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Urban slum detection using texture and spatial metrics derived from satellite imagery / Divyani Kohli in Journal of spatial science, vol 61 n° 2 (December 2016)
[article]
Titre : Urban slum detection using texture and spatial metrics derived from satellite imagery Type de document : Article/Communication Auteurs : Divyani Kohli, Auteur ; Robert Sliuzas, Auteur ; Alfred Stein, Auteur Année de publication : 2016 Article en page(s) : pp 405 - 426 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse d'image orientée objet
[Termes IGN] détection du bâti
[Termes IGN] image Quickbird
[Termes IGN] Maharashtra (Inde ; état)
[Termes IGN] ontologie
[Termes IGN] spatial metrics
[Termes IGN] texture d'image
[Termes IGN] villeRésumé : (auteur) Slum detection from satellite imagery is challenging due to the variability in slum types and definitions. This research aimed at developing a method for slum detection based on the morphology of the built environment. The method consists of segmentation followed by hierarchical classification using object-oriented image analysis and integrating expert knowledge in the form of a local slum ontology. Results show that textural feature contrast derived from a grey-level co-occurrence matrix was useful for delineating segments of slum areas or parts thereof. Spatial metrics such as the size of segments and proportions of vegetation and built-up were used for slum detection. The percentage of agreement between the reference layer and slum classification was 60 percent. This is lower than the accuracy achieved for land cover classification (80.8 percent), due to large variations. We conclude that the method produces useful results and has potential for successful application in contexts with similar morphology. Numéro de notice : A2016--147 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/14498596.2016.1138247 Date de publication en ligne : 05/05/2016 En ligne : http://dx.doi.org/10.1080/14498596.2016.1138247 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86334
in Journal of spatial science > vol 61 n° 2 (December 2016) . - pp 405 - 426[article]Automatic segment-level tree species recognition using high resolution aerial winter imagery / Anton Kuzmin in European journal of remote sensing, vol 49 n° 1 (2016)
[article]
Titre : Automatic segment-level tree species recognition using high resolution aerial winter imagery Type de document : Article/Communication Auteurs : Anton Kuzmin, Auteur ; Lauri Korhonen, Auteur ; Terhikki Manninen, Auteur ; Matti Maltamo, Auteur Année de publication : 2016 Article en page(s) : pp 239 - 259 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse d'image orientée objet
[Termes IGN] analyse discriminante
[Termes IGN] betula pubescens
[Termes IGN] composition floristique
[Termes IGN] forêt boréale
[Termes IGN] hélicoptère
[Termes IGN] hiver
[Termes IGN] image à ultra haute résolution
[Termes IGN] image aérienne
[Termes IGN] neige
[Termes IGN] Picea abies
[Termes IGN] Pinus sylvestrisRésumé : (auteur) Our objective was to automatically recognize the species composition of a boreal forest from high-resolution airborne winter imagery. The forest floor was covered by snow so that the contrast between the crowns and the background was maximized. The images were taken from a helicopter flying at low altitude so that fine details of the canopy structure could be distinguished. Segments created by an object-oriented image processing were used as a basis for a linear discriminant analysis, which aimed at separating the three dominant tree species occurring in the area: Scots pine, Norway spruce, and downy birch. In a cross validation, the classification showed an overall accuracy of 81.9%, and a kappa coefficient of 0.73. Numéro de notice : A2016-831 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.5721/EuJRS20164914 En ligne : http://dx.doi.org/10.5721/EuJRS20164914 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82714
in European journal of remote sensing > vol 49 n° 1 (2016) . - pp 239 - 259[article]Object-based morphological profiles for classification of remote sensing imagery / Christian Geiss in IEEE Transactions on geoscience and remote sensing, vol 54 n° 10 (October 2016)
[article]
Titre : Object-based morphological profiles for classification of remote sensing imagery Type de document : Article/Communication Auteurs : Christian Geiss, Auteur ; Martin Klotz, Auteur ; Andreas Schmitt, Auteur ; Hannes Taubenböck, Auteur Année de publication : 2016 Article en page(s) : pp 5952 - 5963 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse d'image orientée objet
[Termes IGN] classification automatique
[Termes IGN] classification orientée objet
[Termes IGN] décomposition d'image
[Termes IGN] image hyperspectrale
[Termes IGN] image multibande
[Termes IGN] morphologie mathématique
[Termes IGN] reconstruction d'imageRésumé : (auteur) Morphological operators (MOs) and their enhancements such as morphological profiles (MPs) are subject to a lively scientific contemplation since they are found to be beneficial for, for example, classification of very high spatial resolution panchromatic, multi-, and hyperspectral imagery. They account for spatial structures with differing magnitudes and, thus, provide a comprehensive multilevel description of an image. In this paper, we introduce the concept of object-based MPs (OMPs) to also encode shape-related, topological, and hierarchical properties of image objects in an exhaustive way. Thereby, we seek to benefit from the so-called object-based image analysis framework by partitioning the original image into objects with a segmentation algorithm on multiple scales. The obtained spatial entities (i.e., objects) are used to aggregate multiple sequences