Soil water content downscaling method based on terrain and vegetation indexes

Abstract

The invention discloses a soil water content downscaling method based on terrain and vegetation indexes, which comprises the following main steps of: firstly, extracting terrain data of 10km and fine spatial resolution of a watershed, and obtaining a boundary file of the watershed; acquiring topographic data of coarse resolution for downscaling and normalized differential infrared index raster data; selecting an SMOS soil water content satellite product as the soil water content data, and extracting the soil water content data of the watershed according to the watershed mask; determining the soil water content weight of each fine resolution grid based on the terrain humidity index TWI and the terrain humidity index NDII; and multiplying the weight coefficient of each grid by the soil water content of the coarse resolution to obtain the soil water content of the fine spatial resolution. According to the method, the soil water content is downscaled by considering the spatial heterogeneity of the underlying surface, and the influence of topographic factors and vegetation distribution on the spatial distribution of the soil water content is fully considered, so that the downscaling of the coarse-resolution soil water content is realized.

Description

Technical Field

[0001] This invention belongs to the fields of hydrology, ecology, remote sensing and geographic information technology, and specifically relates to a method for downscaling soil moisture content based on topography and vegetation indices. Background Technology

[0002] The development of satellite and remote sensing technologies has provided excellent technical support for continuous spatial observation of soil moisture content. However, due to limitations in existing observation techniques, the spatial resolution of soil moisture content observed by satellite is relatively coarse. The spatial distribution of soil moisture content is limited by factors such as meteorology, vegetation, topography, and soil composition. Therefore, downscaling of soil moisture content data is crucial for obtaining fine-scale data. Summary of the Invention

[0003] To address the aforementioned technical problems, this invention provides a soil moisture downscaling method based on topography and vegetation indices. By considering the spatial heterogeneity of the underlying surface, the method downscales soil moisture content, fully taking into account the influence of topographic factors and vegetation distribution on the spatial distribution of soil moisture, thereby achieving downscaling of coarse-resolution soil moisture content. This invention utilizes fine-scale topographic data and the NDII vegetation index, which is sensitive to soil moisture content, for spatial downscaling of soil moisture content, providing technical support for obtaining high-precision, high-spatiotemporal-resolution soil moisture content data. Currently, there is no relevant research on using the NDII vegetation index for soil moisture downscaling.

[0004] The objective of this invention is achieved through the following technical solution: A method for downscaling soil moisture content based on topography and vegetation indices includes the following steps: S1: Extract the watershed mask file based on DEM data at 10km and 1km resolution; Specifically, the following steps are included: S1-1: Based on DEM data at 10km and 1km resolutions, the basin boundary is extracted and the basin mask file is obtained by filling depressions, calculating flow direction, calculating cumulative runoff, determining the watershed outlet station, and obtaining the watershed mask file. S1-2: Calculate slope, aspect, TWI, and curvature data based on 10km and 1km resolution DEM data; S2: Extract normalized differential infrared index data for 10km and 1km of the watershed from the watershed mask file; Specifically, the following steps are included: S2-1: Calculating NDII value based on MODIS data MOD09A1 data product (1) In the formula, It is the reflectivity at a wavelength of 0.85µm; This is the reflectance at a wavelength of 1.65µm. The NDII normalized index ranges from [-1, 1]. S2-2: Based on NDII data with a spatial resolution of 500m, NDII data with spatial resolutions of 10km and 1km are obtained by averaging. S2-3: Extract the NDII values ​​at spatial resolutions of 10km and 1km based on the watershed mask file; S3: Extract satellite data on soil moisture content of the watershed based on the watershed mask file; S4: Based on normalized index TWI and normalized differential infrared index NDII data, construct a downscaling weight for soil moisture content from coarse resolution to fine resolution. Specifically, the following steps are included: The soil moisture content downscaling factor is based on a 10km topographic map of the watershed, from coarse to fine resolution. Satisfy the following calculation formula (2) In the formula, Soil moisture content data with a spatial resolution of 10 km before downscaling, in m³. 3 / m 3 ; To and The function is calculated based on the curvature of the slope, and the calculation formulas are as follows: (3) In the formula, The slope aspect on a 10km scale; Let be a function of slope and aspect on a 10km scale, and its expression is: (4) In the formula, Slope; The average slope of the area; The coefficient is related to slope aspect, for slopes in the four directions of north, south, west, and east. The values ​​are -0.01, 0.005, -0.003, and 0.002, respectively. It is a function of slope and aspect on a 10km scale; Once determined, linear regression is used to analyze... and Fit the data and construct and The relationship between the two + (5) Sure and Then, it was applied to the calculation of soil moisture content at a 1km scale. (6); In equation (6), The slope aspect on a 1km scale. Let be a function of slope and aspect on a 1km scale; p and q are fitting coefficients. The topographic humidity index is measured on a 1km scale.

