Sinkhole Risk Assessment based on Morphological, Imagery, and Contextual Attributes Derived from GIS and Remotes Sensing Data

主题:  Sinkhole Risk Assessment based on GIS and Remotes Sensing Data

主讲人:  邱晓敏

地点:  松江校区4号学院楼3158室

时间:  2018-01-08 10:00:00

组织单位:   环境科学与工程学院

主讲人简介：邱晓敏，2006年于德克萨斯州圣马可斯密苏里州大学获得博士学位，现为美国密苏里州大学副教授，密苏里州立大学自然与应用科学学院副院长，研究主要涵盖3S在环境领域中的应用，环境数据可视化，环境风险与健康等，先后发表出版论文、专著20多篇(部)。 

内容摘要 :This study proposes robust methodology for extracting and assessing sinkholes based on attributes that can be efficiently derived from common GIS and remotes sensing data. We first applied a sequence of GIS operations to extract topographic depressions,or sinks, from terrain DEMs (digital elevation models). Then, three types of sink attributes, including morphological attributes related to the size,shape, and depth of the sinks, imagery attributes of impervious surface percentage,vegetation index, and seasonal water conditions for the sinks, and contextual attributes describing the land use, population density, and hydrological flow accumulation for the sinks,are derived from data of DEMs, aerial photos, land parcels, and census population. Lastly, potential sinkhole risks are assessed by the sink attributes. The proposed computerized risk assessment will be valuable for supporting further field-based assessment and verification of the established sinkhole records.

报告语言：中文