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

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 (R<sup>2</sup>) of 0.78. The county-level validation showed an averaged R<sup>2</sup> 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 CH<sub>4</sub> emissions, as well as contributing to grassland management.

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Publication Details

Journal
Scientific Data
Published
2024-11-05
DOI
https://doi.org/10.1038/s41597-024-04045-x
Citations
48
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
22.03
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article

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

Qiongyan Peng, Zhangcai Qin, Daju Wang, Xiaosheng Xia et al.
48 citations
Scientific Data
Remote Sensing in Agriculture
22.03
article

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

Qiongyan Peng, Zhangcai Qin, Daju Wang, Xiaosheng Xia, Shunlin Liang, Wenping Yuan, Xiangqian Li, Wen Zhang, Peiyang Ren
article en
48 citations

Abstract

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 (R<sup>2</sup>) of 0.78. The county-level validation showed an averaged R<sup>2</sup> 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 CH<sub>4</sub> emissions, as well as contributing to grassland management.

Scientific DataVol. 11(1)
Sun Yat-sen University (CN), Chinese Academy of Sciences (CN), Peking University (CN), Beijing Institute of Big Data Research (CN), Hong Kong Jockey Club (HK), Chinese Institute for Brain Research (CN), Institute of Atmospheric Physics (CN), University of Hong Kong (HK)
Climate action
Openalex Percentile: Top 0%
Remote Sensing in Agriculture
22.03
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