Flood Monitoring and Damage Assessment in the Mid-Atlantic Region using Landsat Analysis Ready Data (ARD)

Authors: Yiwen Wu, New Jersey Institute of Technology, Huiran Jin*, New Jersey Institute Of Technology, Laramie V. Potts, New Jersey Institute of Technology
Topics: Hazards, Risks, and Disasters, Remote Sensing, Spatial Analysis & Modeling
Keywords: Floods, Inundation, Damage assessment, Landsat ARD
Session Type: Poster
Day: 4/13/2018
Start / End Time: 5:20 PM / 7:00 PM
Room: Napoleon Foyer/Common St. Corridor, Sheraton, 3rd Floor
Presentation File: No File Uploaded


Floods from storm surges and prolonged heavy precipitation frequently affect the Mid-Atlantic region along the northeast coast of the United States. Inundation brought by major meteorological events, such as Hurricane Irene in 2011 and Hurricane Sandy in 2012, breached banks of many rivers and streams in this region, leading to severe beach erosion and extensive damage to agriculture, private properties and public infrastructure. Impacts of flooding on land surface vary in time and space, largely dependent on land-cover/land-use (LCLU) type and proximity to the location of landfall. This research focuses on examining the response of different LCLU types in the coastal areas and of several major rivers in the Mid-Atlantic region to the tropical storms and hurricanes that occurred from 2001 to 2017. Time-series analysis is performed on the recently released Landsat Analysis Ready Data (ARD). Specifically, seventeen years of Landsat-5 TM, Landsat-7 ETM+, and Landsat-8 OLI data archived by Landsat ARD are processed over 32 tiles encompassing the study area, and a set of subpixel water fraction (SWF) maps are generated indicating the percent of surface water within each Landsat pixel. Through comparison of paired SWF maps derived before and after each flood event, inundated areas are identified with respect to different LCLU types. Damage assessment is then conducted by linking satellite imagery to physical (e.g. precipitation) and socioeconomic (e.g. property loss, rehabilitation cost) data on record. The approach developed in this study has the potential to assist in the establishment of a more efficient flood-oriented regional response framework.

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