[0005] The above-mentioned method for downscaling soil moisture content based on topography and vegetation indices, specifically step S4, which determines the parameter transformation relationship between soil moisture and vegetation indices based on the Normalized Differential Infrared Index (NDII), includes the following steps: Since the normalized differential infrared index (NDII) ranges from [-1, 1], the min-max method is first used to standardize the NDII data at the 1 km and 10 km scales. The calculation formula is as follows: (7) (8) In the formula, and These are the normalized differential red index values ​​at scales of 1km and 10km, respectively; and The standardized NDII indices are for 1km and 10km scales, respectively. Based on the standardized Normalized Difference Indices (NDII) values, the downscaling transformation parameters of soil moisture content at a 1 km scale based on vegetation were calculated. (9) In the formula These are the downscaling transformation parameters of soil moisture content at the 1km scale obtained based on the Normalized Differential Infrared Index (NDII).

[0006] The above-mentioned soil moisture downscaling method based on topography and vegetation indices, specifically step S4, which involves downscaling soil moisture based on TWI and NDII parameters, includes the following steps: Based on the downscaling transformation parameters of soil moisture content obtained using the normalized index TWI and the normalized differential infrared index NDII, the soil moisture content downscaling transformation parameters were determined. (10) In the formula, The downscaling transformation parameter for soil moisture content at a 1km scale. Soil moisture content at a 1km scale Here are the downscaling transformation parameters for soil moisture content at a 1km scale; based on 10km soil moisture content data and the soil moisture content downscaling transformation parameters, the formula for calculating the downscaling of soil moisture content at a 1km scale is: (11) In the formula, Soil moisture content data with a spatial resolution of 1 km after downscaling; The data represents soil moisture content with a spatial resolution of 10 km after downscaling.

[0007] Compared with the prior art, the present invention has the following technical effects: This invention downscales soil moisture content by considering the spatial heterogeneity of the underlying surface, fully taking into account the influence of topographic factors and vegetation distribution on the spatial distribution of soil moisture content, thereby achieving downscaling of coarse-resolution soil moisture content. This invention utilizes fine-scale topographic data and the NDII vegetation index, which is sensitive to soil moisture content, for spatial downscaling of soil moisture content, providing technical support for obtaining high-precision, high-spatiotemporal-resolution soil moisture content data. Currently, there is no relevant research on using the NDII vegetation index for soil moisture content downscaling. Attached Figure Description

[0008] Figure 1 This is a schematic diagram of the TWI index extracted from a 10km watershed using this invention.

[0009] Figure 2 This is a schematic diagram of the TWI index extracted from a 1km watershed using this invention.

[0010] Figure 3 This is a schematic diagram of the NDII index extracted from a 10km watershed using this invention.

[0011] Figure 4 This is a schematic diagram of the NDII index extracted from a 1km watershed according to the present invention.

[0012] Figure 5 This is a schematic diagram of soil moisture content over a 10km stretch of watershed extracted by the present invention.

[0013] Figure 6 This is a schematic diagram of the soil moisture content over a 1km stretch of watershed extracted by this invention. Detailed Implementation

[0014] To obtain high spatial resolution soil moisture content data, this invention provides a soil moisture content downscaling method that considers topographic and vegetation factors. By using soil moisture content downscaling transformation parameters obtained from high-resolution topographic and vegetation data, a soil moisture content downscaling model is constructed to obtain high spatial resolution soil moisture content data, which can provide high-quality data support for research in the fields of hydrology and ecology.

