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Termes IGN > géomatique > base de données localisées > couche thématique > occupation du sol
occupation du sol
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Espace, organisation de l' Utilisation du sol Politique foncière Sol, Occupation du Sols -- Utilisation Sols -- Utilisation Terrains -- Utilisation Terrains, Utilisation des Utilisation du sol Espace (économie politique) >> Aménagement du territoire Paysage -- Évaluation Syndrome NIMBY >>Terme(s) spécifique(s) : Améliorations foncières Cadastres Décharges contrôlées Immobilier Photographie aérienne en utilisation du sol Politique forestière Promotion immobilière Propriété foncière Propriété immobilière -- Acquisition par l'Administration Terres publiques Zones d'aménagement différé Equiv. LCSH : Land use Domaine(s) : 330 |
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Spectranomics: Emerging science and conservation opportunities at the interface of biodiversity and remote sensing / Gregory P. Asner in Global ecology and conservation, vol 8 (October 2016)
[article]
Titre : Spectranomics: Emerging science and conservation opportunities at the interface of biodiversity and remote sensing Type de document : Article/Communication Auteurs : Gregory P. Asner, Auteur ; Roberta E. Martin, Auteur Année de publication : 2016 Article en page(s) : pp 212 -219 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] biogéographie
[Termes IGN] canopée
[Termes IGN] couvert forestier
[Termes IGN] couvert végétal
[Termes IGN] politique de conservation (biodiversité)
[Termes IGN] réflectance végétale
[Termes IGN] spectroscopieRésumé : (auteur) With the goal of advancing remote sensing in biodiversity science, Spectranomics represents an emerging approach, and a suite of quantitative methods, intended to link plant canopy phylogeny and functional traits to their spectral-optical properties. The current Spectranomics database contains about one half of known tropical forest canopy tree species worldwide, and has become a forecasting asset for predicting aspects of plant functional and biological diversity to be remotely mapped and monitored with current and future spectral remote sensing technology. To mark ten years of Spectranomics, we review recent scientific outcomes to further stimulate engagement in the use of spectral remote sensing for biodiversity and functional ecology research. In doing so, we highlight three major emerging opportunities for the science and conservation communities based on Spectranomics. Numéro de notice : A2016-715 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET/IMAGERIE Nature : Article DOI : 10.1016/j.gecco.2016.09.010 En ligne : http://dx.doi.org/10.1016/j.gecco.2016.09.010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82108
in Global ecology and conservation > vol 8 (October 2016) . - pp 212 -219[article]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]Exemplaires(1)
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]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]Spatiotemporal subpixel mapping of time-series images / Qunming Wang 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)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)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)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)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)Permalink