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GIS and high resolution Spot imagery evaluating the impact of urbanization on agricultural lands / H. Anys in Geocarto international, vol 17 n° 3 (September - November 2002)
[article]
Titre : GIS and high resolution Spot imagery evaluating the impact of urbanization on agricultural lands Type de document : Article/Communication Auteurs : H. Anys, Auteur ; Dong-Chen He, Auteur ; N. Bijaber, Auteur ; A. Bannari, Auteur Année de publication : 2002 Article en page(s) : pp 35 - 41 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] aide à la décision
[Termes IGN] carte d'occupation du sol
[Termes IGN] cartographie statistique
[Termes IGN] classification
[Termes IGN] image panchromatique
[Termes IGN] image SPOT
[Termes IGN] occupation du sol
[Termes IGN] surface cultivée
[Termes IGN] système d'information géographique
[Termes IGN] urbanisationRésumé : (Auteur) This study advocates the use of GIS and remote sensing technologies to establish urban evolution maps and assess the impact of urbanization on agricultural areas over the last three decades. The target area is the city of BeniMellal, located in central Morocco. The methodology adopted makes use of panchromatic SPOT images to survey the urban areas during the 1980s and 1990s. Available topographic maps provided the information for the 1970s. Maps and statistics of land use and urban growth for Beni Mellal were established after manually classifying images on a perpolygon basis and digitizing topographic maps using GIS capabilities. The results show an increase in dense urban area by 980.7 ha from the 1970s to the 1990s. This increase occurred at the expense of forests (24.7 ha), plantations (752.3 ha), rangeland (113.4 ha), nonirrigated land (69.7 ha), and irrigated land (20.6 ha). During this period, scattered urban areas, predominantly suburbs, increased by 755.9 ha to the detriment of forests (14.9 ha), plantations (109.8 ha), rangeland (138.9 ha), nonirrigated land (400.5 ha), and irrigated land (91.9 ha). These cartographic and statistic results are efficient decisionmaking tools for protecting agricultural land and planning urban and suburban areas. Numéro de notice : A2002-285 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106040208542242 En ligne : https://doi.org/10.1080/10106040208542242 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22196
in Geocarto international > vol 17 n° 3 (September - November 2002) . - pp 35 - 41[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-02031 RAB Revue Centre de documentation En réserve L003 Disponible Impact of contextual information integration on pixel fusion / Sophie Fabre in IEEE Transactions on geoscience and remote sensing, vol 40 n° 9 (September 2002)
[article]
Titre : Impact of contextual information integration on pixel fusion Type de document : Article/Communication Auteurs : Sophie Fabre, Auteur ; Xavier Briottet , Auteur ; A. Appriou, Auteur Année de publication : 2002 Article en page(s) : pp 1997 - 2010 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] classificateur non paramétrique
[Termes IGN] classification de Dempster-Shafer
[Termes IGN] fusion d'images
[Termes IGN] méthode
[Termes IGN] pixel
[Termes IGN] prise en compte du contexte
[Termes IGN] théorie de Dempster-Shafer
[Termes IGN] vapeur d'eauRésumé : (Auteur) Pixel fusion is used to elaborate a classification method at pixel level. It needs to take into account the more accurate as possible information and take advantage of the statistical learning of the previous measurements acquired by sensors. The classical probabilistic fusion methods lack performance when the previous learning is not representative of the real measurements provided by sensors. The DempsterShafer theory is then introduced to face this disadvantage by integrating a further information which is the context of the sensor acquisitions. In this paper, we propose a formalism of modeling of the sensor reliability to the context that leads to two methods of integration: the first one amounts to integrate this further information in the fusion rule as degrees of trust and the second models the sensor reliability directly as mass function. These two methods are compared in the case where the sensor reliability depends on an atmospheric disturbance : the water vapor. Numéro de notice : A2002-288 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2002.805143 En ligne : https://doi.org/10.1109/TGRS.2002.805143 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22199
in IEEE Transactions on geoscience and remote sensing > vol 40 n° 9 (September 2002) . - pp 1997 - 2010[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-02081 RAB Revue Centre de documentation En réserve L003 Disponible Land cover classification models using Shuttle Imaging Radar (SIR-C) data: a case study in New Hampshire, USA / R. Narayanan in Geocarto international, vol 17 n° 3 (September - November 2002)
