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A hybrid classification scheme for mining multisource geospatial data / R. Vatsavai in Geoinformatica, vol 15 n° 1 (January 2011)
[article]
Titre : A hybrid classification scheme for mining multisource geospatial data Type de document : Article/Communication Auteurs : R. Vatsavai, Auteur ; B. Bhaduri, Auteur Année de publication : 2011 Article en page(s) : pp 29 - 47 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage semi-dirigé
[Termes IGN] classification de Dempster-Shafer
[Termes IGN] classification hybride
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] données auxiliaires
[Termes IGN] exploration de données géographiques
[Termes IGN] image Landsat
[Termes IGN] image multibande
[Termes IGN] précision de la classificationRésumé : (Auteur) Supervised learning methods such as Maximum Likelihood (ML) are often used in land cover (thematic) classification of remote sensing imagery. ML classifier relies exclusively on spectral characteristics of thematic classes whose statistical distributions (class conditional probability densities) are often overlapping. The spectral response distributions of thematic classes are dependent on many factors including elevation, soil types, and ecological zones. A second problem with statistical classifiers is the requirement of the large number of accurate training samples (10 to 30 * |dimensions|), which are often costly and time consuming to acquire over large geographic regions. With the increasing availability of geospatial databases, it is possible to exploit the knowledge derived from these ancillary datasets to improve classification accuracies even when the class distributions are highly overlapping. Likewise newer semi-supervised techniques can be adopted to improve the parameter estimates of the statistical model by utilizing a large number of easily available unlabeled training samples. Unfortunately, there is no convenient multivariate statistical model that can be employed for multisource geospatial databases. In this paper we present a hybrid semi-supervised learning algorithm that effectively exploits freely available unlabeled training samples from multispectral remote sensing images and also incorporates ancillary geospatial databases. We have conducted several experiments on Landsat satellite image datasets, and our new hybrid approach shows over 24% to 36% improvement in overall classification accuracy over conventional classification schemes. Numéro de notice : A2011-027 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s10707-010-0113-4 Date de publication en ligne : 22/07/2010 En ligne : https://doi.org/10.1007/s10707-010-0113-4 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30808
in Geoinformatica > vol 15 n° 1 (January 2011) . - pp 29 - 47[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 057-2011011 RAB Revue Centre de documentation En réserve L003 Disponible Semantic web services-based process planning for earth science applications / P. Yue in International journal of geographical information science IJGIS, vol 23 n°9-10 (september 2009)
[article]
Titre : Semantic web services-based process planning for earth science applications Type de document : Article/Communication Auteurs : P. Yue, Auteur ; W. Yang, Auteur ; et al., Auteur Année de publication : 2009 Article en page(s) : pp 1139 - 1163 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] datation
[Termes IGN] implémentation (informatique)
[Termes IGN] intelligence artificielle
[Termes IGN] modélisation
[Termes IGN] ontologie
[Termes IGN] processus
[Termes IGN] service web géographique
[Termes IGN] service web sémantiqueRésumé : (Auteur) In a Web service-based distributed environment, individual services must be chained together dynamically to solve a complex real world problem. The Semantic Web Service has shown promise for automatic chaining of Web services. This paper addresses semi-automatic geospatial service chaining through Semantic Web Services-based process planning. Process planning includes three phases: process modeling, process model instantiation and workflow execution. Ontologies and Artificial Intelligence (AI) planning methods are employed in process planning to help a user dynamically create an executable workflow for earth science applications. In particular, the approach was implemented in a common data and service environment enabled by interoperable standards from OGC and W3C. A case study of the chaining process for wildfire prediction illustrates the applicability of this approach. Copyright Taylor & Francis Numéro de notice : A2009-383 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658810802032680 En ligne : https://doi.org/10.1080/13658810802032680 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=30013
in International journal of geographical information science IJGIS > vol 23 n°9-10 (september 2009) . - pp 1139 - 1163[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-09061 RAB Revue Centre de documentation En réserve L003 Disponible Global elevation ancillary data for land-use classification using granular neural networks / D. Stathakis in Photogrammetric Engineering & Remote Sensing, PERS, vol 74 n° 1 (January 2008)
[article]
Titre : Global elevation ancillary data for land-use classification using granular neural networks Type de document : Article/Communication Auteurs : D. Stathakis, Auteur ; I. Kanellopoulos, Auteur Année de publication : 2008 Article en page(s) : pp 55 - 63 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] altitude
[Termes IGN] classification floue
[Termes IGN] classification par réseau neuronal
[Termes IGN] données auxiliaires
[Termes IGN] fusion d'images
[Termes IGN] granularité d'image
[Termes IGN] logique floue
[Termes IGN] utilisation du solRésumé : (Auteur) The development of digital global databases containing data such as elevation and soil can greatly simplify and aid in the classification of remotely sensed data to create land-use classes. An efficient method that can simultaneously handle diverse input dimensions can be formed by merging fuzzy logic and neural networks. The so-called granular or fuzzy neural networks are able not only to achieve high classification levels, but at the same time produce compressed and transparent neural network skeletons. Compression results in reduced training times, while transparency is an aid for interpreting the structure of the neural network by translating it into meaningful rules and vice versa. The purpose of this paper is to provide some initial guidelines for the construction of granular neural networks in the remote sensing context, while using global elevation ancillary data within the classification process. Copyright ASPRS Numéro de notice : A2008-014 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.74.1.55 En ligne : https://doi.org/10.14358/PERS.74.1.55 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29009