obtained with MOs according to statistical measures of central tendency. This strategy is followed to simultaneously preserve and characterize shape properties of objects and enable both the topological and hierarchical decompositions of an image with respect to the progressive application of MOs. Subsequently, supervised classification models are learned by considering this additionally encoded information. Experimental results are obtained with a random forest classifier with heuristically tuned hyperparameters and a wrapper-based feature selection scheme. We evaluated the results for two test sites of panchromatic WorldView-II imagery, which was acquired over an urban environment. In this setting, the proposed OMPs allow for significant improvements with respect to classification accuracy compared to standard MPs (i.e., obtained by paired sequences of erosion, dilation, opening, closing, opening by top-hat, and closing by top-hat operations). Numéro de notice : A2016-864 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2576978 En ligne : https://doi.org/10.1109/TGRS.2016.2576978 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82899
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 10 (October 2016) . - pp 5952 - 5963[article]A probabilistic approach to detect mixed periodic patterns from moving object data / Jun Li in Geoinformatica, vol 20 n° 4 (October - December 2016)
[article]
Titre : A probabilistic approach to detect mixed periodic patterns from moving object data Type de document : Article/Communication Auteurs : Jun Li, Auteur ; Jingjing Wang, Auteur ; Junfei Zhang, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 715 - 739 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] comportement
[Termes IGN] détection automatique
[Termes IGN] détection d'objet
[Termes IGN] estimation par noyau
[Termes IGN] objet mobile
[Termes IGN] séquence d'images
[Termes IGN] variable aléatoireRésumé : (Auteur) The prevalence of moving object data (MOD) brings new opportunities for behavior related research. Periodic behavior is one of the most important behaviors of moving objects. However, the existing methods of detecting periodicities assume a moving object either does not have any periodic behavior at all or just has a single periodic behavior in one place. Thus they are incapable of dealing with many real world situations whereby a moving object may have multiple periodic behaviors mixed together. Aiming at addressing this problem, this paper proposes a probabilistic periodicity detection method called MPDA. MPDA first identifies high dense regions by the kernel density method, then generates revisit time sequences based on the dense regions, and at last adopts a filter-refine paradigm to detect mixed periodicities. At the filter stage, candidate periods are identified by comparing the observed and reference distribution of revisit time intervals using the chi-square test, and at the refine stage, a periodic degree measure is defined to examine the significance of candidate periods to identify accurate periods existing in MOD. Synthetic datasets with various characteristics and two real world tracking datasets validate the effectiveness of MPDA under various scenarios. MPDA has the potential to play an important role in analyzing complicated behaviors of moving objects. Numéro de notice : A2016-814 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s10707-016-0261-2 En ligne : http://dx.doi.org/10.1007/s10707-016-0261-2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82615
in Geoinformatica > vol 20 n° 4 (October - December 2016) . - pp 715 - 739[article]Apport des images THRS pour la catégorisation des agro-systèmes complexes à Mayotte / Rafaël Molina in Géomatique expert, n° 111 (juillet- août 2016)
[article]
Titre : Apport des images THRS pour la catégorisation des agro-systèmes complexes à Mayotte Type de document : Article/Communication Auteurs : Rafaël Molina, Auteur ; Dominique Didelot, Auteur ; Joël Huat, Auteur Année de publication : 2016 Article en page(s) : pp 30 - 37 Note générale : bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] agriculture
[Termes IGN] analyse d'image orientée objet
[Termes IGN] cartographie
[Termes IGN] classification dirigée
[Termes IGN] drone
[Termes IGN] grande échelle
[Termes IGN] Mayotte
[Termes IGN] télédétection spatialeRésumé : (auteur) [introduction][...]L'enjeu pour le service Statistique de la DAAF Mayotte(Direction de l'Agriculture, Alimentation et Forêt) est d'éviter d'inventorier exhaustivement par voie terrestre, en ayant recours à des images satellites pour orienter les enquêtes sur le terrain lors, notamment, du prochain Recensement Agricole (RA) 2020. Le but de l'étude, décrite ci-après, est de cartographier à grande échelle l'occupation des sols par télédétection. La difficulté majeure vient du fait que le "modèle agricole" le plus usité à Mayotte est le «jardin mahorais» où une famille cultive, sur de petites surfaces (à peine 0,5 ha) différentes espèces : bananes légumes, manioc, embrevade (pois d'angole), ananas, cela sous un couvert arboré épars de manguiers, cocotiers, litchis ou autres essences. Ce mode d'agriculture s'apparente à de l'agro-foresterie dont les vertus ne sont plus à démontrer en termes d'avantages environnementaux et agronomiques.
Le défi consiste donc à réussir à identifier correctement les différents types de systèmes culturaux que l'on trouve sur l'île (agro-forestier, vivrier, maraîchage...) de façon semi-automatique, en vue de suivre leur évolution surfacique dans le temps.Numéro de notice : A2016-487 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81504
in Géomatique expert > n° 111 (juillet- août 2016) . - pp 30 - 37[article]Réservation
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