Categorizing natural disaster damage assessment using satellite-based geospatial techniques

Remote sensing of a natural disaster's damage offers an exciting backup and/or alternative to traditional means of on-site damage assessment. Although necessary for complete assessment of damage areas, ground-based damage surveys conducted in the aftermath of natural hazard passage can some...

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Main Authors: S. W. Myint, M. Yuan, R. S. Cerveny, C. Giri
Format: Article
Language:English
Published: Copernicus Publications 2008-07-01
Series:Natural Hazards and Earth System Sciences
Online Access:http://www.nat-hazards-earth-syst-sci.net/8/707/2008/nhess-8-707-2008.pdf
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author S. W. Myint
M. Yuan
R. S. Cerveny
C. Giri
author_facet S. W. Myint
M. Yuan
R. S. Cerveny
C. Giri
author_sort S. W. Myint
collection DOAJ
description Remote sensing of a natural disaster's damage offers an exciting backup and/or alternative to traditional means of on-site damage assessment. Although necessary for complete assessment of damage areas, ground-based damage surveys conducted in the aftermath of natural hazard passage can sometimes be potentially complicated due to on-site difficulties (e.g., interaction with various authorities and emergency services) and hazards (e.g., downed power lines, gas lines, etc.), the need for rapid mobilization (particularly for remote locations), and the increasing cost of rapid physical transportation of manpower and equipment. Satellite image analysis, because of its global ubiquity, its ability for repeated independent analysis, and, as we demonstrate here, its ability to verify on-site damage assessment provides an interesting new perspective and investigative aide to researchers. Using one of the strongest tornado events in US history, the 3 May 1999 Oklahoma City Tornado, as a case example, we digitized the tornado damage path and co-registered the damage path using pre- and post-Landsat Thematic Mapper image data to perform a damage assessment. We employed several geospatial approaches, specifically the Getis index, Geary's <i>C</i>, and two lacunarity approaches to categorize damage characteristics according to the original Fujita tornado damage scale (F-scale). Our results indicate strong relationships between spatial indices computed within a local window and tornado F-scale damage categories identified through the ground survey. Consequently, linear regression models, even incorporating just a single band, appear effective in identifying F-scale damage categories using satellite imagery. This study demonstrates that satellite-based geospatial techniques can effectively add spatial perspectives to natural disaster damages, and in particular for this case study, tornado damages.
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spelling doaj.art-93a8f0528e06436b89d58f29296478832022-12-21T18:28:28ZengCopernicus PublicationsNatural Hazards and Earth System Sciences1561-86331684-99812008-07-0184707719Categorizing natural disaster damage assessment using satellite-based geospatial techniquesS. W. MyintM. YuanR. S. CervenyC. GiriRemote sensing of a natural disaster's damage offers an exciting backup and/or alternative to traditional means of on-site damage assessment. Although necessary for complete assessment of damage areas, ground-based damage surveys conducted in the aftermath of natural hazard passage can sometimes be potentially complicated due to on-site difficulties (e.g., interaction with various authorities and emergency services) and hazards (e.g., downed power lines, gas lines, etc.), the need for rapid mobilization (particularly for remote locations), and the increasing cost of rapid physical transportation of manpower and equipment. Satellite image analysis, because of its global ubiquity, its ability for repeated independent analysis, and, as we demonstrate here, its ability to verify on-site damage assessment provides an interesting new perspective and investigative aide to researchers. Using one of the strongest tornado events in US history, the 3 May 1999 Oklahoma City Tornado, as a case example, we digitized the tornado damage path and co-registered the damage path using pre- and post-Landsat Thematic Mapper image data to perform a damage assessment. We employed several geospatial approaches, specifically the Getis index, Geary's <i>C</i>, and two lacunarity approaches to categorize damage characteristics according to the original Fujita tornado damage scale (F-scale). Our results indicate strong relationships between spatial indices computed within a local window and tornado F-scale damage categories identified through the ground survey. Consequently, linear regression models, even incorporating just a single band, appear effective in identifying F-scale damage categories using satellite imagery. This study demonstrates that satellite-based geospatial techniques can effectively add spatial perspectives to natural disaster damages, and in particular for this case study, tornado damages.http://www.nat-hazards-earth-syst-sci.net/8/707/2008/nhess-8-707-2008.pdf
spellingShingle S. W. Myint
M. Yuan
R. S. Cerveny
C. Giri
Categorizing natural disaster damage assessment using satellite-based geospatial techniques
Natural Hazards and Earth System Sciences
title Categorizing natural disaster damage assessment using satellite-based geospatial techniques
title_full Categorizing natural disaster damage assessment using satellite-based geospatial techniques
title_fullStr Categorizing natural disaster damage assessment using satellite-based geospatial techniques
title_full_unstemmed Categorizing natural disaster damage assessment using satellite-based geospatial techniques
title_short Categorizing natural disaster damage assessment using satellite-based geospatial techniques
title_sort categorizing natural disaster damage assessment using satellite based geospatial techniques
url http://www.nat-hazards-earth-syst-sci.net/8/707/2008/nhess-8-707-2008.pdf
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