A tool for rapid post-hurricane urban tree debris estimates using high resolution aerial imagery
Coastal communities in the southeast United States have regularly experienced severe hurricane impacts. To better facilitate recovery efforts in these communities following natural disasters, state and federal agencies must respond quickly with information regarding the extent and severity of hurric...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2012
- Institución:
- Universidad del Rosario
- Repositorio:
- Repositorio EdocUR - U. Rosario
- Idioma:
- eng
- OAI Identifier:
- oai:repository.urosario.edu.co:10336/27875
- Acceso en línea:
- https://doi.org/10.1016/j.jag.2011.10.009
https://repository.urosario.edu.co/handle/10336/27875
- Palabra clave:
- Hurricane debrisassessment
Edge detection
Color filtering
Urban forest management
- Rights
- License
- Restringido (Acceso a grupos específicos)
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Repositorio EdocUR - U. Rosario |
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b8420d3d-ae5e-4153-9ef6-a87a2a6e2bc9-10d92d82e-b44e-44e4-8078-67832bcce6d1-19ae99ce8-fc5b-408a-9ab0-eab12cb36c9e-1747ca8ab-fa0a-4501-87e6-903ae43bc644-1c0a2c37a-ed2c-442b-957b-a93788108155-10e1432a8-a298-4f21-a051-5ab80ca77cdc-12020-08-19T14:44:23Z2020-08-19T14:44:23Z2012-08-01Coastal communities in the southeast United States have regularly experienced severe hurricane impacts. To better facilitate recovery efforts in these communities following natural disasters, state and federal agencies must respond quickly with information regarding the extent and severity of hurricane damage and the amount of tree debris volume. A tool was developed to detect downed trees and debris volume to better aid disaster response efforts and tree debris removal. The tool estimates downed tree debris volume in hurricane affected urban areas using a Leica Airborne Digital Sensor (ADS40) and very high resolution digital images. The tool employs a Sobel edge detection algorithm combined with spectral information based on color filtering using 15 different statistical combinations of spectral bands. The algorithm identified downed tree edges based on contrasts between tree stems, grass, and asphalt and color filtering was then used to establish threshold values. Colors outside these threshold values were replaced and excluded from the detection processes. Results were overlaid and an “edge line” was placed where lines or edges from longer consecutive segments and color values within the threshold were met. Where two lines were paired within a very short distance in the scene a polygon was drawn automatically and, in doing so, downed tree stems were detected. Tree stem diameter–volume bulking factors were used to estimate post-hurricane tree debris volumes. Images following Hurricane Ivan in 2005 and Hurricane Ike in 2008 were used to assess the error of the tool by comparing downed tree counts and subsequent debris volume estimates with post-hurricane photo-interpreted downed tree counts and actual field measured estimates of downed tree debris volume. The errors associated with the use of the tool and potential applications are also presented.application/pdfhttps://doi.org/10.1016/j.jag.2011.10.009ISSN: 1569-8432EISSN: 0303-2434https://repository.urosario.edu.co/handle/10336/27875engElsevier556548International Journal of Applied Earth Observation and GeoinformationVol. 18International Journal of Applied Earth Observation and Geoinformation, ISSN:1569-8432;EISSN:0303-2434, Vol.18 (August, 2012); pp. 548-556https://www.sciencedirect.com/science/article/abs/pii/S0303243411001528Restringido (Acceso a grupos específicos)http://purl.org/coar/access_right/c_16ecInternational Journal of Applied Earth Observation and Geoinformationinstname:Universidad del Rosarioreponame:Repositorio Institucional EdocURHurricane debrisassessmentEdge detectionColor filteringUrban forest managementA tool for rapid post-hurricane urban tree debris estimates using high resolution aerial imageryUna herramienta para estimaciones rápidas de escombros de árboles urbanos después de un huracán utilizando imágenes aéreas de alta resoluciónarticleArtículohttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_6501Szantoi, ZoltanMalone, SparkleEscobedo, FranciscoMisas, OrlandoSmith, ScotDewitt, Bon10336/27875oai:repository.urosario.edu.co:10336/278752021-06-03 00:51:06.989https://repository.urosario.edu.coRepositorio institucional EdocURedocur@urosario.edu.co |
dc.title.spa.fl_str_mv |
A tool for rapid post-hurricane urban tree debris estimates using high resolution aerial imagery |
dc.title.TranslatedTitle.spa.fl_str_mv |
Una herramienta para estimaciones rápidas de escombros de árboles urbanos después de un huracán utilizando imágenes aéreas de alta resolución |
title |
A tool for rapid post-hurricane urban tree debris estimates using high resolution aerial imagery |
spellingShingle |
