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...

Full description

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)
id EDOCUR2_2fcc606011d79c7080ff58c8c1ae98d2
oai_identifier_str oai:repository.urosario.edu.co:10336/27875
network_acronym_str EDOCUR2
network_name_str Repositorio EdocUR - U. Rosario
repository_id_str
spelling 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