Descripteur
Documents disponibles dans cette catégorie (1887)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
Habitat change on Horn Island, Mississippi, 1940-2010, determined from textural features in panchromatic vertical aerial imagery / Guy W. Jeter Jr in Geocarto international, Vol 31 n° 9 - 10 (October - November 2016)
[article]
Titre : Habitat change on Horn Island, Mississippi, 1940-2010, determined from textural features in panchromatic vertical aerial imagery Type de document : Article/Communication Auteurs : Guy W. Jeter Jr, Auteur ; Gregory Carter, Auteur Année de publication : 2016 Article en page(s) : pp 985 - 994 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse diachronique
[Termes IGN] analyse spatiale
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] habitat (nature)
[Termes IGN] habitat d'espèce
[Termes IGN] image optique
[Termes IGN] image panchromatique
[Termes IGN] marais
[Termes IGN] Mississippi (Etats-Unis)
[Termes IGN] texture d'imageRésumé : (auteur) Habitat-type land cover on Horn Island, Mississippi, northern Gulf of Mexico, was estimated for the years 1940 and 2010 using a combination of panchromatic imagery and 2010 ground survey data. A grey-level co-occurrence matrix was applied to compute reflectance coefficient of variation (CV) and texture indices. The relationships of 2010 CV ranges with known habitat types defined training regions of interest in the 1940 imagery as a substitute for 1940 ground data. Texture indices contrast, correlation, energy and entropy then served as input bands for maximum likelihood classifications which produced 1940 and 2010 habitat maps. Analysis determined that wetter habitats on Horn expanded linearly over the seven-decade period. This is attributed to constraints on sediment supply and the impacts of severe storms which led to decreases in soil depth to the water table. If this trend continues, marsh habitat will cover 31% of Horn Island’s land area by 2050. Numéro de notice : A2016-669 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2015.1094527 Date de publication en ligne : 29/10/2015 En ligne : http://dx.doi.org/10.1080/10106049.2015.1094527 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81901
in Geocarto international > Vol 31 n° 9 - 10 (October - November 2016) . - pp 985 - 994[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 059-2016051 RAB Revue Centre de documentation En réserve L003 Disponible Influence of tree species complexity on discrimination performance of vegetation indices / Azadeh Ghiyamat in European journal of remote sensing, vol 49 n° 1 (2016)
[article]
Titre : Influence of tree species complexity on discrimination performance of vegetation indices Type de document : Article/Communication Auteurs : Azadeh Ghiyamat, Auteur ; Helmi Zulhaidi Mohd Shafri, Auteur ; Abdul Rashid Mohamed Shariff, Auteur Année de publication : 2016 Article en page(s) : pp 15 - 37 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse de mélange spectral d’extrémités multiples
[Termes IGN] analyse discriminante
[Termes IGN] espèce végétale
[Termes IGN] image aérienne
[Termes IGN] image hyperspectrale
[Termes IGN] indice de végétation
[Termes IGN] information complexe
[Termes IGN] Pinus nigra corsicana
[Termes IGN] Pinus sylvestris
[Termes IGN] test de performanceRésumé : (auteur) Performance of different vegetation indices (VIs) in combination with single- and multipleendmember (SEM and MEM) for discriminating Corsican and Scots pines with different ages and Broadleaves tree species is demonstrated by using an airborne hyperspectral data. The analysis is performed in three different complexity levels. The results show by increasing tree species complexity, overall accuracy significantly reduced. An overall accuracy up to 90% is obtained from the first category with the least complexity; however, it is reduced to 55% in the third category with the highest complexity. By employing MEM, performance of normalized difference vegetation index (NDVI) is increased by 10%. Numéro de notice : A2016-834 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.5721/EuJRS20164902 En ligne : http://dx.doi.org/10.5721/EuJRS20164902 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82723
in European journal of remote sensing > vol 49 n° 1 (2016) . - pp 15 - 37[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]A robust approach for tree segmentation in deciduous forests using small-footprint airborne LiDAR data / Hamid Hamraz in International journal of applied Earth observation and geoinformation, vol 52 (October 2016)
[article]
Titre : A robust approach for tree segmentation in deciduous forests using small-footprint airborne LiDAR data Type de document : Article/Communication Auteurs : Hamid Hamraz, Auteur ; Marco A. Contreras, Auteur ; Jun Zhang, Auteur Année de publication : 2016 Article en page(s) : pp 532 - 541 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] arbre (flore)
[Termes IGN] détection de contours
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] feuillu
[Termes IGN] houppier
