The Gansu Yellow River Basin represents a complex socio-economic-natural ecosystem where developmental and ecological issues intertwine. The soil conservation service of its ecosystem serves as a crucial safeguard for preventing soil erosion and promoting high-quality development. Utilizing the Normalized Difference Vegetation Index (NDVI), the Land Cover product MCD12Q1, precipitation data, Digital Elevation Model (DEM) data, and the Harmonized World Soil Database (HWSD) v1.1, the Revised Universal Soil Loss Equation (RUSLE) was employed to calculate and obtain the soil conservation service dataset for the Gansu Yellow River Basin. This dataset spans a spatial range between 33°6′29″ North latitude and 40°0′6″ North latitude, and 97°23′38″ East longitude and 108°42′38″ East longitude, with a temporal span from 2001 to 2015. The unit of measurement is t•hm-2•a-1. It provides a scientific basis for formulating measures to enhance soil conservation services and offers important data support for assessing ecological security and constructing ecological security patterns.
The Normalized Difference Vegetation Index (NDVI) is sourced from the Resource and Environmental Science Data Registration and Publishing System (http://www.resdc.cn/DOI, DOI: 10.12078/2018060601). The Land Cover product MCD12Q1, which utilizes a vegetation functional type classification scheme for land cover data, is obtained from the NASA website. Precipitation data is sourced from the National Tibetan Plateau Scientific Data Center. Digital Elevation Model (DEM) data is acquired from the Resource and Environment Science and Data Center of the Chinese Academy of Sciences. The Harmonized World Soil Database (HWSD) v1.1 is obtained from the National Cryosphere Desert Data Center.
The soil conservation service was calculated using the RUSLE-based soil conservation service evaluation model (Zhang L W, Fu B J, Lü Y H, et al, 2015. Balancing multiple ecosystem services in conservation priority setting [J]. Landscape Ecology, 30(3): 535–546. DOI: https://doi.org/10.1007/s10980-014-0106-z.)
During the remote sensing image imaging process, due to the influence of weather conditions such as cloud cover, rain, and snow, as well as satellite operating status, some pixel values in the remote sensing data (NDVI, MCD12Q1) exhibit abnormally large or small values. This results in negative values being calculated for soil conservation services, which are uniformly processed as 0. The study area covers a total of 193,462 pixels. From 2001 to 2015, the number of pixels with negative soil conservation services reached a maximum of 11 in 2015, a minimum of 0 in 2002, and an annual average of 4.20 pixels per year (pixel•a-1), which is less than 1/100,000.
| # | number | name | type |
| 1 | 22JR5R194 | Natural Science Foundation of Gansu Province | |
| 2 | 2022QB−143 | other |
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CSTR:11738.11.NCDC.YRIVER.DB4025.2023
10.12072/ncdc.yriver.db4025.2023