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Mapping abandoned farmland in China using time series MODIS NDVI
Xiufang Zhu1, Guofeng Xiao2, Dujuan Zhang3
1State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences, Beijing 100875, China; Key Laboratory of Environmental Change and Natural Disaster, Ministry of Education, Beijing Normal University, Beijing 100875, China; Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China.
Abstract:
Farmland abandonment is an important aspect of land cover land use (LCLU) that has both positive and negative effects on the environment. There is limited information regarding the spatial distribution of abandoned farmland in China. In this study, we 1) use a C5.0 decision tree classification based on a 250 m spatial resolution Moderate-resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) time series to develop LCLU maps for the period 2000-2017; 2) produce time series maps of the abandoned farmland during the period 2002-2017 based on LCLU maps; and 3) analyze spatial distribution, intensity, trend, frequency, and recultivation in terms of farmland abandonment. The results show that the overall accuracy of the LCLU maps ranged from 85.45% to 90.56% over the study period (2002-2017). The average national rate of farmland abandonment was 5% over the period 2002-2017, with the lowest rate in 2002 and the highest in 2015. Approximately 60% of the 34 agricultural areas in China showed an increasing trend for abandonment including some of the main grain-producing areas such as the North China Plain and the middle and lower reaches of the Yangtze River. Abandoned farmland areas with an abandonment frequency of ≤ 3 y comprised 58.24% of the total area of abandoned farmland. The first map detailing the distribution of the abandoned farmland across China was produced in this study, providing guidance for the development of a method of identifying abandoned farmland on a large spatial scale.
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