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Empowering fall webworm surveillance with mobile phone-based community monitoring: a case study in northern China  ( SCI-EXPANDED收录)   被引量:1

文献类型:期刊文献

英文题名:Empowering fall webworm surveillance with mobile phone-based community monitoring: a case study in northern China

作者:Wang, Chengbo[1] Qiao, Yanyou[1] Wu, Honggan[2] Chang, Yuanfei[1] Shi, Muyao[1]

第一作者:Wang, Chengbo

通信作者:Wang, CB[1]

机构:[1]Chinese Acad Sci, Inst Remote Sensing & Digital Earth, 20 Datun Rd, Beijing 100101, Peoples R China;[2]Chinese Acad Forestry, Res Inst Forest Resource Informat Tech, Xiangshan Rd, Beijing 100091, Peoples R China

年份:2016

卷号:27

期号:6

起止页码:1407-1414

外文期刊名:JOURNAL OF FORESTRY RESEARCH

收录:;Scopus(收录号:2-s2.0-84968531628);WOS:【SCI-EXPANDED(收录号:WOS:000386357900022)】;

基金:This research was supported by National Science and Technology Major Projects of China (21-Y30B05-9001-13/15).

语种:英文

外文关键词:Forest pest monitoring; Mobile phone; Community monitoring; Hyphantria cunea Drury; Field survey

摘要:Recent advances in information and communication technologies, such as mobile Internet and smartphones, have created new paradigms for participatory environment monitoring. The ubiquitous mobile phones with capabilities such as a global positioning system, camera, and network access, offer opportunities to establish distributed monitoring networks that can perform a wide range of measurements for a landscape. This study examined the potential of mobile phone-based community monitoring of fall webworm (Hyphantria cunea Drury). We built a prototype of a participatory fall webworm monitoring system based on mobile devices that streamlined data collection, transmission, and visualization. We also assessed the accuracy and reliability of the data collected by the local community. The system performance was evaluated at the Ziya commune of Tianjin municipality in northern China, where fall webworm infestation has occurred. The local community provided data with accuracy comparable to expert measurements (Willmott's index of agreement > 0.85). Measurements by the local community effectively complemented remote sensing images in both temporal and spatial resolution.

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