A tool for rapid post-hurricane urban tree debris estimates using high resolution aerial imagery Hurricane debrisassessment Edge detection Color filtering Urban forest management |
title_short |
A tool for rapid post-hurricane urban tree debris estimates using high resolution aerial imagery |
title_full |
A tool for rapid post-hurricane urban tree debris estimates using high resolution aerial imagery |
title_fullStr |
A tool for rapid post-hurricane urban tree debris estimates using high resolution aerial imagery |
title_full_unstemmed |
A tool for rapid post-hurricane urban tree debris estimates using high resolution aerial imagery |
title_sort |
A tool for rapid post-hurricane urban tree debris estimates using high resolution aerial imagery |
dc.subject.keyword.spa.fl_str_mv |
Hurricane debrisassessment Edge detection Color filtering Urban forest management |
topic |
Hurricane debrisassessment Edge detection Color filtering Urban forest management |
description |
Coastal communities in the southeast United States have regularly experienced severe hurricane impacts. To better facilitate recovery efforts in these communities following natural disasters, state and federal agencies must respond quickly with information regarding the extent and severity of hurricane damage and the amount of tree debris volume. A tool was developed to detect downed trees and debris volume to better aid disaster response efforts and tree debris removal. The tool estimates downed tree debris volume in hurricane affected urban areas using a Leica Airborne Digital Sensor (ADS40) and very high resolution digital images. The tool employs a Sobel edge detection algorithm combined with spectral information based on color filtering using 15 different statistical combinations of spectral bands. The algorithm identified downed tree edges based on contrasts between tree stems, grass, and asphalt and color filtering was then used to establish threshold values. Colors outside these threshold values were replaced and excluded from the detection processes. Results were overlaid and an “edge line” was placed where lines or edges from longer consecutive segments and color values within the threshold were met. Where two lines were paired within a very short distance in the scene a polygon was drawn automatically and, in doing so, downed tree stems were detected. Tree stem diameter–volume bulking factors were used to estimate post-hurricane tree debris volumes. Images following Hurricane Ivan in 2005 and Hurricane Ike in 2008 were used to assess the error of the tool by comparing downed tree counts and subsequent debris volume estimates with post-hurricane photo-interpreted downed tree counts and actual field measured estimates of downed tree debris volume. The errors associated with the use of the tool and potential applications are also presented. |
publishDate |
2012 |
dc.date.created.spa.fl_str_mv |
2012-08-01 |
dc.date.accessioned.none.fl_str_mv |
2020-08-19T14:44:23Z |
dc.date.available.none.fl_str_mv |
2020-08-19T14:44:23Z |
dc.type.eng.fl_str_mv |
article |
dc.type.coarversion.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_6501 |
dc.type.spa.spa.fl_str_mv |
Artículo |
dc.identifier.doi.none.fl_str_mv |
https://doi.org/10.1016/j.jag.2011.10.009 |
dc.identifier.issn.none.fl_str_mv |
ISSN: 1569-8432 EISSN: 0303-2434 |
dc.identifier.uri.none.fl_str_mv |
https://repository.urosario.edu.co/handle/10336/27875 |
url |
https://doi.org/10.1016/j.jag.2011.10.009 https://repository.urosario.edu.co/handle/10336/27875 |
identifier_str_mv |
ISSN: 1569-8432 EISSN: 0303-2434 |
dc.language.iso.spa.fl_str_mv |
eng |
language |
eng |
dc.relation.citationEndPage.none.fl_str_mv |
556 |
dc.relation.citationStartPage.none.fl_str_mv |
548 |
dc.relation.citationTitle.none.fl_str_mv |
International Journal of Applied Earth Observation and Geoinformation |
dc.relation.citationVolume.none.fl_str_mv |
Vol. 18 |
dc.relation.ispartof.spa.fl_str_mv |
International Journal of Applied Earth Observation and Geoinformation, ISSN:1569-8432;EISSN:0303-2434, Vol.18 (August, 2012); pp. 548-556 |
dc.relation.uri.spa.fl_str_mv |
https://www.sciencedirect.com/science/article/abs/pii/S0303243411001528 |
dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_16ec |
dc.rights.acceso.spa.fl_str_mv |
Restringido (Acceso a grupos específicos) |
rights_invalid_str_mv |
Restringido (Acceso a grupos específicos) http://purl.org/coar/access_right/c_16ec |
dc.format.mimetype.none.fl_str_mv |
application/pdf |
dc.publisher.spa.fl_str_mv |
Elsevier |
dc.source.spa.fl_str_mv |
International Journal of Applied Earth Observation and Geoinformation |
institution |
Universidad del Rosario |
dc.source.instname.none.fl_str_mv |
instname:Universidad del Rosario |
dc.source.reponame.none.fl_str_mv |
reponame:Repositorio Institucional EdocUR |
repository.name.fl_str_mv |
Repositorio institucional EdocUR |
repository.mail.fl_str_mv |
edocur@urosario.edu.co |
_version_ |
1814167742988681216 |