in Photogrammetric Engineering & Remote Sensing, PERS > vol 74 n° 1 (January 2008) . - pp 55 - 63[article]Identifying erosion areas at basin scale using remote sensing data and GIS: a case study in a geologically complex mountain basin in the Spanish Pyrenees / S. Begueria in International Journal of Remote Sensing IJRS, vol 27 n°18 - 19 - 20 (October 2006)
[article]
Titre : Identifying erosion areas at basin scale using remote sensing data and GIS: a case study in a geologically complex mountain basin in the Spanish Pyrenees Type de document : Article/Communication Auteurs : S. Begueria, Auteur Année de publication : 2006 Article en page(s) : pp 4585 - 4598 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] bassin hydrographique
[Termes IGN] carte géologique
[Termes IGN] cartographie écologique
[Termes IGN] données auxiliaires
[Termes IGN] érosion
[Termes IGN] Espagne
[Termes IGN] image Landsat-ETM+
[Termes IGN] image Landsat-TM
[Termes IGN] lithologie
[Termes IGN] prédiction
[Termes IGN] Pyrénées (montagne)
[Termes IGN] régression linéaire
[Termes IGN] sédiment
[Termes IGN] système d'information géographiqueRésumé : (Auteur) Inventory and monitoring of eroded areas at basin scale (Mm2) can be very useful for environmental planning and can help to reduce land degradation and sediment yield to streams. Combined use of remote sensing images and auxiliary geocoded data has been widely used for mapping various environmental features, including surface erosion. Here an example is presented in the Yesa reservoir catchment in the Spanish Pyrenees. Several combinations of radiometric data (a sequence of images from different seasons of the year) and other geocoded information, including topographical (altitude and slope) and geological maps, were compared in their ability to predict previously identified erosive features. Multinomial logistic regression was used as the classification method. The datasets were compared in terms of classification error statistics (sensitivity and specificity) using an independent random sample. The incorporation of lithological information improved the discrimination of eroded areas, but the same did not happen in the case of topographical information. Two final maps of eroded areas were obtained applying an equal predicted area rule and an equal error rate rule. Copyright Taylor & Francis Numéro de notice : A2006-469 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160600735640 En ligne : https://doi.org/10.1080/01431160600735640 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28193
in International Journal of Remote Sensing IJRS > vol 27 n°18 - 19 - 20 (October 2006) . - pp 4585 - 4598[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 080-06101 RAB Revue Centre de documentation En réserve L003 Disponible Incorporating 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)
[article]
Titre : Incorporating domain knowledge and spatial relationships into land cover classifications: a rule-based approach Type de document : Article/Communication Auteurs : A.E. Daniels, Auteur Année de publication : 2006 Article en page(s) : pp 2949 - 2975 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] carte d'occupation du sol
[Termes IGN] classe d'objets
[Termes IGN] classification à base de connaissances
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] données auxiliaires
[Termes IGN] feuillu
[Termes IGN] forêt tropicale
[Termes IGN] interprétation automatique
[Termes IGN] occupation du sol
[Termes IGN] précision de la classificationRésumé : (Auteur) For some tropical regions, remote sensing of land cover yields unacceptable results, particularly as the number of land cover classes increases. This research explores the utility of incorporating domain knowledge and multiple algorithms into land cover classifications via a rule-based algorithm for a series of satellite images. The proposed technique integrates the fundamental, knowledge-based interpretation elements of remote sensing without sacrificing the ease and consistency of automated, algorithm-based processing. Compared with results from a traditional maximum likelihood algorithm, classification accuracy was improved substantially for each of the six land cover classes and all three years in the image series. Use of domain knowledge proved effective in accurately classifying problematic tropical land covers, such as tropical deciduous forest and seasonal wetlands. Results also suggest that ancillary data may be most useful in the classification of historic images, where the greatest improvement was observed relative to results from maximum likelihood. The cost of incorporating contextual knowledge and extensive spatial data sets may be justified, since results from the proposed technique suggest a considerable improvement in accuracy may be achieved. Copyright Taylor & Francis Numéro de notice : A2006-310 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160600567753 En ligne : https://doi.org/10.1080/01431160600567753 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28034
in International Journal of Remote Sensing IJRS > vol 27 n°12-13-14 (July 2006) . - pp 2949 - 2975[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 080-06071 RAB Revue Centre de documentation En réserve L003 Disponible A method for detecting large-scale forest covers change using coarse spatial resolution imagery / R.H. Fraser in Remote sensing of environment, vol 95 n° 4 (30/04/2005)PermalinkUpdating land cover classification using a rule-based decision system / Damien Raclot in International Journal of Remote Sensing IJRS, vol 26 n° 7 (April 2005)PermalinkLand-cover change monitoring with classification trees using Landsat TM and ancillary data / J. Rogan in Photogrammetric Engineering & Remote Sensing, PERS, vol 69 n° 7 (July 2003)PermalinkAnalyse multidate et multiresolution pour l'étude de la productivité végétale en zone climatique tempérée : bassin versant "arroyo Sanchez", Uruguay / F. Anno in Bulletin [Société Française de Photogrammétrie et Télédétection], n° 170 (Avril 2003)PermalinkFusion d'informations en traitement du signal et des images / Isabelle Bloch (2003)PermalinkRemote sensing and spatial data: the establishment and visualisation of 3D computer landscape models as basis for visual impact assessment / B. Koch in GIS Geo-Informations-Systeme, vol 2001 n° 12 (Dezember 2001)PermalinkProgress in the development of a high performance airborne digital sensor / P. Fricker in Photogrammetric record, vol 16 n° 96 (October 2000 - March 2001)PermalinkCaractérisation des directions de visée / Roland Gachet in Bulletin [Société Française de Photogrammétrie et Télédétection], n° 159 (Juillet 2000)PermalinkDevelopment of models for monitoring the urban environment using radar remote sensing / Catherine Ticehurst (1998)PermalinkSAR images and ancillary data in crop species interpretation / Leena Matikainen (1998)Permalink