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Assessing reference dataset representativeness through confidence metrics based on information density / Giorgos Mountrakis in ISPRS Journal of photogrammetry and remote sensing, vol 78 (April 2013)
[article]
Titre : Assessing reference dataset representativeness through confidence metrics based on information density Type de document : Article/Communication Auteurs : Giorgos Mountrakis, Auteur ; Bo Xi, Auteur Année de publication : 2013 Article en page(s) : pp 129 - 147 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse de sensibilité
[Termes IGN] carte d'occupation du sol
[Termes IGN] carte de confiance
[Termes IGN] classification dirigée
[Termes IGN] densité d'information
[Termes IGN] données localisées de référence
[Termes IGN] jeu de données localisées
[Termes IGN] representativitéRésumé : (Auteur) Land cover maps obtained from classification of remotely sensed imagery provide valuable information in numerous environmental monitoring and modeling tasks. However, many uncertainties and errors can directly or indirectly affect the quality of derived maps. This work focuses on one key aspect of the supervised classification process of remotely sensed imagery: the quality of the reference dataset used to develop a classifier. More specifically, the representative power of the reference dataset is assessed by contrasting it with the full dataset (e.g. entire image) needing classification. Our method is applicable in several ways: training or testing datasets (extracted from the reference dataset) can be compared with the full dataset. The proposed method moves beyond spatial sampling schemes (e.g. grid, cluster) and operates in the multidimensional feature space (e.g. spectral bands) and uses spatial statistics to compare information density of data to be classified with data used in the reference process. The working hypothesis is that higher information density, not in general but with respect to the entire classified image, expresses higher confidence in obtained results. Presented experiments establish a close link between confidence metrics and classification accuracy for a variety of image classifiers namely maximum likelihood, decision tree, Backpropagation Neural Network and Support Vector Machine. A sensitivity analysis demonstrates that spatially-continuous reference datasets (e.g. a square window) have the potential to provide similar classification confidence as typically-used spatially-random datasets. This is an important finding considering the higher acquisition costs for randomly distributed datasets. Furthermore, the method produces confidence maps that allow spatially-explicit comparison of confidence metrics within a given image for identification of over- and under-represented image portions. The current method is presented for individual image classification but, with sufficient evaluation from the remote sensing community it has the potential to become a standard for reference dataset reporting and thus allowing users to assess representativeness of reference datasets in a consistent manner across different classification tasks. Numéro de notice : A2013-183 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.01.011 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.01.011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32321
in ISPRS Journal of photogrammetry and remote sensing > vol 78 (April 2013) . - pp 129 - 147[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2013041 RAB Revue Centre de documentation En réserve L003 Disponible Line segment confidence region-based string matching method for map conflation / Yong Huh in ISPRS Journal of photogrammetry and remote sensing, vol 78 (April 2013)
[article]
Titre : Line segment confidence region-based string matching method for map conflation Type de document : Article/Communication Auteurs : Yong Huh, Auteur ; Sungchul Yang, Auteur ; Chillo Ga, Auteur ; et al., Auteur Année de publication : 2013 Article en page(s) : pp 69 - 84 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] appariement de données localisées
[Termes IGN] carte topographique
[Termes IGN] conflation
[Termes IGN] points homologues