[article]
Titre : Land cover classification models using Shuttle Imaging Radar (SIR-C) data: a case study in New Hampshire, USA Type de document : Article/Communication Auteurs : R. Narayanan, Auteur ; Jing Zhang, Auteur Année de publication : 2002 Article en page(s) : pp 57 - 65 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] classification dirigée
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] classification par réseau neuronal
[Termes IGN] covariance
[Termes IGN] fréquence
[Termes IGN] image radar
[Termes IGN] image SIR-C
[Termes IGN] New Hampshire (Etats-Unis)
[Termes IGN] occupation du sol
[Termes IGN] polarisation
[Termes IGN] précision de la classification
[Termes IGN] réalité de terrain
[Termes IGN] varianceRésumé : (Auteur) Spaceborne synthetic aperture radar (SAR) systems have the ability to provide high resolution information on land cover characteristics under adverse conditions such as darkness or cloud cover. The use of multiple frequencies and multiple polarizations yields better classification accuracies. The results of various land cover classification algorithms using Shuttle Imaging Radar (SIR-C) SAR data as applied to a site in Suncook, New Hampshire, are described in this paper. Three classification models were developed and tested: minimum distance classification, maximum a posteriori probability classification, and neural network classification. Using the available ground truth information, land cover was classified into five distinct regions: water, swamp, sand, trees, and grass. All three methods were applied to the same site and results compared. The maximum a posteriori probability approach yielded the highest overall classification accuracy on a pixelbypixel basis. Although the minimum distance approach was simpler than the maximum a posteriori approach, its performance was not as good as the latter since it did not use the covariance information between the data channels. The neural network approach performed well and its results were comparable to the maximum a posteriori approach when the variance of the data was small; however, its performance degraded rapidly when the variance of the data was high. Numéro de notice : A2002-286 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106040208542245 En ligne : https://doi.org/10.1080/10106040208542245 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22197
in Geocarto international > vol 17 n° 3 (September - November 2002) . - pp 57 - 65[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-02031 RAB Revue Centre de documentation En réserve L003 Disponible A multiple-cascade-classifier system for a robust and partially unsupervised updating of land-cover maps / Lorenzo Bruzzone in IEEE Transactions on geoscience and remote sensing, vol 40 n° 9 (September 2002)
[article]
Titre : A multiple-cascade-classifier system for a robust and partially unsupervised updating of land-cover maps Type de document : Article/Communication Auteurs : Lorenzo Bruzzone, Auteur ; R. Cossu, Auteur Année de publication : 2002 Article en page(s) : pp 1984 - 1996 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification non dirigée
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] classification par réseau neuronal
[Termes IGN] image multitemporelle
[Termes IGN] mise à jour cartographiqueRésumé : (Auteur) A system for a regular updating of landcover maps is proposed that is based on the use of multitemporal remote sensing images. Such a system is able to address the updating problem under the realistic but critical constraint that, for the image to be classified (i.e., the most recent of the considered multitemporal dataset no ground truth information is available. The system is composed of an ensemble of partially unsupervised classifiers integrated in a multipleclassifier architecture. Each classifier of the ensemble exhibits the following novel characteristics: 1) it is developed in the framework of the cascade-classification approach to exploit the temporal correlation existing between images acquired at different times in the considered area; and 2) it is based on a partially unsupervised methodology capable of accomplishing the classification process under the aforementioned critical constraint. Both a parametric maximumlikelihood (ML) classification approach and a nonparametric radial basis function (RBF) neuralnetwork classification approach are used as basic methods for the development of partially unsupervised cascade classifiers. In addition, in order to generate an effective ensemble of classification algorithms, hybrid ML and RBF neuralnetwork cascade classifiers are defined by exploiting the characteristics of the cascadeclassification methodology. The results yielded by the different classifiers are combined by using standard unsupervised combination strategies. This allows the definition of a robust and accurate partially unsupervised classification system capable of analyzing a wide typology of remote sensing data (e.g., images acquired by passive sensors, synthetic aperture radar images, and multisensor and multisource data). Experimental results obtained on a real multitemporal and multisource dataset confirm the effectiveness of the proposed system. Numéro de notice : A2002-287 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2002.803794 En ligne : https://doi.org/10.1109/TGRS.2002.803794 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22198
