International Journal of Applied Earth Observations and Geoinformation | |
Satellite observed rapid green fodder expansion in northeastern Tibetan Plateau from 2010 to 2019 | |
Yuzhe Li1  Yuanyuan Di2  Qiang Zhang3  Jie Wang3  Nanshan You3  Tong Yang3  Geli Zhang3  Russell B. Doughty3  Ruoqi Liu4  Danfeng Sun4  Jiangwen Fan4  | |
[1] Corresponding author at: College of Land Science and Technology, China Agricultural University, Beijing 100193, China..;College of Grassland Science and Technology, China Agricultural University, Beijing 100193, China;College of Land Science and Technology, China Agricultural University, Beijing 100193, China;Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; | |
关键词: Green fodder mapping; Pixel- and phenology-based approach; Google Earth Engine (GEE); Landsat; Northeastern Tibetan Plateau; Rapid expansion; | |
DOI : | |
来源: DOAJ |
【 摘 要 】
The livestock product consumption per capita in China has almost doubled in the past three decades. The planting of green fodder has increased in the agropastoral ecotone of China to meet the increasing demand for livestock feed, and the green fodder expansion can have subsequent consequences on the environment. However, information on the area and distribution of green fodder is very limited. Here, we developed a pixel- and phenology-based algorithm to map green fodder and track its dynamics in the northeastern Tibetan Plateau, a typical alpine pasture region in China, using all the available Landsat images and Google Earth Engine (GEE). We developed a simple approach for the rapid identification of green fodder fields by using a new green fodder index that considers the unique phenology of green fodder, which has higher greenness and water content in the late growing season than other vegetation. A total of 858 Landsat images were used to generate green fodder maps in northeastern Tibetan Plateau (including Zeku, Guinan, and Tongde Counties) in three periods (circa 2010, 2015, and 2019). The overall accuracies of our green fodder maps were 93–97% and the Matthews correlation coefficients were 0.76–0.83. We found a rapid expansion of green fodder from 16.3 km2 in 2010 to 136.1 km2 in 2019. Newly cultivated green fodder occurred in both existing croplands and natural grasslands. Our study demonstrated the potential of the phenology-based approach, all the available Landsat images, and GEE for tracing the historical dynamics of green fodder at 30-m resolution in alpine regions. Our findings advance our understanding of changes in forage area, production, the supply–demand gap, and the ecological and climatic consequences of green fodder expansion.
【 授权许可】
Unknown