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Understanding the spatial distribution of elephant (Loxodonta africana) poaching incidences in the mid-Zambezi Valley, Zimbabwe using Geographic Information Systems and remote sensing / Mbulisi Sibanda in Geocarto international, Vol 31 n° 9 - 10 (October - November 2016)
[article]
Titre : Understanding the spatial distribution of elephant (Loxodonta africana) poaching incidences in the mid-Zambezi Valley, Zimbabwe using Geographic Information Systems and remote sensing Type de document : Article/Communication Auteurs : Mbulisi Sibanda, Auteur ; Timothy Dube, Auteur ; Victor M. Bangamwabo, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 1006 - 1018 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] aire protégée
[Termes IGN] chasse
[Termes IGN] couvert végétal
[Termes IGN] distribution spatiale
[Termes IGN] habitat animal
[Termes IGN] Mammalia
[Termes IGN] régression logistique
[Termes IGN] surveillance écologique
[Termes IGN] ZimbabweMots-clés libres : braconnage Résumé : (auteur) The objective of this study was to understand the factors that explain the spatial distribution of elephant poaching activities in the areas of the mid-Zambezi Valley, Zimbabwe using geographic information system (GIS) and remotely sensed data integrated with spatial logistic regression. The results showed that significant (α = 0.05) elephant poaching hot spots are located closer to wildlife protected areas. Results further demonstrated that resource availability (water and forage) are the main factors explaining elephant poaching activities in the mid-Zambezi Valley. For example, the majority of poaching activities were found to occur in areas with high vegetation fractional cover (high forage) and close to waterholes. The results also showed that poaching incidences were more prevalent during the dry season. The findings of this study highlight the significance of integrating GIS, remotely sensed data and spatial logistic regression tools for understanding and monitoring elephant poaching activities. This information is critical if poaching activities are to be minimized and it is also important for planning, monitoring and mitigation of poaching activities in similar protected areas across the sub-Saharan Africa. Numéro de notice : A2016-670 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2015.1094529 Date de publication en ligne : 27/10/2015 En ligne : http://dx.doi.org/10.1080/10106049.2015.1094529 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81902
in Geocarto international > Vol 31 n° 9 - 10 (October - November 2016) . - pp 1006 - 1018[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2016051 RAB Revue Centre de documentation En réserve L003 Disponible Accuracy 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)
[article]
Titre : Accuracy assessment of NOAA coastal change analysis program 2006 - 2010 land cover and land cover change data Type de document : Article/Communication Auteurs : John W. McCombs, Auteur ; Shan G. Burkhalter, Auteur ; Christopher D. Robinson, Auteur Année de publication : 2016 Article en page(s) : pp 711 - 718 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photo-interprétation
[Termes IGN] analyse diachronique
[Termes IGN] couvert végétal
[Termes IGN] détection de changement
[Termes IGN] Etats-Unis
[Termes IGN] image Landsat
[Termes IGN] littoral
[Termes IGN] niveau d'analyseRésumé : (Auteur) A new approach to locating accuracy assessment sample units was used to quantify 2010 land cover accuracy, in addition to being able to make statements about 2006-2010 land cover change mapping accuracy for National Oceanic and Atmospheric Administration (NOAA) Coastal Change Analysis Program (C-CAP) data. Three customized tiers of sampling strata were created, as discussed, to meet these goals. Stratified random sampling was employed in each stratum with a six out of nine pixel-homogeneity criteria (different from the final minimum mapping unit) required for each sampling unit. Accuracy was assessed for nine regions in the coastal United States with overall accuracy ranging from 82.3 percent to 85.6 percent. Binary change was mapped with 88.7 percent accuracy, with the largest error being errors of commission (71.2 percent user accuracy). This sampling design also allowed for the identification of 137 locations where true change was not mapped, allowing for statements to be made about missed change. Numéro de notice : A2016-741 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14358/PERS.82.9.711 En ligne : https://doi.org/10.14358/PERS.82.9.711 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82277
in Photogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 9 (September 2016) . - pp 711 - 718[article]Enhancing building footprints with squaring operations / Imran Lokhat in Journal of Spatial Information Science, JoSIS, n° 13 (September 2016)
[article]
Titre : Enhancing building footprints with squaring operations Type de document : Article/Communication Auteurs : Imran Lokhat , Auteur ; Guillaume Touya , Auteur Année de publication : 2016 Article en page(s) : pp 33 - 60 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] base de données localisées
[Termes IGN] bati
[Termes IGN] empreinte
[Termes IGN] généralisation cartographique automatisée
[Termes IGN] méthode des moindres carrés
[Termes IGN] OpenStreetMap