in IEEE Transactions on geoscience and remote sensing > vol 40 n° 9 (September 2002) . - pp 1984 - 1996[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-02081 RAB Revue Centre de documentation En réserve L003 Disponible Spatial data mining for enhanced soil map modelling / C.J. Moran in International journal of geographical information science IJGIS, vol 16 n° 6 (september 2002)
[article]
Titre : Spatial data mining for enhanced soil map modelling Type de document : Article/Communication Auteurs : C.J. Moran, Auteur ; E. Bui, Auteur Année de publication : 2002 Article en page(s) : pp 533 - 549 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Information géographique
[Termes IGN] base de données localisées
[Termes IGN] cartographie thématique
[Termes IGN] classification
[Termes IGN] exploration de données
[Termes IGN] modèle conceptuel de données
[Termes IGN] occupation du solRésumé : (Auteur) The principle of using induction rules based on spatial environmental data to model a soil map has previously been demonstrated. Whilst the general pattern of classes of large spatial extent and those with close association with geology were delineated, small classes and the detailed spatial pattern of the map were less well rendered. Here we examine several strategies to improve the quality of the soil map models generated by rule induction. Terrain attributes that are bettersuited to landscape description at a resolution of 250m are introduced as predictors of soil type. A map sampling strategy is developed. Classification error is reduced by using boosting rather than crossvalidation to improve the model. Further, the benefit of incorporating the local spatial context for each environmental variable into the rule induction is examined. The best model was achieved by sampling in proportion to the spatial extent of the mapped classes, boosting the decision trees, and using spatial contextual information extracted from the environmental variables. Numéro de notice : A2002-194 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/13658810210138715 En ligne : https://doi.org/10.1080/13658810210138715 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22109
in International journal of geographical information science IJGIS > vol 16 n° 6 (september 2002) . - pp 533 - 549[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-02061 RAB Revue Centre de documentation En réserve L003 Disponible Techniques for mapping suburban sprawl / J. Epstein in Photogrammetric Engineering & Remote Sensing, PERS, vol 68 n° 9 (September 2002)PermalinkEvaluation of SAR-optical imagery synthesis techniques in a complex coastal ecosystem / F.M. Henderson in Photogrammetric Engineering & Remote Sensing, PERS, vol 68 n° 8 (August 2002)PermalinkExperimental evaluation of positional accuracy estimates from linear network using point- and line-based testing methods / T.G. Van Niel in International journal of geographical information science IJGIS, vol 16 n° 5 (july 2002)PermalinkIntegration of classification methods for improvement of land-cover map accuracy / XiaoHang Liu in ISPRS Journal of photogrammetry and remote sensing, vol 56 n° 4 (July - August 2002)PermalinkAn experimental study on content-based image classication for image databases / R.D. Holowczak in IEEE Transactions on geoscience and remote sensing, vol 40 n° 6 (June 2002)PermalinkAnomaly detection and classification for hyperspectral imagery / C.I. Chang in IEEE Transactions on geoscience and remote sensing, vol 40 n° 6 (June 2002)PermalinkCognitive geometry for cartography / J. Comenetz in Cartographic journal (the), vol 39 n° 1 (June 2002)PermalinkComparative evaluation of Indian remote sensing multi-spectral sensors data for crop classification / R.P. Singh in Geocarto international, vol 17 n° 2 (June - August 2002)PermalinkÉtude par télédétection aéroportée d’un environnement lagunaire en zone tropicale : cas de la lagune Ébrié en Côte d’Ivoire / Éric Valère Djagoua in Télédétection : revue de recherche et d'application en télédétection, vol 2 n° 4 ([01/06/2002])PermalinkFusion radar and optical data for land cover mapping / Nathaniel D. Herold in Geocarto international, vol 17 n° 2 (June - August 2002)Permalink