Distribution pattern of rocky desertification in southwest China and analysis of its main driving factors based on GIS and Geodetector
Data files
Oct 25, 2023 version files 12.91 GB
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Data_Description.docx
14.89 KB
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Elevation_Southwest.rar
6.55 GB
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People_density_SouthwestChina.rar
3.27 MB
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Precipitation2020_China.rar
196.35 MB
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README.md
5 KB
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Slope_SouthwestChina.rar
3.73 GB
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Southwest_Albedo_MODIS_006_MCD43A3-20230505T092210Z-001.zip
221.60 MB
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Southwest_Lithology.rar
8.19 MB
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Southwest_LST_MODIS_006_MOD11A2-20230505T095621Z-001.zip
76.80 MB
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Southwest_LST_MODIS_006_MOD11A2-20230505T104928Z-001.zip
214.45 MB
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Southwest_NDVI_MODIS_006_MOD13A1-20230505T063005Z-001.zip
412.62 MB
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Southwest_TGSI_MODIS_006_MCD43A4-20230506T005344Z-001.zip
1.50 GB
Abstract
Rocky desertification, a pressing environmental concern in Southwest China, significantly impacts local living conditions and regional sustainability. Employing remote sensing on a macro scale, this study focuses on identifying and analyzing the spatial distribution and driving factors of rocky desertification. Conducted in Southwest China, using Landsat data from Google Earth Engine for 2020, the research quantitatively extracts information on rocky desertification patches through traditional methods. Excluding unlikely areas using land use data, spatial distribution features and driving factors are examined via GIS spatial analysis and a geodetector model. The main conclusions are as follows. Rocky desertification covers 217,530.4 km2 (accounting for 15.6% of Southwest China), with areas of slight, moderate, and severe rocky desertification at 81.3%, 7.1%, and 11.6%, respectively. Spatially, rocky desertification primarily occurs in areas where lithology is carbonate rock between clastic rocks and continuous limestone, slope exceeds 15°, elevation ranges is 1000–2000 m, land use types are grassland and woodland, precipitation is 80–120 mm, and population density is below 50 people/km2. Human activities have minimal influence. Geodetector analysis identifies lithology, land use type, and slope as primary driving factors, with interactive effects of lithology and land use type and slope and land use type jointly influencing rocky desertification formation in Southwest China.
README
Data Description:
[Access this dataset on Dryad](DOI: 10.5061/dryad.ns1rn8q0p)
Description of the data and file structure
This dataset encompasses various influencing factors related to land degradation in Southwest China, alongside a collection of remote sensing data used for extracting the extent of land degradation.
Influencing Factor Data
- Elevation_Southwest:
- Data Type: Raster Data
- Resolution: 30 meters
- Unit: Meters
- Description: Elevation data and Slope data for the Southwest China.
- Lithology_SouthwestChina:
- Data Type: Vector Data (Shapefile)
- Description: This is about the rock type data of the southwestern region of China, including five provinces: Sichuan, Yunnan, Guangxi, Guizhou, and Chongqing. It includes the distribution of carbonate rocks, limestone, dolomite, and other types.
- People_density_SouthwestChina:
- Data Type: Raster Data
- Resolution: 1 km
- Unit: People/km²
- Description: Population density data for Southwest China.
- Precipitation2020_China:
- Data Type: Raster Data
- Resolution: 1km
- Unit: Millimeters
- Description: Precipitation data for China in the year 2020.Monthly average rainfall data for 12 months in total, e.g. "pre_2020_1" represents the average rainfall for January 2020
- Slope_SouthwestChina:
- Data Type: Raster Data
- Resolution: 30 meters
- Unit: Degrees
- Description: Southwest_Slope-Slope data for Southwest China. Slope_Reclass:0–8°, 8–15°, 15–25°, 15–25°, four categories.