[Termes IGN] segment de droiteRésumé : (Auteur) In this paper, a method to detect corresponding point pairs between polygon object pairs with a string matching method based on a confidence region model of a line segment is proposed. The optimal point edit sequence to convert the contour of a target object into that of a reference object was found by the string matching method which minimizes its total error cost, and the corresponding point pairs were derived from the edit sequence. Because a significant amount of apparent positional discrepancies between corresponding objects are caused by spatial uncertainty and their confidence region models of line segments are therefore used in the above matching process, the proposed method obtained a high F-measure for finding matching pairs. We applied this method for built-up area polygon objects in a cadastral map and a topographical map. Regardless of their different mapping and representation rules and spatial uncertainties, the proposed method with a confidence level at 0.95 showed a matching result with an F-measure of 0.894. Numéro de notice : A2013-180 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.01.006 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.01.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32318
in ISPRS Journal of photogrammetry and remote sensing > vol 78 (April 2013) . - pp 69 - 84[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2013041 RAB Revue Centre de documentation En réserve L003 Disponible Object-based fusion of multitemporal multiangle ENVISAT ASAR and HJ-1B multispectral data for urban land-cover mapping / Yifang Ban in IEEE Transactions on geoscience and remote sensing, vol 51 n° 4 Tome 1 (April 2013)
[article]
Titre : Object-based fusion of multitemporal multiangle ENVISAT ASAR and HJ-1B multispectral data for urban land-cover mapping Type de document : Article/Communication Auteurs : Yifang Ban, Auteur ; Alexender Jacob, Auteur Année de publication : 2013 Article en page(s) : pp 1998 - 2006 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] carte d'occupation du sol
[Termes IGN] conflation
[Termes IGN] fusion de données multisource
[Termes IGN] image Envisat-ASAR
[Termes IGN] image HJ-1B
[Termes IGN] image multibande
[Termes IGN] image multitemporelle
[Termes IGN] image radar moirée
[Termes IGN] Pékin (Chine)
[Termes IGN] segmentation d'image
[Termes IGN] zone urbaineRésumé : (Auteur) The objectives of this research are to develop robust methods for segmentation of multitemporal synthetic aperture radar (SAR) and optical data and to investigate the fusion of multitemporal ENVISAT advanced synthetic aperture radar (ASAR) and Chinese HJ-1B multispectral data for detailed urban land-cover mapping. Eight-date multiangle ENVISAT ASAR images and one-date HJ-1B charge-coupled device image acquired over Beijing in 2009 are selected for this research. The edge-aware region growing and merging (EARGM) algorithm is developed for segmentation of SAR and optical data. Edge detection using a Sobel filter is applied on SAR and optical data individually, and a majority voting approach is used to integrate all edge images. The edges are then used in a segmentation process to ensure that segments do not grow over edges. The segmentation is influenced by minimum and maximum segment sizes as well as the two homogeneity criteria, namely, a measure of color and a measure of texture. The classification is performed using support vector machines. The results show that our EARGM algorithm produces better segmentation than eCognition, particularly for built-up classes and linear features. The best classification result (80%) is achieved using the fusion of eight-date ENVISAT ASAR and HJ-1B data. This represents 5%, 11%, and 14% improvements over eCognition, HJ-1B, and ASAR classifications, respectively. The second best classification is achieved using fusion of four-date ENVISAT ASAR and HJ-1B data (78%). The result indicates that fewer multitemporal SAR images can achieve similar classification accuracy if multitemporal multiangle dual-look-direction SAR data are carefully selected. Numéro de notice : A2013-213 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2236560 En ligne : https://doi.org/10.1109/TGRS.2012.2236560 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32351
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 4 Tome 1 (April 2013) . - pp 1998 - 2006[article]Soil moisture estimation under low vegetation cover using a multi-angular polarimetric decomposition / Thomas Jaghuber in IEEE Transactions on geoscience and remote sensing, vol 51 n° 4 Tome 2 (April 2013)
[article]
Titre : Soil moisture estimation under low vegetation cover using a multi-angular polarimetric decomposition Type de document : Article/Communication Auteurs : Thomas Jaghuber, Auteur ; Irena Hajnsek, Auteur ; Axel Bronstert, Auteur ; Konstantinos Panagiotis Papathanassiou, Auteur Année de publication : 2013 Article en page(s) : pp 2201 - 2215 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] bande L
[Termes IGN] couvert végétal
[Termes IGN] décomposition d'image
[Termes IGN] diffusion du rayonnement
[Termes IGN] humidité du sol
[Termes IGN] image E-SAR
[Termes IGN] image radar moirée