[Termes IGN] quadrillage
[Vedettes matières IGN] GénéralisationRésumé : (Auteur) Whatever the data source, or the capture process, the creation of a building footprint in a geographical dataset is error prone. Building footprints are designed with square angles, but once in a geographical dataset, the angles may not be exactly square. The almost-square angles blur the legibility of the footprints when displayed on maps, but might also be propagated in further applications based on the footprints, e.g., 3D city model construction. This paper proposes two new methods to square such buildings: a simple one, and a more complex one based on nonlinear least squares. The latter squares right and flat angles by iteratively moving vertices, while preserving the initial shape and position of the buildings. The methods are tested on real datasets and assessed against existing methods, proving the usefulness of the contribution. Direct applications of the squaring transformation, such as OpenStreetMap enhancement, or map generalization are presented. Numéro de notice : A2016--117 Affiliation des auteurs : LASTIG COGIT (2012-2019) Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5311/JOSIS.2016.13.276 En ligne : http://josis.org/index.php/josis/article/view/276 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84777
in Journal of Spatial Information Science, JoSIS > n° 13 (September 2016) . - pp 33 - 60[article]Documents numériques
en open access
Enhancing building footprints ... - pdf éditeurAdobe Acrobat PDF Local-scale flood mapping on vegetated floodplains from radiometrically calibrated airborne LiDAR data / Radosław Malinowski in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)
[article]
Titre : Local-scale flood mapping on vegetated floodplains from radiometrically calibrated airborne LiDAR data Type de document : Article/Communication Auteurs : Radosław Malinowski, Auteur ; Bernhard Höfle, Auteur ; Kristina Koenig, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 267 - 279 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] capteur aérien
[Termes IGN] cartographie des risques
[Termes IGN] classification
[Termes IGN] classification bayesienne
[Termes IGN] classification par arbre de décision
[Termes IGN] coefficient de rétrodiffusion
[Termes IGN] couvert végétal
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] étalonnage radiométrique
[Termes IGN] forme d'onde pleine
[Termes IGN] inondation
[Termes IGN] lidar à retour d'onde complète
[Termes IGN] lit majeurRésumé : (Auteur) Knowledge about the magnitude of localised flooding of riverine areas is crucial for appropriate land management and administration at regional and local levels. However, detection and delineation of localised flooding with remote sensing techniques are often hampered on floodplains by the presence of herbaceous vegetation. To address this problem, this study presents the application of full-waveform airborne laser scanning (ALS) data for detection of floodwater extent. In general, water surfaces are characterised by low values of backscattered energy due to water absorption of the infrared laser shots, but the exact strength of the recorded laser pulse depends on the area covered by the targets located within a laser pulse footprint area. To account for this we analysed the physical quantity of radiometrically calibrated ALS data, the backscattering coefficient, in relation to water and vegetation coverage within a single laser footprint. The results showed that the backscatter was negatively correlated to water coverage, and that of the three distinguished classes of water coverage (low, medium, and high) only the class with the largest extent of water cover (>70%) had relatively distinct characteristics that can be used for classification of water surfaces. Following the laser footprint analysis, three classifiers, namely AdaBoost with Decision Tree, Naïve Bayes and Random Forest, were utilised to classify laser points into flooded and non-flooded classes and to derive the map of flooding extent. The performance of the classifiers is highly dependent on the set of laser points features used. Best performance was achieved by combining radiometric and geometric laser point features. The accuracy of flooding maps based solely on radiometric features resulted in overall accuracies of up to 70% and was limited due to the overlap of the backscattering coefficient values between water and other land cover classes. Our point-based classification methods assure a high mapping accuracy (∼89%) and demonstrate the potential of using full-waveform ALS data to detect water surfaces on floodplain areas with limited water surface exposition through the vegetation canopy. Numéro de notice : A2016-785 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2016.06.009 En ligne : https://doi.org/10.1016/j.isprsjprs.2016.06.009 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82499
in ISPRS Journal of photogrammetry and remote sensing > vol 119 (September 2016) . - pp 267 - 279[article]Mapping of land cover in northern California with simulated hyperspectral satellite imagery / Matthew L. Clark in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)
[article]
