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

Authors: Xiaomin Qiu*, Missouri State University, Shuo-Sheng Wu, Missouri State University
Topics: Hazards, Risks, and Disasters, Geographic Information Science and Systems, Remote Sensing
Keywords: sinkhole, hazard, mapping, DEMs
Session Type: Poster
Day: 4/11/2018
Start / End Time: 3:20 PM / 5:00 PM
Room: Napoleon Foyer/Common St. Corridor, Sheraton, 3rd Floor
Presentation File: No File Uploaded


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.

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