A long-term high-resolution dataset of grasslands grazing intensity in China

被引:3
|
作者
Wang, Daju [1 ,2 ]
Peng, Qiongyan [1 ]
Li, Xiangqian [1 ]
Zhang, Wen [3 ]
Xia, Xiaosheng [1 ]
Qin, Zhangcai [1 ]
Ren, Peiyang [1 ]
Liang, Shunlin [4 ]
Yuan, Wenping [5 ]
机构
[1] Sun Yat Sen Univ, Guangdong Prov Data Ctr Terr & Marine Ecosyst Carb, Sch Atmospher Sci, Zhuhai 510245, Guangdong, Peoples R China
[2] Int Res Ctr Big Data Sustainable Dev Goals, Beijing 100094, Peoples R China
[3] Chinese Acad Sci, Inst Atmospher Phys, State Key Lab Atmospher Boundary Layer Phys & Atmo, Beijing 100029, Peoples R China
[4] Univ Hong Kong, Dept Geog, JockeyClub STEM Lab Quantitat Remote Sensing, Hong Kong, Peoples R China
[5] Peking Univ, Inst Carbon Neutral, Sino French Inst Earth Syst Sci, Coll Urban & Environm Sci, Beijing 100091, Peoples R China
关键词
VEGETATION; MODIS;
D O I
10.1038/s41597-024-04045-x
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Grazing is a significant anthropogenic disturbance to grasslands, impacting their function and composition, and affecting carbon budgets and greenhouse gas emissions. However, accurate evaluations of grazing impacts are limited by the absence of long-term high-resolution grazing intensity data (i.e., the number of livestock per unit area). This study utilized census livestock data and a satellite-based vegetation index to develop the first Long-term High-resolution Grazing Intensity (LHGI) dataset of grassland in seven pastoral provinces in western China from 1980 to 2022. The LHGI dataset effectively captured spatial variations in grazing intensity, with validation at 73 sites showing a correlation coefficient (R2) of 0.78. The county-level validation showed an averaged R2 values of 0.73 +/- 0.03 from 1980 to 2022. This dataset serves as a vital resource for estimating grassland carbon cycling and livestock system CH4 emissions, as well as contributing to grassland management.
引用
收藏
页数:15
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