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Performance evaluation of object-based and pixel-based building detection algorithms from very high spatial resolution imagery / Iman Khosravi in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 6 (June 2014)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 80 n° 6 (June 2014) . - pp 519 - 528 Titre : Performance evaluation of object-based and pixel-based building detection algorithms from very high spatial resolution imagery Type de document : Article/Communication Auteurs : Iman Khosravi, Auteur ; Mehdi Momeni, Auteur ; Maryam Rahnemoonfar, Auteur Année de publication : 2014 Article en page(s) : pp 519 - 528 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse comparative [Termes IGN] classification orientée objet [Termes IGN] classification pixellaire [Termes IGN] détection du bâti [Termes IGN] erreur de classification [Termes IGN] image à très haute résolution [Termes IGN] segmentation d'image Résumé : (Auteur) Building detection from remote sensed images is the main technique to monitor economic or environmental develop-ment of an area. Advanced Land Observing Satellite (alos) and SPOT data are reliable sources due to the limitation of weather, position, time, and other practical reasons. How-ever, to the best of our knowledge, algorithms proposed in the identification of buildings mostly aim only at images with very high spatial resolution or high spectral resolution. There are few algorithms for detecting buildings from ALOS and SPOT data. A built-up detection index (bdi) is proposed in this paper to automatically identify buildings from images with 10 meters resolution. It synthesizes morphological theory and normalized differential vegetation index (NDVl) to enhance buildings by suppressing vegetation. Four images of ALOS and SPOT are used to verify the efficiency, stability and ac-curacy of BDI. Experiments show that BDI is suitable to detect buildings from 10 meters resolution with reliable accuracy. Numéro de notice : A2014-291 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.80.6.519-528 En ligne : https://doi.org/10.14358/PERS.80.6.519-528 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=33194 [article]

An effective morphological index in automatic recognition of built-up area suitable for high spatial resolution images as ALOS and SPOT data / Bo Yu in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 6 (June 2014)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 80 n° 6 (June 2014) . - pp 529 - 536 Titre : An effective morphological index in automatic recognition of built-up area suitable for high spatial resolution images as ALOS and SPOT data Type de document : Article/Communication Auteurs : Bo Yu, Auteur ; Li Wang, Auteur ; Zheng Niu, Auteur ; Muhammad Shakir, Auteur Année de publication : 2014 Article en page(s) : pp 529 - 536 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] détection du bâti [Termes IGN] image ALOS [Termes IGN] image SPOT [Termes IGN] indice de détection [Termes IGN] morphologie mathématique [Termes IGN] Normalized Difference Vegetation Index Résumé : (Auteur) Building detection from remote sensed images is the main technique to monitor economic or environmental development of an area. Advanced Land Observing Satellite (alos) and SPOT data are reliable sources due to the limitation of weather, position, time, and other practical reasons. However, to the best of our knowledge, algorithms proposed in the identification of buildings mostly aim only at images with very high spatial resolution or high spectral resolution. There are few algorithms for detecting buildings from ALOS and SPOT data. A built-up detection index (BDI) is proposed in this paper to automatically identify buildings from images with 10 meters resolution. It synthesizes morphological theory and normalized differential vegetation index (NDVl) to enhance buildings by suppressing vegetation. Four images of ALOS and SPOT are used to verify the efficiency, stability and accuracy of BDI. Experiments show that BDI is suitable to detect buildings from 10 meters resolution with reliable accuracy. Numéro de notice : A2014-292 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.80.6.529-536 En ligne : https://doi.org/10.14358/PERS.80.6.529-536 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=33195 [article]

Annual crop type classification of the US great plains for 2000 to 20011 / Daniel M. Howard in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 6 (June 2014)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 80 n° 6 (June 2014) . - pp 537 - 549 Titre : Annual crop type classification of the US great plains for 2000 to 20011 Type de document : Article/Communication Auteurs : Daniel M. Howard, Auteur ; Bruce K. Wyllie, Auteur Année de publication : 2014 Article en page(s) : pp 537 - 549 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] classification à base de connaissances [Termes IGN] climatologie [Termes IGN] culture [Termes IGN] environnement [Termes IGN] modèle de géopotentiel [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] surveillance agricole Résumé : (Auteur) The purpose of this study was to increase the spatial and temporal availability of crop classification data. In this study, nearly 16.2 million crop observation points were used in the training of the US Great Plains classification tree crop type model (CTM). Each observation point was further defined by weekly Normalized Difference Vegetation Index, annual climate, and a number of other biogeophysical environmental characteristics. This study accounted for the most prevalent crop types in the region, including, corn, soybeans, winter wheat, spring wheat, cotton, sorghum, and alfalfa. Annual CTM crop maps of the US Great Plains were created for 2000 to 2011 at a spatial resolution of 250 meters. The CTM achieved an 87 percent classification success rate on 1.8 million obser-vation points that were withheld from model training. Product validation was performed on greater than 15,000 county records with a coefficient of determination of R2 = 0.76. Numéro de notice : A2014-293 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.80.6.537-549 En ligne : https://doi.org/10.14358/PERS.80.6.537-549 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=33196 [article]

Planar block adjustment and orthorectification of ZY-3 satellite images / Toyang Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 6 (June 2014)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 80 n° 6 (June 2014) . - pp 559 - 570 Titre : Planar block adjustment and orthorectification of ZY-3 satellite images Type de document : Article/Communication Auteurs : Toyang Wang, Auteur ; Guo Zhang, Auteur ; Deren Li, Auteur Année de publication : 2014 Article en page(s) : pp 559 - 570 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] 1:50.000 [Termes IGN] carte topographique [Termes IGN] compensation par bloc [Termes IGN] image ZiYuan-3 [Termes IGN] orthorectification automatique [Termes IGN] point d'appui [Termes IGN] précision du positionnement Résumé : (Auteur) For the problem of block adjustment for satellite images, which cannot be solved under conditions of weak geomet-ric convergence, this paper proposes a strategy that uses a planar block adjustment method to solve the orientation parameters of all satellite images, and then each satellite image is orthorectified. This strategy can ensure both the uniformity of the positioning accuracy and the strictness of the relative positions of the adjacent orthoimages. Tests of 139 panchromatic nadir images from the ZY-3 satellite show that by using only a small number of ground control points (GCPs), whose plane accuracy is 5 m, the plane accuracy of independent check points (iCPs) is better than 7 m after planar block adjustment. This accuracy meets the requirements for Chinese 1:50 000 topographic maps. Moreover, the precise-ness of tie points (TPs) in adjacent images is better than 0.5 pixels, so a seamless level in mosaic geometry is attained. Numéro de notice : A2014-294 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.80.6.559-570 En ligne : https://doi.org/10.14358/PERS.80.6.559-570 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=33197 [article]