[Termes IGN] polarimétrie radar
[Termes IGN] rétrodiffusion
[Termes IGN] surface cultivéeRésumé : (Auteur) The estimation of volumetric soil moisture under low agricultural vegetation from fully polarimetric synthetic aperture radar (SAR) data at L-band using a multi-angular polarimetric decomposition is investigated. Radar polarimetry provides the framework to decompose the backscattered signal into different canonical scattering mechanisms referring to scattering contributions from the underlying soil and the vegetation cover. Multi-angular observation diversity further increases the information space for soil moisture inversion enabling higher inversion rates and a stable inversion performance. The developed approach was applied on the multi-angular L-band data set acquired by German Aerospace Center's ESAR sensor as part of the OPAQUE campaign in 2008. The obtained results are compared against ground measurements collected by the OPAQUE team over a variety of vegetated agricultural fields. The validation of the estimated against ground measured soil moisture results in an root mean square error level of 6–8 vol.% including all test fields with a variety of crop types. Numéro de notice : A2013-222 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2209433 En ligne : https://doi.org/10.1109/TGRS.2012.2209433 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32360
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 4 Tome 2 (April 2013) . - pp 2201 - 2215[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2013041B RAB Revue Centre de documentation En réserve L003 Disponible Soil water balance performs better than climatic water variables in tree species distribution modelling / Christian Piedallu in Global ecology and biogeography, vol 22 n° 4 (April 2013)
[article]
Titre : Soil water balance performs better than climatic water variables in tree species distribution modelling Type de document : Article/Communication Auteurs : Christian Piedallu, Auteur ; Jean-Claude Gégout, Auteur ; Vincent Perez, Auteur ; François Lebourgeois, Auteur Année de publication : 2013 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Végétation
[Termes IGN] bilan hydrique
[Termes IGN] biogéographie
[Termes IGN] carte pédologique
[Termes IGN] changement climatique
[Termes IGN] espèce végétale
[Termes IGN] phytogéographie
[Termes IGN] Quercus pedunculata
[Termes IGN] Quercus pubescens
[Termes IGN] répartition géographique
[Termes IGN] système d'information géographiqueRésumé : (auteur) Aim: Soil water is essential for the physiological processes of plant growth and fitness. Owing to the difficulty of assessing wide variations in soil water reserves, plant distribution models usually estimate available water for plants through such climatic proxies as precipitation data (P) or climatic water balance (P minus potential evapotranspiration). We evaluated the ability of simple climatic proxies and soil water balance indices to predict the ecological niches of forest tree species.
Location: France
Methods: Soil water content and deficits were computed and mapped at a resolution of 1 × 1 km throughout France. The predictive abilities of these indices were compared to those of P and climatic water balance to model the distributions of 37 of the most common European tree species. We focused on two species with contrasting water tolerance, Quercus robur and Quercus pubescens, to illustrate the differences between climatic proxies and soil water balance in species response curves and distribution maps.
Results: Throughout France, soil water content was poorly correlated with P and climatic water balance, because low P in the lowlands can be compensated for by water provided by deeper soils, which is not the case in most mountainous areas. Soil water balance performed better than simple climatic water variables for explaining tree species distribution, improving 82% of the models for hygrophilous, meso-hygrophilous, meso-xerophilous, and meso-xerophilous species. Main conclusions: Our results showed that simple climatic values do not accurately represent available water for trees and that soil water balance indices perform better than do climatic proxies for most species. This point is crucial in avoiding underestimating the importance of water in studies aiming to determine the ecological niches of plant species and their responses to climate change.Numéro de notice : A2013-784 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1111/geb.12012 En ligne : https://doi.org/10.1111/geb.12012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75719
in Global ecology and biogeography > vol 22 n° 4 (April 2013)[article]Documents numériques
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