[0015] Example 1: A method for downscaling soil moisture content based on topography and vegetation indices includes the following steps: S1: Extract the watershed mask file based on DEM (Digital Elevation Model) data at 10km and 1km resolutions; Specifically, the following steps are included: S1-1: Based on DEM data at 10km and 1km resolutions, the basin boundary is extracted and the basin mask file is obtained by filling depressions, calculating flow direction, calculating cumulative runoff, determining the watershed outlet station, and obtaining the watershed mask file. S1-2: Based on DEM data at 10km and 1km resolutions, calculate slope, aspect, TWI, curvature, and other data at 10km and 1km resolutions. The TWI index is as follows: Figure 1 and Figure 2 As shown; S2: Extract normalized differential infrared index (NDII) data for 10km and 1km of the watershed from the watershed mask file; Specifically, the following steps are included: S2-1: Calculate NDII value based on MODIS data MOD09A1 data product (500m) (1) In the formula, It is the reflectivity at a wavelength of 0.85µm; It is the reflectivity at a wavelength of 1.65µm; the NDII normalization index ranges from [-1, 1]. S2-2: Based on NDII data with a spatial resolution of 500m, NDII data with spatial resolutions of 10km and 1km are obtained by averaging. S2-3: Based on the watershed mask file, extract the NDII values ​​at spatial resolutions of 10km and 1km for the watershed, such as... Figure 3 and Figure 4 As shown; S3: Based on the watershed mask file, extract satellite data on soil moisture content over a 10km radius within the watershed, such as... Figure 5 As shown; S4: Based on normalized index TWI and normalized differential infrared index NDII data, construct a downscaling weight for soil moisture content from coarse resolution to fine resolution. Specifically, the following steps are included: The soil moisture content downscaling factor is based on a 10km topographic map of the watershed, from coarse to fine resolution. Satisfy the following calculation formula (2) In the formula, Soil moisture content data with a spatial resolution of 10 km before downscaling, in m³. 3 / m 3 .

[0016] Assumption To and The function is calculated based on the curvature of the slope, and the calculation formulas are as follows: (3) In the formula, The slope aspect on a 10km scale; Let be a function of slope and aspect on a 10km scale, and its expression is: (4) In the formula, Slope; The average slope of the area; The coefficient is related to slope aspect, for slopes in the four directions of north, south, west, and east. The values ​​are -0.01, 0.005, -0.003, and 0.002, respectively. , which is a function of slope and aspect on a 10km scale; Once determined, linear regression is used to analyze... and Fit the data and construct and The relationship between the two + (5) Sure and Then, apply it. b The calculation of soil moisture content on the m-scale, at this point... In equation (6), The slope aspect on a 1km scale. Let be a function of slope and aspect on a 1km scale; p and q are fitting coefficients. The topographic humidity index is measured on a 1km scale.

[0017] S5: Multiply the soil moisture content downscaling factor by the coarse-resolution soil moisture content data to obtain soil moisture content data with a spatial resolution of 1 km.

[0018] The parameter conversion relationship between soil moisture and vegetation index is determined in step S4 based on the Normalized Differential Infrared Index (NDII), specifically including the following steps: Since the normalized differential infrared index (NDII) ranges from [-1, 1], the min-max method is first used to standardize the NDII data at the 1 km and 10 km scales. The calculation formula is as follows: (7) (8) In the formula, and These are the normalized differential red index values ​​at scales of 1km and 10km, respectively; , The standardized NDII indices are for 1km and 10km scales, respectively. Based on the standardized Normalized Difference Indices (NDII) values, the downscaling transformation parameters of soil moisture content based on vegetation were calculated. (9) In the formula These are the downscaling transformation parameters of soil moisture content obtained based on the Normalized Differential Infrared Index (NDII).

[0019] The soil moisture downscaling in S4, based on TWI and NDII soil moisture downscaling parameters, specifically includes the following steps: Based on the downscaling transformation parameters of soil moisture content obtained using the normalized index TWI and the normalized differential infrared index NDII, the soil moisture content downscaling transformation parameters were determined. (10) In the formula, The parameters are downscaling transformation parameters for soil moisture content at a 1km scale.

[0020] Based on 10km soil moisture content data and soil moisture content downscaling transformation parameters, the formula for downscaling soil moisture content at 1km is calculated as follows: (11) In the formula, For downscaled soil moisture data with a spatial resolution of 1 km, such as Figure 5 and Figure 6 As shown.

[0021] The above description is only a preferred embodiment of the present invention. It should be noted that those skilled in the art can make several changes and improvements without departing from the overall concept of the present invention, and these should also be considered within the scope of protection of the present invention.

