Mapping Alpine Grassland Fraction Coverage Using Zhuhai-1 OHS Imagery in the Three River Headwaters Region, China

Author:

Xing Fei123ORCID,An Ru1,Guo Xulin3,Shen Xiaoji45ORCID,Soubry Irini3ORCID,Wang Benlin26ORCID,Mu Yanmei37,Huang Xianglin2

Affiliation:

1. College of Hydrology and Water Resources, Hohai University, Nanjing 210024, China

2. School of Earth Science and Engineering, Hohai University, Nanjing 211100, China

3. Department of Geography and Planning, University of Saskatchewan, Saskatoon, SK S7N 5C8, Canada

4. Yangtze Institute for Conservation and Development, Hohai University, Nanjing 210024, China

5. Department of Civil Engineering, Monash University, Clayton, VIC 3800, Australia

6. School of Geographic Information and Tourism, Chuzhou University, Chuzhou 239000, China

7. Yanchi Research Station, School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China

Abstract

The widely spread alpine grassland ecosystem in the Three River Headwaters Region (TRHR) plays an essential ecological role in carbon sequestration and soil and water conservation. In this study, we test the latest high spatial resolution hyperspectral (Zhuhai-1 OHS) remote sensing imagery to examine different alpine grassland coverage levels using Multiple Endmember Spectral Mixture Analysis (MESMA). Our results suggest that the 3-endmember (3-EM) MESMA model can provide the highest image pixel unmixing percentage, with a percentage exceeding 97% and 96% for pixel scale and landscape scale, respectively. The overall accuracy shows that Zhuhai-1 OHS imagery obtained the highest overall accuracy (83.7%, k = 0.77) in the landscape scale, but in the pixel scale, it is not as good as Landsat 8 OLI imagery. Overall, we can conclude that the hyperspectral imagery combined 3-EM MESMA model performs better in both pixel scale and landscape scale alpine grassland coverage mapping, while the multispectral imagery with the 3-EM MESMA model can satisfy requirements of alpine grassland coverage mapping at the pixel scale. The approaches and workflow to mapping alpine grassland in this study can help monitor alpine grassland degradation; not only in the Qinghai–Tibetan Plateau (QTP), but also in other grassland ecosystems.

Funder

National Natural Science Foundation of China

Natural Sciences and Engineering Research Council of Canada

Key Project of Natural Science Research of Anhui Provincial Department of Education

China Scholarship Council

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

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