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Article

Spatial Autocorrelation Analysis of Land Use and Ecosystem Service Value in the Huangshui River Basin at the Grid Scale

1
School of Geographical Science, Qinghai Normal University, Xining 810008, China
2
Institute of Qinghai Meteorological Science Research, Xining 810008, China
3
Ministry of Education Key Laboratory of Tibetan Plateau Land Surface Processes and Ecological Conservation, Xining 810008, China
4
Qinghai Province Key Laboratory of Physical Geography and Environmental Process, Xining 810008, China
5
Qinghai Province Key Laboratory of Disaster Prevention and Mitigation, Xining 810008, China
6
Qinghai Provincial Key Laboratory of Restoration Ecology in Cold Regions, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810008, China
7
Qinghai General Station of Grassland, Xining 810008, China
8
Institute of Meteorological Development and Planning, China Meteorological Administration, Beijing 100081, China
*
Author to whom correspondence should be addressed.
Plants 2022, 11(17), 2294; https://doi.org/10.3390/plants11172294
Submission received: 10 August 2022 / Revised: 30 August 2022 / Accepted: 31 August 2022 / Published: 2 September 2022
(This article belongs to the Special Issue Alpine Ecosystems in a Changing World)

Abstract

The Huangshui River Basin is one of the most densely populated areas on the Qinghai–Tibet Plateau and is characterized by a high level of human activity. The contradiction between ecological protection and socioeconomic development has become increasingly prominent; determining how to achieve the balanced and coordinated development of the Huangshui River Basin is an important task. Thus, this study used the Google Earth Engine (GEE) cloud-computing platform and Sentinel-1/2 data, supplemented with an ALOS digital elevation model (ALOS DEM) and field survey data, and combined a remote sensing classification method, grid method, and ecosystem service value (ESV) evaluation method to study the spatial correlation and interaction between land use (LU) and ESV in the Huangshui River Basin. The following results were obtained: (1) on the GEE platform, Sentinel-1/2 active and passive remote sensing data, combined with the gradient tree-boosting algorithm, can efficiently produce highly accurate LU data with a spatial resolution of 10 m in the Huangshui River Basin; the overall accuracy (OA) reached 88%. (2) The total ESV in the Huangshui River Basin in 2020 was CNY 33.18 billion (USD 4867.2 million), of which woodland and grassland were the main contributors to ESV. In the Huangshui River Basin, the LU type, LU degree, and ESV have significant positive spatial correlations, with urban and agricultural areas showing an H-H agglomeration in terms of LU degree, with woodlands, grasslands, reservoirs, and wetlands showing an H-H agglomeration in terms of ESV. (3) There is a significant negative spatial correlation between the LU degree and ESV in the Huangshui River Basin, indicating that the enhancement of the LU degree in the basin could have a negative spatial spillover effect on the ESV of surrounding areas. Thus, green development should be the future direction of progress in the Huangshui River Basin, i.e., while maintaining and expanding the land for ecological protection and restoration, and the LU structure should be actively adjusted to ensure ecological security and coordinated and sustainable socioeconomic development in the Basin.
Keywords: land use; ecosystem service value; GEE platform; Sentinel 1/2; Huangshui River Basin land use; ecosystem service value; GEE platform; Sentinel 1/2; Huangshui River Basin

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MDPI and ACS Style

Shi, F.; Zhou, B.; Zhou, H.; Zhang, H.; Li, H.; Li, R.; Guo, Z.; Gao, X. Spatial Autocorrelation Analysis of Land Use and Ecosystem Service Value in the Huangshui River Basin at the Grid Scale. Plants 2022, 11, 2294. https://doi.org/10.3390/plants11172294

AMA Style

Shi F, Zhou B, Zhou H, Zhang H, Li H, Li R, Guo Z, Gao X. Spatial Autocorrelation Analysis of Land Use and Ecosystem Service Value in the Huangshui River Basin at the Grid Scale. Plants. 2022; 11(17):2294. https://doi.org/10.3390/plants11172294

Chicago/Turabian Style

Shi, Feifei, Bingrong Zhou, Huakun Zhou, Hao Zhang, Hongda Li, Runxiang Li, Zhuanzhuan Guo, and Xiaohong Gao. 2022. "Spatial Autocorrelation Analysis of Land Use and Ecosystem Service Value in the Huangshui River Basin at the Grid Scale" Plants 11, no. 17: 2294. https://doi.org/10.3390/plants11172294

APA Style

Shi, F., Zhou, B., Zhou, H., Zhang, H., Li, H., Li, R., Guo, Z., & Gao, X. (2022). Spatial Autocorrelation Analysis of Land Use and Ecosystem Service Value in the Huangshui River Basin at the Grid Scale. Plants, 11(17), 2294. https://doi.org/10.3390/plants11172294

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