The Quantitative Estimation of Grazing Intensity on the Zoige Plateau Based on the Space-Air-Ground Integrated Monitoring Technology
文献类型:期刊论文
作者 | Lei, Guangbin2; Li, Ainong2; Zhang, Zhengjian2,3; Bian, Jinhu2; Hu, Guyue2,3; Wang, Changbo2,3; Nan, Xi2; Wang, Jiyan1; Tan, Jianbo4; Liao, Xiaohan5 |
刊名 | REMOTE SENSING
![]() |
出版日期 | 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. |
WOS关键词 | XILINGOL STEPPE REGION ; INNER-MONGOLIA ; HJ-1A/B CONSTELLATION ; GRASSLAND ; MODEL ; GPS ; SYSTEMS ; LANDSAT ; IMAGES ; CATTLE |
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研究方向 | Remote Sensing |
语种 | 英语 |
WOS记录号 | WOS:000543394000046 |
出版者 | MDPI |
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 |
源URL | [http://ir.imde.ac.cn/handle/131551/35165] ![]() |
专题 | 成都山地灾害与环境研究所_数字山地与遥感应用中心 |
通讯作者 | Li, Ainong; Liao, Xiaohan; Li Ainong |
作者单位 | 1.Southwest Petr Univ, Sch Civil Engn & Architecture, Chengdu 610500, 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.Changsha Univ Sci & Technol, Sch Traff & Transportat Engn, Changsha 410114, 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.,...&Bian Jinhu.(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. |
入库方式: OAI收割
来源:成都山地灾害与环境研究所
浏览0
下载0
收藏0
其他版本
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。