caa a22 4500 445300418 CHVBK 20180317142555.0 cr unu---uuuuu 170323e20101201xx s 000 0 eng 10.1007/s11430-010-4122-9 doi (NATIONALLICENCE)springer-10.1007/s11430-010-4122-9 Spatial prediction and analysis of Himalayan marmot plague natural epidemic foci in China based on HJ-1 satellite data [Elektronische Daten] [MengXu Gao, XiaoWen Li, ChunXiang Cao, Hao Zhang, Qun Li, Hang Zhou, QiSheng He, Min Xu, Jian Zhao, Sheng Zheng, Wei Chen] Plague, caused by the gram-negative bacterium Yersinia pestis, is a serious and rapidly progressing illness in humans that can be fatal if not treated effectively. The Qinghai-Tibet Plateau is the largest area of natural Himalayan marmot (Marmota himalayana) plague foci in China and covers more than 630000 km2. Akesai County in Gansu Province is a part of this natural focus of plague and was chosen as a study area. Our study used an ecological niche modeling (ENM) approach to predict the potential distribution of the Himalayan marmot. Environment and Disaster Monitor Satellite (HJ-1) data was used to investigate environment factors that affect plague host animal activity. Host animal point data from active surveillance was combined with environmental variables from the HJ-1 satellite and other databases, and the models of the potential distribution of Himalayan marmot were produced with the Genetic Algorithm for Rule-Set Production (GARP). The probability of marmot presence was divided into 0-5%, 5%-20%, 20%-40%, 40%-80%, and 80%-100% subgroups. Areas with 80%-100% probability exhibited the greatest potential for the presence of Himalayan marmot. According to the predicted potential distribution of Himalayan marmot in the study area, active surveillance of plague hosts and plague control and prevention could be more efficient. Science China Press and Springer-Verlag Berlin Heidelberg, 2010 Himalayan marmot nationallicence plague nationallicence spatial prediction nationallicence GARP nationallicence HJ-1 satellite nationallicence Gao MengXu State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, 100101, Beijing, China aut Li XiaoWen State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, 100101, Beijing, China aut Cao ChunXiang State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, 100101, Beijing, China aut Zhang Hao State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, 100101, Beijing, China aut Li Qun Office for Disease Control and Emergency Response, Chinese Center for Disease Control and Prevention, 102206, Beijing, China aut Zhou Hang Office for Disease Control and Emergency Response, Chinese Center for Disease Control and Prevention, 102206, Beijing, China aut He QiSheng State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, 100101, Beijing, China aut Xu Min State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, 100101, Beijing, China aut Zhao Jian State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, 100101, Beijing, China aut Zheng Sheng State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, 100101, Beijing, China aut Chen Wei State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, 100101, Beijing, China aut Science China Earth Sciences SP Science China Press 53(2010-12-01), 8-15 1674-7313 53<8 2010 53 11430 https://doi.org/10.1007/s11430-010-4122-9 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11430-010-4122-9 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Gao MengXu State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, 100101, Beijing, China aut NATIONALLICENCE 700 1- Li XiaoWen State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, 100101, Beijing, China aut NATIONALLICENCE 700 1- Cao ChunXiang State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, 100101, Beijing, China aut NATIONALLICENCE 700 1- Zhang Hao State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, 100101, Beijing, China aut NATIONALLICENCE 700 1- Li Qun Office for Disease Control and Emergency Response, Chinese Center for Disease Control and Prevention, 102206, Beijing, China aut NATIONALLICENCE 700 1- Zhou Hang Office for Disease Control and Emergency Response, Chinese Center for Disease Control and Prevention, 102206, Beijing, China aut NATIONALLICENCE 700 1- He QiSheng State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, 100101, Beijing, China aut NATIONALLICENCE 700 1- Xu Min State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, 100101, Beijing, China aut NATIONALLICENCE 700 1- Zhao Jian State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, 100101, Beijing, China aut NATIONALLICENCE 700 1- Zheng Sheng State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, 100101, Beijing, China aut NATIONALLICENCE 700 1- Chen Wei State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, 100101, Beijing, China aut NATIONALLICENCE 773 0- Science China Earth Sciences SP Science China Press 53(2010-12-01), 8-15 1674-7313 53<8 2010 53 11430 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer