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Modelling and mapping potential hooded warbler (Wilsonia citrina) habitat using remotely sensed imagery / J. Pasher in Remote sensing of environment, vol 107 n° 3 (12 April 2007)
[article]
Titre : Modelling and mapping potential hooded warbler (Wilsonia citrina) habitat using remotely sensed imagery Type de document : Article/Communication Auteurs : J. Pasher, Auteur ; Dominique King, Auteur ; K. Lindsay, Auteur Année de publication : 2007 Article en page(s) : pp 471 - 483 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Aves
[Termes IGN] carte thématique
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] habitat animal
[Termes IGN] image Ikonos
[Termes IGN] image Landsat
[Termes IGN] luminance lumineuse
[Termes IGN] Ontario (Canada)
[Termes IGN] photo-interprétation
[Termes IGN] précision de la classification
[Termes IGN] régression logistiqueRésumé : (Auteur) Modelling and mapping of hooded warbler (Wilsonia citrina) nesting habitat in forests of southern Ontario were conducted using Ikonos and Landsat data. The study began with an analysis of skyward hemispherical photography to determine canopy characteristics associated with nest sites. It showed that nest sites had significantly less overhead canopy cover and larger maximum gap size than in non-nest areas. These findings led to the hypothesis that brightness variability in high to moderate resolution remotely sensed imagery may be greater at nest sites than in non-nest areas due to larger shadows and greater shadow variability related to these gap characteristics. This was confirmed when, in addition to some spectral band brightness variables, several image texture and spectrally unmixed fraction (shadow, bare soil) variables were found to be significantly different for nest and non-nest sites in Ikonos and Landsat imagery. These significantly different variables were used in maximum likelihood classification (MLC) and logistic regression (LR) to produce maps of potential nesting habitat. Mapping was conducted with Ikonos and Landsat in a local area where most known nest sites occur, and regionally using Landsat data for almost all of the hooded warbler range in southern Ontario. For the local area mapping using Ikonos data, a posteriori probabilities for both the MLC and LR methods showed that about 62% of the nest sites set aside for validation had been classified with high probability (p > 0.70) in the nest class. MLC mapping accuracy was 70% for the validation nest sites and 87% of validation nest sites were within 10 m of classified nesting habitat, a distance approximately equivalent to expected positional error in the data. LR accuracy was slightly lower. Nest site MLC mapping accuracy in the local area using Landsat data was 87% but the map was much coarser due to the larger pixel size. Regional mapping with Landsat imagery produced lower classification accuracy due to high errors of commission for the habitat class. This resulted from a poor spatial distribution and low number of observations of nest sites throughout the region compared to the local area, while the non-nest site data distribution was too narrow, having been defined and assessed (using standard accepted methods) as areas with no ground shrubs. If either of these problems can be ameliorated, regional mapping accuracy may improve. Copyright Elsevier Numéro de notice : A2007-139 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2006.09.022 En ligne : https://doi.org/10.1016/j.rse.2006.09.022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28502
in Remote sensing of environment > vol 107 n° 3 (12 April 2007) . - pp 471 - 483[article]Comparison between several feature extraction/classification methods for mapping complicated agricultural land use patches using airborne hyperspectral data / S. Lu in International Journal of Remote Sensing IJRS, vol 28 n°5-6 (March 2007)
[article]
Titre : Comparison between several feature extraction/classification methods for mapping complicated agricultural land use patches using airborne hyperspectral data Type de document : Article/Communication Auteurs : S. Lu, Auteur ; K. Oki, Auteur Année de publication : 2007 Article en page(s) : pp 963 - 984 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] agriculture
[Termes IGN] analyse comparative
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification dirigée
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] extraction automatique
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] image aérienne
[Termes IGN] image hyperspectrale
[Termes IGN] précision de la classification
[Termes IGN] surface cultivée
[Termes IGN] Tokyo (Japon)
[Termes IGN] utilisation du solRésumé : (Auteur) Airborne hyperspectral remote sensing was applied to agricultural land in the Miura Peninsula, near the metropolis of Tokyo in Japan. The study area is characterized by complicated land use patches, which is the general characteristic of most agricultural lands in Japan. Several feature extraction/classification methods were examined in classifying the land use and plant species. The results showed that decision boundary feature extraction (DBFE) was better than principal component analysis (PCA) as the feature extraction method. Moreover, the pre-classification process using NDVI that separates the whole study area into vegetated area and non-vegetated areas also improved the classification accuracy. After the pre-procedures, the land use and plant species were finally mapped by maximum likelihood classification (MLC) or extraction and classification of homogeneous objects (ECHO). The best kappa (overall accuracy) of classification was 0.914 (92.4%) and 0.924 (93.3%) for MLC and ECHO, respectively. The best accuracies of each category for the image were 79.5% to 100% for plant species (watermelon, pumpkin, marigold, grass and tree), 88.7% to 100% for soil types, 97.8% for concrete, and 99.4% for vinyl-mulches. Although, built-up area has low estimation accuracy, this did not affect the overall classification accuracy because it covers only a very small area. Copyright Taylor & Francis Numéro de notice : A2007-097 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160600771561 En ligne : https://doi.org/10.1080/01431160600771561 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28462
in International Journal of Remote Sensing IJRS > vol 28 n°5-6 (March 2007) . - pp 963 - 984[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 080-07031 RAB Revue Centre de documentation En réserve L003 Disponible Terrestrial and submerged aquatic vegetation mapping in Fire Island national seashore using high spatial resolution remote sensing data / Y. Wang in Marine geodesy, vol 30 n° 1-2 (March - June 2007)
[article]
Titre : Terrestrial and submerged aquatic vegetation mapping in Fire Island national seashore using high spatial resolution remote sensing data Type de document : Article/Communication Auteurs : Y. Wang, Auteur ; M. Traber, Auteur ; B. Milstead, Auteur ; S. Stevens, Auteur Année de publication : 2007 Article en page(s) : pp 77 - 95 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] carte de la végétation
[Termes IGN] classification dirigée
[Termes IGN] données bathymétriques
[Termes IGN] ERDAS Imagine
[Termes IGN] extraction automatique
[Termes IGN] herbier marin
[Termes IGN] image à très haute résolution
[Termes IGN] image Quickbird
[Termes IGN] image vidéo
[Termes IGN] littoral
[Termes IGN] parc naturel national
[Termes IGN] photographie sous-marine
[Termes IGN] plante aquatique d'eau salée
[Termes IGN] plante halophile
[Termes IGN] précision de la classification
[Termes IGN] Rhode Island (Etats-Unis)Résumé : (Auteur) The vegetation communities and spatial patterns on the Fire Island National Seashore are dynamic as the result of interactions with driving forces such as sand deposition, storm-driven over wash, salt spray, surface water, as well as with human disturbances. We used high spatial resolution QuickBird-2 satellite remote sensing data to map both terrestrial and submerged aquatic vegetation communities of the National Seashore. We adopted a stratified classification and unsupervised classification approach for mapping terrestrial vegetation types. Our classification scheme included detailed terrestrial vegetation types identified by previous vegetation mapping efforts of the National Park Service and three generalized categories of high-density seagrass, low-density seagrass coverages, and unvegetated bottom to map the submerged aquatic vegetation habitats. We used underwater videography, GPS-guided field reference photography, and bathymetric data to support remote sensing image classification and information extraction. This study achieved approximately 82% and 75% overall classification accuracy for the terrestrial and submerged aquatic vegetations, respectively, and provided an updated vegetation inventory and change analysis for the Northeast Coastal and Barrier Network of the National Park Service. Copyright Taylor & Francis Numéro de notice : A2007-436 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1080/01490410701296226 En ligne : https://doi.org/10.1080/01490410701296226 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28799
in Marine geodesy > vol 30 n° 1-2 (March - June 2007) . - pp 77 - 95[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 230-07011 RAB Revue Centre de documentation En réserve L003 Disponible Extraction of spectral channels from hyperspectral images for classification purposes / S.B. Serpico in IEEE Transactions on geoscience and remote sensing, vol 45 n° 2 (February 2007)
[article]
Titre : Extraction of spectral channels from hyperspectral images for classification purposes Type de document : Article/Communication Auteurs : S.B. Serpico, Auteur ; G. Moser, Auteur Année de publication : 2007 Article en page(s) : pp 484 - 495 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] bande spectrale
[Termes IGN] classification dirigée
[Termes IGN] extraction
[Termes IGN] image hyperspectrale
[Termes IGN] précision de la classificationRésumé : (Auteur) This paper proposes a procedure to extract spectral channels of variable bandwidths and spectral positions from the hyperspectral image in such a way as to optimize the accuracy for a specific classification problem. In particular, each spectral channel ("s-band") is obtained by averaging a group of contiguous channels of the hyperspectral image ("h-bands"). Therefore, if one wants to define m s-bands, the problem can be formulated as the optimization of the related m starting and m ending h-bands. Toward this end, we propose to adopt, as an optimization criterion, an interclass distance computed on a training set and to generate a sequence of possible solutions by one of three possible search strategies. As the proposed formalization of the problem makes it analogous to a feature-selection problem, the proposed three strategies have been derived by modifying three feature-selection strategies, namely: 