Bulletin of Surveying and Mapping ›› 2025, Vol. 0 ›› Issue (4): 152-157.doi: 10.13474/j.cnki.11-2246.2025.0425

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Spatio-temporal distribution of grassland degradation in the Qilian Mountain area from 2013 to 2020 based on Landsat 8 OLI data

TIAN Dan1, BAI Xiao2, QIN Kun1   

  1. 1. First Institute of Photogrammetry and Remote Sensing, Ministry of Natural Resources, Xi'an 710054, China;
    2. College of Geomatics, Xi'an University of Science and Technology, Xi'an 710054, China
  • Received:2024-08-20 Published:2025-04-28

Abstract: To clarify the spatio-temporal distribution characteristics of grassland degradation in the Qilian Mountain area and to assess its degradation trends, this study uses Landsat 8 OLI image data in conjunction with geographical national condition monitoring results. By calculating the normalized difference vegetation index (NDVI) and grassland degradation index (GDI) from 2013 to 2020, a quantitative analysis of the spatial and temporal changes in grassland coverage and degradation in the area is conducted. The results show that: ①The grassland coverage area in the Qilian Mountain area is 121 039.75 km2, accounting for 79.15% of the total area, with high coverage grasslands accounting for 28.25%.②The grassland degradation index in the Qilian Mountain area decreases from 1.59 in 2014 to 1.27 in 2020, indicating an overall improvement in the temporal trend.③The spatial distribution of degraded grasslands shows significant heterogeneity, with more concentrated degradation in the western region, while the central and eastern regions show no significance. The change trends in the grassland degradation index vary significantly among different watersheds, with the Huangshui/Datong River and Hexi Corridor areas showing a fluctuating downward trend, while the Qaidam Basin area has risen after 2018. The findings provide a scientific basis for assessing grassland degradation and vegetation restoration in the Qilian Mountain area, which is of great significance for regional ecological protection and sustainable development.

Key words: grassland degradation, remote sensing in ecology, spatio-temporal analysis, Qilian Mountain area, Landsat 8 OLI

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