AUTOMATIC BUILDING DAMAGE DETECTION METHOD USING HIGH-RESOLUTION REMOTE SENSING IMAGES AND 3D GIS MODEL
In this paper, a novel approach of building damaged detection is proposed using high resolution remote sensing images and 3D GIS-Model data. Traditional building damage detection method considers to detect damaged building due to earthquake, but little attention has been paid to analyze various buil...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
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Copernicus Publications
2016-06-01
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Series: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
Online Access: | http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/III-8/43/2016/isprs-annals-III-8-43-2016.pdf |
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author | J. Tu H. Sui W. Feng Z. Song |
author_facet | J. Tu H. Sui W. Feng Z. Song |
author_sort | J. Tu |
collection | DOAJ |
description | In this paper, a novel approach of building damaged detection is proposed using high resolution remote sensing images and 3D GIS-Model data. Traditional building damage detection method considers to detect damaged building due to earthquake, but little attention has been paid to analyze various building damaged types(e.g., trivial damaged, severely damaged and totally collapsed.) Therefore, we want to detect the different building damaged type using 2D and 3D feature of scenes because the real world we live in is a 3D space. The proposed method generalizes that the image geometric correction method firstly corrects the post-disasters remote sensing image using the 3D GIS model or RPC parameters, then detects the different building damaged types using the change of the height and area between the pre- and post-disasters and the texture feature of post-disasters. The results, evaluated on a selected study site of the Beichuan earthquake ruins, Sichuan, show that this method is feasible and
effective in building damage detection. It has also shown that the proposed method is easily applicable and well suited for rapid damage assessment after natural disasters. |
first_indexed | 2024-04-12T01:29:11Z |
format | Article |
id | doaj.art-08bcc48aa6124b4ba2f005c2ee788e6c |
institution | Directory Open Access Journal |
issn | 2194-9042 2194-9050 |
language | English |
last_indexed | 2024-04-12T01:29:11Z |
publishDate | 2016-06-01 |
publisher | Copernicus Publications |
record_format | Article |
series | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
spelling | doaj.art-08bcc48aa6124b4ba2f005c2ee788e6c2022-12-22T03:53:32ZengCopernicus PublicationsISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences2194-90422194-90502016-06-01III-8435010.5194/isprs-annals-III-8-43-2016AUTOMATIC BUILDING DAMAGE DETECTION METHOD USING HIGH-RESOLUTION REMOTE SENSING IMAGES AND 3D GIS MODELJ. Tu0H. Sui1W. Feng2Z. Song3State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 430079 Wuhan, ChinaState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 430079 Wuhan, ChinaState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 430079 Wuhan, ChinaState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 430079 Wuhan, ChinaIn this paper, a novel approach of building damaged detection is proposed using high resolution remote sensing images and 3D GIS-Model data. Traditional building damage detection method considers to detect damaged building due to earthquake, but little attention has been paid to analyze various building damaged types(e.g., trivial damaged, severely damaged and totally collapsed.) Therefore, we want to detect the different building damaged type using 2D and 3D feature of scenes because the real world we live in is a 3D space. The proposed method generalizes that the image geometric correction method firstly corrects the post-disasters remote sensing image using the 3D GIS model or RPC parameters, then detects the different building damaged types using the change of the height and area between the pre- and post-disasters and the texture feature of post-disasters. The results, evaluated on a selected study site of the Beichuan earthquake ruins, Sichuan, show that this method is feasible and effective in building damage detection. It has also shown that the proposed method is easily applicable and well suited for rapid damage assessment after natural disasters.http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/III-8/43/2016/isprs-annals-III-8-43-2016.pdf |
spellingShingle | J. Tu H. Sui W. Feng Z. Song AUTOMATIC BUILDING DAMAGE DETECTION METHOD USING HIGH-RESOLUTION REMOTE SENSING IMAGES AND 3D GIS MODEL ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
title | AUTOMATIC BUILDING DAMAGE DETECTION METHOD USING HIGH-RESOLUTION REMOTE SENSING IMAGES AND 3D GIS MODEL |
title_full | AUTOMATIC BUILDING DAMAGE DETECTION METHOD USING HIGH-RESOLUTION REMOTE SENSING IMAGES AND 3D GIS MODEL |
title_fullStr | AUTOMATIC BUILDING DAMAGE DETECTION METHOD USING HIGH-RESOLUTION REMOTE SENSING IMAGES AND 3D GIS MODEL |
title_full_unstemmed | AUTOMATIC BUILDING DAMAGE DETECTION METHOD USING HIGH-RESOLUTION REMOTE SENSING IMAGES AND 3D GIS MODEL |
title_short | AUTOMATIC BUILDING DAMAGE DETECTION METHOD USING HIGH-RESOLUTION REMOTE SENSING IMAGES AND 3D GIS MODEL |
title_sort | automatic building damage detection method using high resolution remote sensing images and 3d gis model |
url | http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/III-8/43/2016/isprs-annals-III-8-43-2016.pdf |
work_keys_str_mv | AT jtu automaticbuildingdamagedetectionmethodusinghighresolutionremotesensingimagesand3dgismodel AT hsui automaticbuildingdamagedetectionmethodusinghighresolutionremotesensingimagesand3dgismodel AT wfeng automaticbuildingdamagedetectionmethodusinghighresolutionremotesensingimagesand3dgismodel AT zsong automaticbuildingdamagedetectionmethodusinghighresolutionremotesensingimagesand3dgismodel |