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Fusion of airborne laserscanning point clouds and images for supervised and unsupervised scene classification / Markus Gerke in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)
[article]
Titre : Fusion of airborne laserscanning point clouds and images for supervised and unsupervised scene classification Type de document : Article/Communication Auteurs : Markus Gerke, Auteur ; Jing Xiao, Auteur Année de publication : 2014 Article en page(s) : pp 78 - 92 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] champ aléatoire de Markov
[Termes IGN] classification dirigée
[Termes IGN] classification non dirigée
[Termes IGN] classification par arbre de décision
[Termes IGN] conflation
[Termes IGN] densification
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] semis de points
[Termes IGN] toit
[Termes IGN] voxelRésumé : (Auteur) Automatic urban object detection from airborne remote sensing data is essential to process and efficiently interpret the vast amount of airborne imagery and Laserscanning (ALS) data available today. This paper combines ALS data and airborne imagery to exploit both: the good geometric quality of ALS and the spectral image information to detect the four classes buildings, trees, vegetated ground and sealed ground. A new segmentation approach is introduced which also makes use of geometric and spectral data during classification entity definition. Geometric, textural, low level and mid level image features are assigned to laser points which are quantified into voxels. The segment information is transferred to the voxels and those clusters of voxels form the entity to be classified. Two classification strategies are pursued: a supervised method, using Random Trees and an unsupervised approach, embedded in a Markov Random Field framework and using graph-cuts for energy optimization. A further contribution of this paper concerns the image-based point densification for building roofs which aims to mitigate the accuracy problems related to large ALS point spacing. Results for the ISPRS benchmark test data show that to rely on color information to separate vegetation from non-vegetation areas does mostly lead to good results, but in particular in shadow areas a confusion between classes might occur. The unsupervised classification strategy is especially sensitive in this respect. As far as the point cloud densification is concerned, we observe similar sensitivity with respect to color which makes some planes to be missed out, or false detections still remain. For planes where the densification is successful we see the expected enhancement of the outline. Numéro de notice : A2014-014 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.10.011 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.10.011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32919
in ISPRS Journal of photogrammetry and remote sensing > vol 87 (January 2014) . - pp 78 - 92[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2014011 RAB Revue Centre de documentation En réserve L003 Disponible Hyperspectral image classification using nearest feature line embedding approach / Yang-Lang Chang in IEEE Transactions on geoscience and remote sensing, vol 52 n° 1 tome 1 (January 2014)
[article]
Titre : Hyperspectral image classification using nearest feature line embedding approach Type de document : Article/Communication Auteurs : Yang-Lang Chang, Auteur ; Jan-Nan Liu, Auteur ; Chin-Chuan Han, Auteur ; Ying-Nong Chen, Auteur Année de publication : 2014 Article en page(s) : pp 278 - 287 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] analyse discriminante
[Termes IGN] classification barycentrique
[Termes IGN] classification dirigée
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] image AVIRIS
[Termes IGN] image hyperspectrale
[Termes IGN] image MASTER
[Termes IGN] Indiana (Etats-Unis)
[Termes IGN] occupation du sol
[Termes IGN] réduction géométriqueRésumé : (Auteur) Eigenspace projection methods are widely used for feature extraction from hyperspectral images (HSI) for the classification of land cover. Projection transformation is used to reduce higher dimensional feature vectors to lower dimensional vectors for more accurate classification of land cover types. In this paper, a nearest feature line embedding (NFLE) transformation is proposed for the dimension reduction (DR) of an HSI. The NFL measurement is embedded in the transformation during the discriminant analysis phase, instead of the matching phase. Three factors, including class separability, neighborhood structure preservation, and NFL measurement, are considered simultaneously to determine an effective and discriminating transformation