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

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

主講人:  邱曉敏

地點:  松江校區4號沐鸣2樓3158室

時間:  2018-01-08 10:00:00

組織單位:   沐鸣2官网

主講人簡介：邱曉敏，2006年於德克薩斯州聖馬可斯密蘇裏州大學獲得博士學位🥒，現為美國密蘇裏州大學副教授🧚‍♂️，密蘇裏州立大學自然與應用科學沐鸣2副院長🔁，研究主要涵蓋3S在環境領域中的應用，環境數據可視化，環境風險與健康等，先後發表出版論文💃🏽、專著20多篇(部)。 

內容摘要 :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.

報告語言：中文