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] Kentucky (Etats-Unis)
[Termes IGN] pente
[Termes IGN] segmentation
[Termes IGN] semis de pointsRésumé : (auteur) This paper presents a non-parametric approach for segmenting trees from airborne LiDAR data in deciduous forests. Based on the LiDAR point cloud, the approach collects crown information such as steepness and height on-the-fly to delineate crown boundaries, and most importantly, does not require a priori assumptions of crown shape and size. The approach segments trees iteratively starting from the tallest within a given area to the smallest until all trees have been segmented. To evaluate its performance, the approach was applied to the University of Kentucky Robinson Forest, a deciduous closed-canopy forest with complex terrain and vegetation conditions. The approach identified 94% of dominant and co-dominant trees with a false detection rate of 13%. About 62% of intermediate, overtopped, and dead trees were also detected with a false detection rate of 15%. The overall segmentation accuracy was 77%. Correlations of the segmentation scores of the proposed approach with local terrain and stand metrics was not significant, which is likely an indication of the robustness of the approach as results are not sensitive to the differences in terrain and stand structures. Numéro de notice : A2016-705 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.jag.2016.07.006 En ligne : http://dx.doi.org/10.1016/j.jag.2016.07.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82075
in International journal of applied Earth observation and geoinformation > vol 52 (October 2016) . - pp 532 - 541[article]Robust collaborative nonnegative matrix factorization for hyperspectral unmixing / Jun Li in IEEE Transactions on geoscience and remote sensing, vol 54 n° 10 (October 2016)PermalinkSAR image change detection based on correlation kernel and multistage extreme learning machine / Lu Jia in IEEE Transactions on geoscience and remote sensing, vol 54 n° 10 (October 2016)PermalinkAccuracy assessment of NOAA coastal change analysis program 2006 - 2010 land cover and land cover change data / John W. McCombs in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 9 (September 2016)PermalinkAn adaptable equal-area pseudoconic map projection / Daniel "daan" Strebe in Cartography and Geographic Information Science, Vol 43 n° 4 (September 2016)PermalinkAutomatic recognition of long period events from volcano tectonic earthquakes at Cotopaxi volcano / Román A. Lara-Cueva in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)PermalinkDistance measure based change detectors for polarimetric SAR imagery / Yonghong Zhang in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 9 (September 2016)PermalinkEstimating forest species abundance through linear unmixing of CHRIS/PROBA imagery / S. Stagakis in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)PermalinkInternational benchmarking of the individual tree detection methods for modeling 3-D canopy structure for silviculture and forest ecology using airborne laser scanning / Yunsheng Wang in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)PermalinkReconstruction en 3D des bâtiments à partir des données Lidar / M. A. Missomi in Géomatique expert, n° 112 (septembre - octobre 2016)PermalinkSatellite images analysis for shadow detection and building height estimation / Gregoris Liasis in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)PermalinkSemiblind hyperspectral unmixing in the presence of spectral library mismatches / Xiao Fu in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)PermalinkShadow detection and removal in RGB VHR images for land use unsupervised classification / A. Movia in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)PermalinkA simulated annealing algorithm for zoning in planning using parallel computing / Inès Santé in Computers, Environment and Urban Systems, vol 59 (September 2016)PermalinkSlicing method for curved façade and window extraction from point clouds / S.M. Iman Zolanvari in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)PermalinkSpatiotemporal subpixel mapping of time-series images / Qunming Wang in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)PermalinkA local structure and direction-aware optimization approach for three-dimensional tree modeling / Zhen Wang in IEEE Transactions on geoscience and remote sensing, vol 54 n° 8 (August 2016)PermalinkSimultaneously sparse and low-rank abundance matrix estimation for hyperspectral image unmixing / Paris V. Giampouras in IEEE Transactions on geoscience and remote sensing, vol 54 n° 8 (August 2016)PermalinkApport des images THRS pour la catégorisation des agro-systèmes complexes à Mayotte / Rafaël Molina in Géomatique expert, n° 111 (juillet- août 2016)PermalinkAutomatic delineation of built-up area at urban block level from topographic maps / Sebastian Muhs in Computers, Environment and Urban Systems, vol 58 (July 2016)PermalinkClassifying buildings from point clouds and images / Evangelos Maltezos in GIM international, vol 30 n° 7 (July 2016)Permalink