in the eigenspaces for land cover classification. Three state-of-the-art classifiers, the nearest-neighbor, support vector machine, and NFL classifiers, were used to classify the reduced features. The proposed NFLE transformation is compared with different feature extraction approaches and evaluated using two benchmark data sets, the MASTER set at Au-Ku and the AVIRIS set at Northwest Tippecanoe County. The experimental results demonstrate that the NFLE approach is effective for DR in land cover classification in the field of Earth remote sensing. Numéro de notice : A2014-036 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2238635 En ligne : https://doi.org/10.1109/TGRS.2013.2238635 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32941
in IEEE Transactions on geoscience and remote sensing > vol 52 n° 1 tome 1 (January 2014) . - pp 278 - 287[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2014011A RAB Revue Centre de documentation En réserve L003 Disponible A unified framework for land-cover database update and enrichment using satellite imagery / Adrien Gressin (2014)
Titre : A unified framework for land-cover database update and enrichment using satellite imagery Type de document : Article/Communication Auteurs : Adrien Gressin , Auteur ; Nicole Vincent, Auteur ; Clément Mallet , Auteur ; Nicolas Paparoditis , Auteur Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2014 Conférence : ICIP 2014, 21st IEEE International Conference on Image Processing 27/10/2014 30/10/2014 Paris France Proceedings IEEE Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] base de données d'occupation du sol
[Termes IGN] classification dirigée
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] classification semi-dirigée
[Termes IGN] découverte de connaissances
[Termes IGN] image à très haute résolution
[Termes IGN] image Pléiades-HR
[Termes IGN] mise à jour de base de donnéesRésumé : (auteur) 2D land-cover databases (LC-DB) have been established at various levels (global, national or regional scales), various spatial samplings and for various themes of interest (forest, agriculture, urban areas, etc.). However, they exhibit many flaws (limited geometric accuracy, low coverage) and require to be updated with automatic algorithms. Very High Reso-lution satellite imagery offers a suitable solution for setting up such on-purpose algorithms, and a large body of litera-ture has tackled this topic. This paper proposes a framework that is able to deal with both LC-DB update of any kind and their enrichment in case of incomplete DB. The supervised classification-based solution integrates an efficient learning strategy that allows to capture the heterogeneity of the ap-pearances of the various themes of interest. The proposed framework is favorably compared with two state-of-the-art methods, on a reconstructed dataset, composed of sub-metric satellite image patches. Numéro de notice : C2014-032 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE/INFORMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/ICIP.2014.7026024 Date de publication en ligne : 29/01/2015 En ligne : https://doi.org/10.1109/ICIP.2014.7026024 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92056 Documents numériques
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A unified framework for land-cover... - pdf auteurAdobe Acrobat PDF A parcel shape index for use in land consolidation planning / Demetris Demetriou in Transactions in GIS, vol 17 n° 6 (December 2013)
[article]
Titre : A parcel shape index for use in land consolidation planning Type de document : Article/Communication Auteurs : Demetris Demetriou, Auteur ; Linda M. See, Auteur ; John Stillwell, Auteur Année de publication : 2013 Article en page(s) : pp 861 - 882 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] aide à la décision
[Termes IGN] Chypre
[Termes IGN] classification dirigée
[Termes IGN] forme caractéristique
[Termes IGN] index spatial
[Termes IGN] mesure géométrique
[Termes IGN] parcelle agricoleRésumé : (Auteur) Area shape analysis has been a subject of focus for research in geography and other disciplines for many years. However, existing area shape indices present significant weaknesses for the analysis of land parcels in an agricultural context as they do not measure shape in an appropriate, reliable or explicit manner. This article presents a new parcel shape index (PSI) which integrates six geometric parameters through multi-attribute decision-making, combined with value functions for parameter standardization. The superior performance of the new PSI in relation to three existing indices is demonstrated through a case study area in Cyprus. The methodology can be applied in other contexts aimed at assessing the quality of a particular shape compared to an optimum. Numéro de notice : A2013-673 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/j.1467-9671.2012.01371.x Date de publication en ligne : 05/02/2013 En ligne : https://doi.org/10.1111/j.1467-9671.2012.01371.x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32809
