is the CIE-XYZ color system, and the conversion relationship between XYZ and RGB is: X = 2.7689Red + 1.7517Green + 1.1302Blue Y = 1.0000Red + 4.5907Green + 0.0601Blue Z = 0.0000Red + 0.0565Green + 5.5943Blue; According to X, Y, and Z, calculate the two-dimensional coordinates x and y on the two-dimensional chromaticity diagram; x = X / (X + Y + Z) y = Y / (X + Y + Z); Each color corresponds to a chromaticity coordinate (x, y) on the two-dimensional chromaticity diagram. Subsequently, substitute the chromaticity coordinate (x, y) into Equation 7 to calculate the chromaticity angle: α = arctan2(x - 0.3333, y - 0.3333) * 180 / π + 180; Due to the small number of bands and discreteness of the multi-spectral satellite sensor, there is a deviation from the real color perceived by the human eye (equivalent to a hyperspectral sensor). Correction is required to eliminate the deviation. Therefore, a polynomial correction formula needs to be adopted for correction. Δ = 33.086a 5 -221.6a 4 +512.65a 3 -468.4a 2 +137.27a + 4.6374,R 2 = 0.5 2. The water environment monitoring method for coal mining subsidence water accumulation area based on water body color according to claim 1, wherein: The pixels with stronger water body signals than vegetation signals are considered actual water body pixels, and the conditions are: Modified Normalized Difference Water Index (MNDWI) is greater than Normalized Difference Vegetation Index (NDVI), and MNDWI is greater than Enhanced Vegetation Index (EVI).

3. The water environment monitoring method for coal mining subsidence water accumulation area based on water body color according to claim 1, characterized in that: The perennial waterlogging area described in Step 3 indicates that water bodies exist in most of the time in a year for pixels, including the central areas of lakes and rivers, and the remaining water bodies are defined as seasonal water bodies. The AWFI is divided into three categories according to the threshold. When 0 ≤ AWFI < 0.3, it is non-waterlogged; when 0.3 ≤ AWFI < 0.75, it is seasonal waterlogging; when AWFI ≥ 0.75, it is perennial waterlogging area. The seasonal waterlogging area is affected by multiple factors such as seasonal climate and rainfall, and the area range of the waterlogging area will fluctuate.

4. A water environment monitoring method for coal mining subsidence water accumulation areas based on water body color according to claim 1, characterized in that: In the CIE-XYZ system described in Step 4, X, Y, and Z are used to replace R, G, and B, making all the spectral tristimulus values X, Y, and Z in the chromaticity system positive.

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