Remote Sensing Classification of Temperate Grassland in Eurasia Based on Normalized Difference Vegetation Index (NDVI) Time-Series Data

Xuefeng Xu, Jiakui Tang (), Na Zhang, Anan Zhang, Wuhua Wang and Qiang Sun
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Xuefeng Xu: College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
Jiakui Tang: College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
Na Zhang: College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
Anan Zhang: College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
Wuhua Wang: College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
Qiang Sun: Beijing Geoway Software Co., Ltd., Beijing 100049, China

Sustainability, 2023, vol. 15, issue 20, 1-16

Abstract: The Eurasian temperate grassland is the largest temperate grassland ecosystem and vegetation transition zone globally. The spatiotemporal distribution and changes of grassland types are vital for grassland monitoring and management. However, there is currently a lack of a unified classification method and standard distribution map of Eurasian temperate grassland types. The Normalized Difference Vegetation Index (NDVI) from remote sensing data is commonly used in grassland monitoring. In this paper, the Accumulated Rate of NDVI Change Index (ARNCI) was proposed to characterize the annual NDVI trend of different temperate grassland types, and four transitional categories were introduced to account for the overlap between them. Based on survey data on the distribution of Eurasian temperate grassland types in the 1980s, the study area was divided into three sub-regions: Northern China, Central Asia, and Mongolia. Regionally, pixel-based ARNCI maps in the 1980s and 1990s were successfully calculated from using NOAA’s AVHRR NDVI time-series products. The ARNCI classification thresholds for different sub-regions were determined, and classification experiments and validation were conducted for each sub-region. The overall accuracies of grasslands types classification for Northern China, Central Asia, and Mongolia in the 1980s were 75.3%, 64.2%, and 84.6%, respectively, which demonstrated that there were variations in classification accuracy in the three sub-regions, and the overall performance was favorable. Finally, distribution maps of Eurasian temperate grassland types in the 1980s and 1990s were obtained, and the spatiotemporal changes of grassland types were analyzed and discussed. The ARNCI method is simple to operate and easy to obtain data, and it can be conveniently used in grassland type classification. The maps firstly address the lack of remote sensing classification maps of Eurasian temperate grassland types, and provide a promising tool for monitoring grassland degradation, management, and utilization.

Keywords: normalized difference vegetation index; remote sensing classification; temperate grassland; grassland types; Eurasia (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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