Titre : Mapping of land cover in northern California with simulated hyperspectral satellite imagery Type de document : Article/Communication Auteurs : Matthew L. Clark, Auteur ; Nina E. Kilham, Auteur Année de publication : 2016 Article en page(s) : pp 228 - 245 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] base de données d'occupation du sol
[Termes IGN] Californie (Etats-Unis)
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] image hyperspectrale
[Termes IGN] interprétation automatique
[Termes IGN] occupation du sol
[Termes IGN] simulation d'imageRésumé : (Auteur) Land-cover maps are important science products needed for natural resource and ecosystem service management, biodiversity conservation planning, and assessing human-induced and natural drivers of land change. Analysis of hyperspectral, or imaging spectrometer, imagery has shown an impressive capacity to map a wide range of natural and anthropogenic land cover. Applications have been mostly with single-date imagery from relatively small spatial extents. Future hyperspectral satellites will provide imagery at greater spatial and temporal scales, and there is a need to assess techniques for mapping land cover with these data. Here we used simulated multi-temporal HyspIRI satellite imagery over a 30,000 km2 area in the San Francisco Bay Area, California to assess its capabilities for mapping classes defined by the international Land Cover Classification System (LCCS). We employed a mapping methodology and analysis framework that is applicable to regional and global scales. We used the Random Forests classifier with three sets of predictor variables (reflectance, MNF, hyperspectral metrics), two temporal resolutions (summer, spring-summer-fall), two sample scales (pixel, polygon) and two levels of classification complexity (12, 20 classes). Hyperspectral metrics provided a 16.4–21.8% and 3.1–6.7% increase in overall accuracy relative to MNF and reflectance bands, respectively, depending on pixel or polygon scales of analysis. Multi-temporal metrics improved overall accuracy by 0.9–3.1% over summer metrics, yet increases were only significant at the pixel scale of analysis. Overall accuracy at pixel scales was 72.2% (Kappa 0.70) with three seasons of metrics. Anthropogenic and homogenous natural vegetation classes had relatively high confidence and producer and user accuracies were over 70%; in comparison, woodland and forest classes had considerable confusion. We next focused on plant functional types with relatively pure spectra by removing open-canopy shrublands, woodlands and mixed forests from the classification. This 12-class map had significantly improved accuracy of 85.1% (Kappa 0.83) and most classes had over 70% producer and user accuracies. Finally, we summarized important metrics from the multi-temporal Random Forests to infer the underlying chemical and structural properties that best discriminated our land-cover classes across seasons. Numéro de notice : A2016-783 Affiliation des auteurs : non IGN Autre URL associée : Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2016.06.007 En ligne : https://doi.org/10.1016/j.isprsjprs.2016.06.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82480
in ISPRS Journal of photogrammetry and remote sensing > vol 119 (September 2016) . - pp 228 - 245[article]A measure of average error variance of line features / Eryong Liu in Cartography and Geographic Information Science, Vol 43 n° 4 (September 2016)PermalinkNovel tool for examination of data completeness based on a comparative study of VGI data and official building datasets / Joanna Nowak Da Costa in Geodetski vestnik, vol 60 n° 3 (September - November 2016)PermalinkSpatiotemporal subpixel mapping of time-series images / Qunming Wang in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)PermalinkThe impacts of building orientation on polarimetric orientation angle estimation and model-based decomposition for multilook polarimetric SAR data in urban areas / Hongzhong Li in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)PermalinkAirborne lidar estimation of aboveground forest biomass in the absence of field inventory / António Ferraz in Remote sensing, vol 8 n° 8 (August 2016)PermalinkGeographically weighted evidence combination approaches for combining discordant and inconsistent volunteered geographical information / Alexis Comber in Geoinformatica, vol 20 n° 3 (July - September 2016)PermalinkLearning-based superresolution land cover mapping / Feng Ling in IEEE Transactions on geoscience and remote sensing, vol 54 n° 7 (July 2016)PermalinkThe direction-constrained k nearest neighbor query dealing with spatio-directional objects / Min-Joong Lee in Geoinformatica, vol 20 n° 3 (July - September 2016)PermalinkFusion of hyperspectral and VHR multispectral image classifications in urban α–areas / Alexandre Hervieu in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol III-3 (July 2016)PermalinkAn assessment of algorithmic parameters affecting image classification accuracy by random forests / Dee Shi in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 6 (June 2016)PermalinkConception de modèles 3D précis pour un suivi 4D optimisé des ouvrages hydrauliques linéaires : intérêt et particularité du drone / Vincent Tournadre in La Houille Blanche, revue internationale de l'eau, vol 2016 n° 3 (juin 2016)PermalinkContext-dependent detection of non-linearly distributed points for vegetation classification in airborne LiDAR / Denis Horvat in ISPRS Journal of photogrammetry