Claims

1. A method for downscaling soil moisture content based on topography and vegetation indices, characterized in that: Includes the following steps: S1: Extract the watershed mask file based on DEM data at 10km and 1km resolution; Specifically, the following steps are included: S1-1: Based on DEM data at 10km and 1km resolutions, the basin boundary is extracted and the basin mask file is obtained by filling depressions, calculating flow direction, calculating cumulative runoff, determining the watershed outlet station, and obtaining the watershed mask file. S1-2: Calculate slope, aspect, TWI, and curvature data based on 10km and 1km resolution DEM data; S2: Extract normalized differential infrared index data for 10km and 1km of the watershed from the watershed mask file; Specifically, the following steps are included: S2-1: Calculating NDII value based on MODIS data MOD09A1 data product （1） In the formula, It is the reflectivity at a wavelength of 0.85µm; It is the reflectivity at a wavelength of 1.65µm, and the NDII normalization index ranges from [-1,1]. S2-2: Based on NDII data with a spatial resolution of 500m, NDII data with spatial resolutions of 10km and 1km are obtained by averaging. S2-3: Extract the NDII values ​​at spatial resolutions of 10km and 1km based on the watershed mask file; S3: Extract satellite data on soil moisture content of the watershed based on the watershed mask file; S4: Based on normalized index TWI and normalized differential infrared index NDII data, construct a downscaling weight for soil moisture content from coarse resolution to fine resolution. Specifically, the following steps are included: The soil moisture content downscaling factor is based on a 10km topographic map of the watershed, from coarse to fine resolution. Satisfy the following calculation formula （2） In the formula, Soil moisture content data with a spatial resolution of 10 km before downscaling, in m³. 3 / m 3 ; To and The function is calculated based on the curvature of the slope, and the calculation formulas are as follows: （3） In the formula, The slope aspect on a 10km scale; Let be a function of slope and aspect on a 10km scale, and its expression is: （4） In the formula, Slope; The average slope of the area; The coefficient is related to slope aspect, for slopes in the four directions of north, south, west, and east. The values ​​are -0.01, 0.005, -0.003, and 0.002, respectively. It is a function of slope and aspect on a 10km scale; Once determined, linear regression is used to analyze... and Fit the data and construct and The relationship between the two + （5） Sure and Then, it was applied to the calculation of soil moisture content at a 1km scale. （6）； In equation (6), The slope aspect on a 1km scale. Let be a function of slope and aspect on a 1km scale; p and q are fitting coefficients. The topographic humidity index is measured on a 1km scale.

2. The method for downscaling soil moisture content based on topography and vegetation indices according to claim 1, characterized in that, The parameter conversion relationship between soil moisture and vegetation index is determined in step S4 based on the Normalized Differential Infrared Index (NDII), specifically including the following steps: Since the normalized differential infrared index (NDII) ranges from [-1, 1], the min-max method is first used to standardize the NDII data at the 1 km and 10 km scales. The calculation formula is as follows: （7） （8） In the formula, The normalized differential infrared index value is the value at a 1km scale; The normalized difference index value at a 10km scale; The standardized NDII index is calculated at a 1km scale. The NDII index is standardized for a 10km scale. Based on the standardized Normalized Difference Indices (NDII) values, the downscaling transformation parameters of soil moisture content at a 1 km scale based on vegetation were calculated. （9） In the formula These are the downscaling transformation parameters of soil moisture content obtained based on the Normalized Differential Infrared Index (NDII).

3. The method for downscaling soil moisture content based on topography and vegetation indices according to claim 2, characterized in that, The soil moisture downscaling in S4, based on TWI and NDII soil moisture downscaling parameters, specifically includes the following steps: Based on the downscaling transformation parameters of soil moisture content obtained using the normalized index TWI and the normalized differential infrared index NDII, the soil moisture content downscaling transformation parameters were determined. （10） In the formula, The downscaling transformation parameter for soil moisture content at a 1km scale. Soil moisture content at a 1km scale The downscaling transformation parameter for soil moisture content at a 1km scale; Based on 10km soil moisture content data and soil moisture content downscaling transformation parameters, the formula for downscaling soil moisture content at 1km is calculated as follows: （11） In the formula, This is soil moisture content data with a spatial resolution of 1 km after downscaling.

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