1) the "sequential forward selection", 2) the "steepest ascent," and 3) the "fast constrained search". Experimental results on a well-known hyperspectral data set confirm the effectiveness of the approach, which yields better results than other widely used methods. The importance of this kind of procedure lies in feature reduction for hyperspectral image classification or in the case-based design of the spectral bands of a programmable sensor. It represents a special case of feature extraction that is expected to be more powerful than feature selection. The kind of transformation used allows the interpretability of the new features (i.e., the spectral bands) to be saved. Copyright IEEE Numéro de notice : A2007-081 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2006.886177 En ligne : https://doi.org/10.1109/TGRS.2006.886177 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28446
in IEEE Transactions on geoscience and remote sensing > vol 45 n° 2 (February 2007) . - pp 484 - 495[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-07021 RAB Revue Centre de documentation En réserve L003 Disponible 065-07022 RAB Revue Centre de documentation En réserve L003 Disponible Assessing the effect of attribute uncertainty on the robustness of choropleth map classification / N. Xiao in International journal of geographical information science IJGIS, vol 21 n° 1-2 (january 2007)
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Titre : Assessing the effect of attribute uncertainty on the robustness of choropleth map classification Type de document : Article/Communication Auteurs : N. Xiao, Auteur ; C.A. Calder, Auteur ; Marc P. Armstrong, Auteur Année de publication : 2007 Article en page(s) : pp 121 - 144 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] attribut
[Termes IGN] carte choroplèthe
[Termes IGN] classification dirigée
[Termes IGN] incertitude des données
[Termes IGN] précision de la classification
[Termes IGN] visualisationRésumé : (Auteur) Choropleth maps are often used to visualize the spatial distribution of information collected for enumeration units. Such maps, however, are normally produced without considering the effect of uncertainty associated with data, which can contribute to incorrect interpretation. The purpose of this paper is to develop a method that can be used to evaluate the classification robustness of choropleth maps when the attribute uncertainty associated with the data is known or can be estimated. We first develop a measure to indicate the robustness of classification schemes. We then design a set of experiments to examine the robustness of different choropleth map classifications under various levels and types of uncertainty. Our experiments suggest that the robustness of a choropleth classification scheme is a function of uncertainty and the number of classes used. Increases in data uncertainty will decrease map robustness. However, it is possible to increase map robustness by choosing a smaller number of classes. We also discuss a visualization approach that can be used to display the classification robustness of each enumeration unit within a choropleth map. Numéro de notice : A2007-029 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658810600894307 En ligne : https://doi.org/10.1080/13658810600894307 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78189
in International journal of geographical information science IJGIS > vol 21 n° 1-2 (january 2007) . - pp 121 - 144[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-07011 RAB Revue Centre de documentation En réserve L003 Disponible 079-07012 RAB Revue Centre de documentation En réserve L003 Disponible Comparison of pixel-based and object-oriented image classification approaches: a case study in a coal fire area, Wuda, Inner Mongolia, China / G. Yan in International Journal of Remote Sensing IJRS, vol 27 n°18 - 19 - 20 (October 2006)PermalinkLa transformation en ondelettes pour l'extraction de la texture-couleur : application à la classification combinée des images (HRV) de SPOT / A. Safia in International Journal of Remote Sensing IJRS, vol 27 n°18 - 19 - 20 (October 2006)PermalinkA pixel shape index coupled with spectral information for classification of high spatial resolution remotely sensed imagery / L. Zhang in IEEE Transactions on geoscience and remote sensing, vol 44 n° 10 Tome 2 (October 2006)PermalinkIncorporating domain knowledge and spatial relationships into land cover classifications: a rule-based approach / A.E. Daniels in International Journal of Remote Sensing IJRS, vol 27 n°12-13-14 (July 2006)PermalinkSome issues in the classification of DAIS hyperspectral data / M. Pal in International Journal of Remote Sensing IJRS, vol 27 n°12-13-14 (July 2006)PermalinkInterrelationships between spatial resolution and per-pixel classifiers for extracting information classes part 1: the urban environment / J.R. Jensen (29/03/2006)PermalinkParcel-based classification / J. Wijnant in GEO: Geoconnexion international, vol 5 n° 2 (february 2006)PermalinkEtude de différents facteurs influant les classifications d'images multi-résolution / F. Kazemipour (2006)PermalinkUsing satellite imagery and GIS for land-use and land-cover change mapping in an estuarine watershed / X. Yang in International Journal of Remote Sensing IJRS, vol 26 n° 23 (December 2005)PermalinkSpectral filtering and classification of terrestrial laser scanner point clouds / Derek D. Lichti in Photogrammetric record, vol 20 n° 111 (September - November 2005)Permalink