and remote sensing, vol 116 (June 2016)PermalinkGeometric accuracy of topographical objects at Polish topographic maps / Radzym Lawniczack in Geodesy and cartography, vol 65 n° 1 (June 2016)PermalinkOptical remotely sensed time series data for land cover classification: A review / Cristina Gómez in ISPRS Journal of photogrammetry and remote sensing, vol 116 (June 2016)PermalinkQualitative spatial logics for buffered geometries / Heshan Du in Journal of Artificial Intelligence Research, vol 56 (May - August 2016)PermalinkVector attribute profiles for hyperspectral image classification / Erchan Aptoula in IEEE Transactions on geoscience and remote sensing, vol 54 n° 6 (June 2016)PermalinkHybrid terrain rendering based on the external edge primitive / E.G. Paredes in International journal of geographical information science IJGIS, vol 30 n° 5-6 (May - June 2016)PermalinkL’imagerie satellitaire stéréoscopique très haute résolution spatiale Pléiades : apport pour les problématiques urbaines / Dominique Hébrard in Signature, n° 60 (mai 2016)PermalinkQuantifying the completeness of and correspondence between two historical maps: a case study from nineteenth-century Palestine / Gad Schaffer in Cartography and Geographic Information Science, Vol 43 n° 2 (April - May 2016)PermalinkDie Fortführung des 3D-Gebäudemodells LoD2 in Nordrhein-Westfalen / Marco Oestereich in ZFV, Zeitschrift für Geodäsie, Geoinformation und Landmanagement, Vol 141 n° 3 (Mai - Juni 2016)PermalinkLes données géographiques 3D pour simuler l'impact de la réglementation urbaine sur la morphologie du bâti / Mickaël Brasebin in Cartes & Géomatique, n° 227 (mars - mai 2016)PermalinkA GEOBIA framework for the implementation of national and international forest definitions using very high spatial resolution optical satellite data / M. Tompoulidou in Geocarto international, vol 31 n° 3 - 4 (March - April 2016)PermalinkMapping urban growth of the capital city of Honduras from Landsat data using the impervious surface fraction algorithm / Nguyen-Thanh Son in Geocarto international, vol 31 n° 3 - 4 (March - April 2016)PermalinkA region-line primitive association framework for object-based remote sensing image analysis / Wang Min in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 2 (February 2016)PermalinkPermalinkPermalinkPermalinkChanges in thermal infrared spectra of plants caused by temperature and water stress / Maria F. Buitrago in ISPRS Journal of photogrammetry and remote sensing, vol 111 (January 2016)PermalinkConception et implémentation d'un modèle de style adapté à une application web 3D / Anouk Vinesse (2016)PermalinkLand Surface Remote Sensing in Urban and Coastal Areas, 1. Optical remote sensing in urban environments / Xavier Briottet (2016)PermalinkA multiscale masking method for point geographic data / K.C. Clarke in International journal of geographical information science IJGIS, vol 30 n° 1-2 (January - February 2016)PermalinkObject-oriented semantic labelling of spectral–spatial LiDAR point cloud for urban land cover classification and buildings detection / Anandakumar M. Ramiya in Geocarto international, vol 31 n° 1 - 2 (January - February 2016)PermalinkPassive microwave remote sensing of soil moisture based on dynamic vegetation scattering properties for AMSR-E / Jinyang Du in IEEE Transactions on geoscience and remote sensing, vol 54 n° 1 (January 2016)PermalinkPrise en compte des mises à jour d’un référentiel dans une base métier : cas des réseaux linaires / Silvio Rousic in Signature, n° 59 (janvier 2016)PermalinkPermalinkA back-propagation neural network-based approach for multi-represented feature matching in update propagation / Yanxia Wang in Transactions in GIS, vol 19 n° 6 (December 2015)PermalinkUn cadre formel pour la généralisation multi-échelle de l'occupation du sol au sein de ScaleMaster 2.0 / Jean-François Girres in Cartes & Géomatique, n° 226 (décembre 2015)PermalinkResidual vegetation patches within natural boreal wild fires: Characterizing by pattern metrics, land cover expec tations and proximity to firebreak features / Yikalo H. Araya in Geomatica, vol 69 n° 4 (December 2015)PermalinkUrban classification by the fusion of thermal infrared hyperspectral and visible data / Jiayi Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 12 (December 2015)PermalinkA moving weighted harmonic analysis method for reconstructing high-quality SPOT VEGETATION NDVI time-series data / Gang Yang in IEEE Transactions on geoscience and remote sensing, vol 53 n° 11 (November 2015)PermalinkLa néo-géographie sous l'oeil des chercheurs / Françoise de Blomac in DécryptaGéo le mag, n° 171 (novembre 2015)PermalinkAccelerated deforestation driven by large-scale land acquisitions in Cambodia / Kyle Frankel Davis in Nature geoscience, vol 8 n° 10 (October 2015)PermalinkEarth observation as a tool for tracking progress towards the Aichi Biodiversity Targets / Brian O’Connor in Remote sensing in ecology and conservation, vol 1 n° 1 (October 2015)PermalinkFusion of waveform LiDAR data and hyperspectral imagery for land cover classification / Hongzhou Wang in ISPRS Journal of photogrammetry and remote sensing, vol 108 (October 2015)PermalinkLand cover changes assessment using object-based image analysis in the Binah River watershed (Togo and Benin) / Hèou Maléki Badjana in Earth and space science, vol 2 n° 10 (October 2015)Permalink