Remote Sensing Data for Land Degradation Extraction
- Southwest_Albedo_MODIS_006_MCD43A3:
- Data Type: Raster Data
- Resolution: 500 meters
- Description: MODIS_006_MCD43A3 is one of the surface reflectance data products collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensor. MODIS is a collaboration between NASA (National Aeronautics and Space Administration) and NOAA (National Oceanic and Atmospheric Administration), designed to monitor various physical parameters of the Earth's surface, atmosphere, land, and oceans.This data range is for Southwest China.The time frame for this data is 2000 to 2020
- Southwest_LST_MODIS_006_MOD11A2:
- Data Type: Raster Data
- Resolution: 1 km
- Description: MODIS_006_MOD11A2 is one of the data products provided by the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensor, offering information on land surface temperature and fire points.This data range is for Southwest China.The time frame for this data is 2000 to 2020
- Southwest_NDVI_MODIS_006_MOD13A1:
- Data Type: Raster Data
- Resolution:250 meters
- Description:MODIS_006_MOD13A1 is one of the vegetation index data products provided by the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensor.This data range is for Southwest China.The time frame for this data is 2000 to 2020
- Southwest_TGSI_MODIS_006_MCD43A4:
- Data Type: Raster Data
- Resolution: 500 meters
- Description: MODIS_006_MCD43A4 is one of the data products provided by the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensor, offering information on land surface bidirectional reflectance distribution function (BRDF) and albedo.TGSI is obtained by calculating.This data range is for Southwest China.The time frame for this data is 2000 to 2020
Sharing/Access information
This document provides an overview of the data accessibility for the following five websites:
- US Geological Survey (USGS) (https://www.usgs.gov):
Data Types: Geological, geographical, hydrological, and various other fields.
Open Access Policy: USGS offers extensive open data, allowing users to access, download, and use the data free of charge.
- National Earth System Science Data Sharing Service Platform (http://www.gscloud.cn):
Data Types: Diverse data covering the field of Earth system science.
Open Access Policy: The platform is committed to data sharing, enabling users to freely access data according to the platform's regulations.
- Resource and Environmental Science Data Center (https://www.resdc.cn):
Data Types: Data related to resource and environmental science.
Open Access Policy: The data center supports open access, and users can find detailed data download information on the website.
- China Meteorological Administration (http://www.cma.gov.cn):
Data Types: Meteorological data, including weather and climate-related information.
Open Access Policy: The China Meteorological Administration provides some open data through its website, allowing users to access meteorological information.
- National Bureau of Statistics of China - Annual Data (http://www.stats.gov.cn/tjsj/ndsj):
Data Types: Annual statistical data covering various fields.
Open Access Policy: The National Bureau of Statistics of China provides open accessto annual statistical data through its official website, allowing users to download and use the data.
All users can use this dataset for free
Methods
The rocky desertification data were obtained from Landsat 8 operational land imager (OLI) image data provided by the U.S. Geological Survey (USGS) ("https://www.usgs.gov"), de-clouded based on the Google Earth Engine (GEE), and atmospherically corrected using ENVI5.3 Fast line-of-sight atmospheric analysis of spectral hypercubes (FLAASH) atmospheric correction tool with a spatial resolution of 30 m [37,38]. The land use type data with a spatial resolution of 1000 m were downloaded from the Resource and Environmental Science and Data Center of the Chinese Academy of Sciences ("https://www.resdc.cn"). The land use types in these data mainly include watersheds, rivers, and urban industrial construction land, cultivated land, woodland, grassland, and unutilized land. The overall accuracy of this dataset reached 95.41%, which met the needs of this study. The digital elevation model (DEM) data for the study area were obtained from the Geospatial Data Cloud Platform of the Computer Network Information Center of the Chinese Academy of Sciences ("http://www.gscloud.cn"), with a spatial resolution of 30 m. The precipitation data for 2020 were obtained from the China Meteorological Administration ("http://www.cma.gov.cn/"). The monthly average precipitation data of Southwest China for 2020 were obtained after kriging interpolation. The population density data were obtained from the 2020 Yearbook of the National and Local Government Statistical Bureau ("http://www.stats.gov.cn/tjsj/ndsj/").