in Transactions in GIS > vol 17 n° 6 (December 2013) . - pp 861 - 882[article]Landscape metrics for analysing urbanization-induced land use and land cover changes / Hua Liu in Geocarto international, vol 28 n° 7-8 (November - December 2013)
[article]
Titre : Landscape metrics for analysing urbanization-induced land use and land cover changes Type de document : Article/Communication Auteurs : Hua Liu, Auteur ; Qihao Weng, Auteur Année de publication : 2013 Article en page(s) : pp 582 - 593 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse diachronique
[Termes IGN] changement d'occupation du sol
[Termes IGN] changement d'utilisation du sol
[Termes IGN] classification dirigée
[Termes IGN] image Landsat-TM
[Termes IGN] image Terra-ASTER
[Termes IGN] Indianapolis
[Termes IGN] métrique
[Termes IGN] prairie
[Termes IGN] surface cultivée
[Termes IGN] urbanisationRésumé : (Auteur) The objective of this study is to assess the effectiveness of landscape metrics in quantifying the urbanization-induced land use and land cover (LULC) changes from a landscape ecology perspective using the City of Indianapolis, Indiana, USA as a case study. Two Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images, acquired on 3 October 2000 and 13 October 2006, respectively, and two Landsat 5 Thematic Mapper images, acquired on 22 October 1989 and 20 October 2000, respectively, were used for the study. Seven LULC types were identified: urban, agriculture, grasslands, forest, water, barren lands and wetlands. A series of landscape metrics were then computed for each LULC type and these metrics were used to compare the two ASTER-derived LULC maps with the two Landsat-derived maps. Results show that urbanization contributed significantly to LULC changes in the study area. Agricultural lands decreased and forests became more disaggregated. Grassland increased slightly in size and aggregation level and improved in connectedness. Numéro de notice : A2013-699 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2012.752530 Date de publication en ligne : 06/02/2013 En ligne : https://doi.org/10.1080/10106049.2012.752530 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32835
in Geocarto international > vol 28 n° 7-8 (November - December 2013) . - pp 582 - 593[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2013041 RAB Revue Centre de documentation En réserve L003 Disponible Modeling of spatio-temporal dynamics of land use and land cover in a part of Brahmaputra River basin using Geoinformatic techniques / M. Sarabuddin Mondal in Geocarto international, vol 28 n° 7-8 (November - December 2013)PermalinkLa télédétection au service des études urbaines : expansion de la ville de Pondichéry entre 1973 et 2009 / Emilien Kieffer in Géomatique expert, n° 95 (01/11/2013)PermalinkAssessing the relationship between ground measurements and object-based image analysis of land cover classes in Pinyon and Juniper Woodlands / April Hulet in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 9 (September 2013)PermalinkAutomatic extraction of building roofs using LIDAR data and multispectral imagery / Mohammad Awrangjeb in ISPRS Journal of photogrammetry and remote sensing, vol 83 (September 2013)PermalinkGeneralized composite kernel framework for hyperspectral image classification / J. Li in IEEE Transactions on geoscience and remote sensing, vol 51 n° 9 (September 2013)PermalinkCommercial tree species discrimination using airborne AISA Eagle hyperspectral imagery and partial least squares discriminant analysis (PLS-DA) in KwaZulu–Natal, South Africa / Kabir Yunus Peerbhay in ISPRS Journal of photogrammetry and remote sensing, vol 79 (May 2013)PermalinkAssessing reference dataset representativeness through confidence metrics based on information density / Giorgos Mountrakis in ISPRS Journal of photogrammetry and remote sensing, vol 78 (April 2013)PermalinkClassification and reconstruction from random projections for hyperspectral imagery / W. Li in IEEE Transactions on geoscience and remote sensing, vol 51 n° 2 (February 2013)PermalinkGround filtering and vegetation mapping using multi-return terrestrial laser scanning / Francesco Pirotti in ISPRS Journal of photogrammetry and remote sensing, vol 76 (February 2013)PermalinkSupport vector machine for spatial variation / C. Andris in Transactions in GIS, vol 17 n° 1 (February 2013)Permalink