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

Author:

Xu Xuefeng1,Tang Jiakui12ORCID,Zhang Na12ORCID,Zhang Anan1,Wang Wuhua1ORCID,Sun Qiang3

Affiliation:

1. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China

2. Beijing Yanshan Earth Critical Zone National Research Station, University of Chinese Academy of Sciences, Beijing 101408, China

3. Beijing Geoway Software Co., Ltd., Beijing 100049, China

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.

Funder

CAS Strategic Priority Research Program

Science & Technology Fundamental Resources Investigation Program

Publisher

MDPI AG

Subject

Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development,Building and Construction

Reference47 articles.

1. Coupland, R.T. (1978). Grassland Ecosystems of the World: Analysis of Grasslands and Their Uses, Cambridge University Press.

2. Archibold, O.W. (1995). Ecology of World Vegetation, Springer.

3. White, R.P., Murray, S., and Rohweder, M. (2000). Grasslands of the World, World Resources Institute.

4. White, R., Murray, S., and Rohweder, M. (2000). Pilot Analysis of Global Ecosystems: Grassland Ecosystems, World Resources Institute.

5. The Steppe Biome in Russia: Ecosystem Services, Conservation Status, and Actual Challenges;Werger;Eurasian Steppes. Ecological Problems and Livelihoods in a Changing World; Plant and Vegetation,2012

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