The Quantitative Estimation of Grazing Intensity on the Zoige Plateau Based on the Space-Air-Ground Integrated Monitoring Technology

doi:10.3390/rs12091399

	The Quantitative Estimation of Grazing Intensity on the Zoige Plateau Based on the Space-Air-Ground Integrated Monitoring Technology
	Lei, Guangbin 2; Li, Ainong 2; Zhang, Zhengjian 2,3; Bian, Jinhu 2; Hu, Guyue 2,3; Wang, Changbo 2,3; Nan, Xi 2; Wang, Jiyan 4; Tan, Jianbo 1; Liao, Xiaohan 5
刊名	REMOTE SENSING
	2020-05-01
卷号	12 期号:9 页码:21
关键词	grazing intensity space-air-ground integrated monitoring unmanned aerial vehicle (UAV) trajectory data animal husbandry remote sensing
DOI	10.3390/rs12091399
通讯作者	Li, Ainong(ainongli@imde.ac.cn) ; Liao, Xiaohan(liaoxh@igsnrr.ac.cn)
英文摘要	Grazing intensity (GI) is an important indicator for grazing situations in pastoral areas. However, it has been difficult to be observed directly in the field, due to the randomness and dynamics of the grazing behavior of livestock. Consequently, the lack of actual GI information has become a common issue in studies on quantitatively estimating GI. In this paper, a novel quantitative estimation method is proposed based on the Space-Air-Ground integrated monitoring technology. It systematically integrates GPS tracking technology, Unmanned Aerial Vehicle (UAV) observation technology, and satellite remote sensing technology. Taking Xiangdong Village on the Zoige Plateau as a study area, the trajectory data and UAV images were acquired by the GPS tracking experiments and UAV observation experiments, respectively. The GI at paddock scale (PGI) was then generated with the Kernel Density Estimation (KDE) algorithm and the above data. Taking the generated PGI as training data, an estimation model of GI at region scale (RGI) was constructed by using the time-series satellite remote sensing images and random forest regression algorithm. Finally, the time-series RGI data with a spatial resolution of 10 m in Xiangdong Village were produced by the above model. The accuracy assessment demonstrated that the generated time-series RGI data could reflect the spatial-temporal heterogeneity of actual GI, with a mean absolute error of 0.9301 and r(2) of 0. 8573. The proposed method provides a new idea for generating the actual GI on the ground and the time-series RGI data. This study also highlights the feasibility and potential of using the Space-Air-Ground integrated monitoring technology to generate time-series RGI data with high spatial resolution. The generated time-series RGI data would provide data support for the formulation of policies and plans related to the sustainable development of animal husbandry.
资助项目	National Natural Science Foundation project of China[41701433] ; National Natural Science Foundation project of China[41701430] ; National Natural Science Foundation project of China[41701432] ; National Natural Science Foundation project of China[41571373] ; Key Deployment Project of the Chinese Academy of Sciences[KFZD-SW-319-04] ; National Key Research and Development Program of China[2016YFA0600103] ; National Key Research and Development Program of China[2016YFC0500201-06] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDA19030303] ; CAS Light ofWest China Program ; 135 Strategic Program of the Institute of Mountain Hazards and Environment, CAS[SDS-135-1708]
WOS关键词	XILINGOL STEPPE REGION ; INNER-MONGOLIA ; HJ-1A/B CONSTELLATION ; GRASSLAND ; MODEL ; GPS ; SYSTEMS ; LANDSAT ; IMAGES ; CATTLE
WOS研究方向	Remote Sensing
语种	英语
出版者	MDPI
WOS记录号	WOS:000543394000046
资助机构	National Natural Science Foundation project of China ; Key Deployment Project of the Chinese Academy of Sciences ; National Key Research and Development Program of China ; Strategic Priority Research Program of the Chinese Academy of Sciences ; CAS Light ofWest China Program ; 135 Strategic Program of the Institute of Mountain Hazards and Environment, CAS
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/162388]
专题	中国科学院地理科学与资源研究所
通讯作者	Li, Ainong; Liao, Xiaohan
作者单位	1.Changsha Univ Sci & Technol, Sch Traff & Transportat Engn, Changsha 410114, Peoples R China 2.Chinese Acad Sci, Res Ctr Digital Mt & Remote Sensing Applicat, Inst Mt Hazards & Environm, Chengdu 610041, Peoples R China 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 4.Southwest Petr Univ, Sch Civil Engn & Architecture, Chengdu 610500, Peoples R China 5.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
推荐引用方式 GB/T 7714	Lei, Guangbin,Li, Ainong,Zhang, Zhengjian,et al. The Quantitative Estimation of Grazing Intensity on the Zoige Plateau Based on the Space-Air-Ground Integrated Monitoring Technology[J]. REMOTE SENSING,2020,12(9):21.
APA	Lei, Guangbin.,Li, Ainong.,Zhang, Zhengjian.,Bian, Jinhu.,Hu, Guyue.,...&Liao, Xiaohan.(2020).The Quantitative Estimation of Grazing Intensity on the Zoige Plateau Based on the Space-Air-Ground Integrated Monitoring Technology.REMOTE SENSING,12(9),21.
MLA	Lei, Guangbin,et al."The Quantitative Estimation of Grazing Intensity on the Zoige Plateau Based on the Space-Air-Ground Integrated Monitoring Technology".REMOTE SENSING 12.9(2020):21.