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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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A spectral and spatial source separation of multispectral images / M.A. Loghmari in IEEE Transactions on geoscience and remote sensing, vol 44 n° 12 (December 2006)
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Titre : A spectral and spatial source separation of multispectral images Type de document : Article/Communication Auteurs : M.A. Loghmari, Auteur ; Mohamed Saber Naceur, Auteur ; Mohamed-Rached Boussema, Auteur Année de publication : 2006 Article en page(s) : pp 3659 - 3673 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification bayesienne
[Termes IGN] données multisources
[Termes IGN] hétérogénéité
[Termes IGN] image multibande
[Termes IGN] occupation du sol
[Termes IGN] segmentation d'image
[Termes IGN] séparabilité
[Termes IGN] signature spectraleRésumé : (Auteur) This paper deals with the problem of blind source separation of remote sensing data based on a Bayesian estimation framework. We consider the case of multispectral images in which we have observed images of the same zone through different spectral bands. The land cover types existing in the scanned zone constitute the sources to separate. Associating each source to a specific significant theme remains the real challenge in the source-separation method applied to satellite images. In fact, multispectral images consist of multiple channels, each channel containing data acquired from different bands within the frequency spectrum. Since most objects emit or reflect energy over a large spectral bandwidth, there usually exists a significant correlation between channels. This constitutes the first difficulty for sources identification. The second difficulty lies in the heterogeneity of most of the geological and vegetative ground surfaces. In this case, the geometrical projection of a single detector element at the Earth's surface, which is sometimes called the instantaneous field of view, is formed from a mixture of spectral signatures. In such circumstances, the needed information is either not available or not reliable. In this paper, the goal is to establish a new approach based on a two-level source separation (TLSS), which consists of a spectral separation along the different used bands and a spatial separation along neighboring pixels of each image band. The spectral separation has been used prior to the Bayesian approach, and it is based on a second-order statistics approach that exploits the correlation through different spectral bands of the multispectral sensor. The given images are represented according to independent axes that provide more effective representation of the information within the observation images. The spectral separation consists of identifying the sources without resorting to any a priori information, hence the term blind. The obtained source-separation represent the starting point for the Bayesian approach, which is known for its weakness in front of initial conditions. To identify a significant theme for each source, we have to spatially separate each image based on a Bayesian source-separation framework. The proposed approach has the added advantages of the blind source method as well as the Bayesian method. It should give segmented images related to each theme covering the scanned zone, which are the TLSS results of the observation images. Copyright IEEE Numéro de notice : A2006-559 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2006.882261 En ligne : https://doi.org/10.1109/TGRS.2006.882261 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28282
in IEEE Transactions on geoscience and remote sensing > vol 44 n° 12 (December 2006) . - pp 3659 - 3673[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-06121 RAB Revue Centre de documentation En réserve L003 Disponible The national integrated land system [of USA] / Bruce Hedquist in Surveying and land information science, vol 66 n° 4 (01/12/2006)
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Titre : The national integrated land system [of USA] Type de document : Article/Communication Auteurs : Bruce Hedquist, Auteur Année de publication : 2006 Article en page(s) : pp 279 - 288 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Infrastructure de données
[Termes IGN] accès aux données localisées
[Termes IGN] cartographie par internet
[Termes IGN] données publiques
[Termes IGN] Etats-Unis
[Termes IGN] infrastructure nationale des données localisées
[Termes IGN] National integrated land system
[Termes IGN] occupation du sol
[Termes IGN] utilisation du solRésumé : (Auteur) There are billions of federal computer records that relate to the millions of acres of “public lands” in the United States. These records are administered by the U.S. Bureau of Land Management (BLM). In the late 1990s, a publicly funded effort was undertaken to develop a truly modern GIS, in order to help manage the extensive land holdings and data records in the U.S. It is called the National Integrated Land System, or NILS for short. This system is now accessible to the public for on-line searching, viewing, and eventual downloading of selected records. It also can be used to generate custom maps of selected lands. The following article describes NILS in mostly general terms. More detailed papers and articles can be found on the BLM website at www.blm.gov/nils/. Copyright SaLIS Numéro de notice : A2006-608 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28331
in Surveying and land information science > vol 66 n° 4 (01/12/2006) . - pp 279 - 288[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 121-06041 RAB Revue Centre de documentation En réserve L003 Disponible Documents numériques
en open access
The national integrated land system - pdf éditeurAdobe Acrobat PDFMultiple support vector machines for land cover change detection: an application for mapping urban extensions / H. Nemmour in ISPRS Journal of photogrammetry and remote sensing, vol 61 n° 2 (November 2006)
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Titre : Multiple support vector machines for land cover change detection: an application for mapping urban extensions Type de document : Article/Communication Auteurs : H. Nemmour, Auteur ; Y. Chibani, Auteur Année de publication : 2006 Article en page(s) : pp 125 - 133 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Alger
[Termes IGN] analyse comparative
[Termes IGN] classification par réseau neuronal
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] détection de changement
[Termes IGN] occupation du sol
[Termes IGN] précision géométrique (imagerie)
[Termes IGN] urbanisationRésumé : (Auteur) The reliability of support vector machines for classifying hyperspectral images of remote sensing has been proven in various studies. In this paper, we investigate their applicability for land cover change detection. First, SVM-based change detection is presented and performed for mapping urban growth in the Algerian capital. Different performance indicators, as well as a comparison with artificial neural networks, are used to support our experimental analysis. In a second step, a combination framework is proposed to improve change detection accuracy. Two combination rules, namely, Fuzzy Integral and Attractor Dynamics, are implemented and evaluated with respect to individual SVMs. Recognition rates achieved by individual SVMs, compared to neural networks, confirm their efficiency for land cover change detection. Furthermore, the relevance of SVM combination is highlighted. Copyright ISPRS Numéro de notice : A2006-531 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2006.09.004 En ligne : https://doi.org/10.1016/j.isprsjprs.2006.09.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28254
in ISPRS Journal of photogrammetry and remote sensing > vol 61 n° 2 (November 2006) . - pp 125 - 133[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-06081 SL Revue Centre de documentation Revues en salle Disponible Urban surface biophysical descriptors and land surface temperature variations / D. Weng in Photogrammetric Engineering & Remote Sensing, PERS, vol 72 n° 11 (November 2006)
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Titre : Urban surface biophysical descriptors and land surface temperature variations Type de document : Article/Communication Auteurs : D. Weng, Auteur ; Dong Lu, Auteur ; B. Liang, Auteur Année de publication : 2006 Article en page(s) : pp 1275 - 1286 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] albedo
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] émission thermique
[Termes IGN] flore locale
[Termes IGN] image Landsat-ETM+
[Termes IGN] Indianapolis
[Termes IGN] milieu urbain
[Termes IGN] morphologie urbaine
[Termes IGN] occupation du sol
[Termes IGN] surface imperméable
[Termes IGN] température de surface
[Termes IGN] variable biophysique (végétation)
[Termes IGN] zone urbaineRésumé : (Auteur) In remote sensing studies of land surface temperatures (LST), thematic land-use and land-cover (LULC) data are frequently employed for simple correlation analyses between LULC types and their thermal signatures. Development of quantitative surface descriptors could improve our capabilities for modeling urban thermal landscapes and advance urban climate research. This study developed an analytical procedure based upon a spectral unmixing model for characterizing and quantifying the urban landscape in Indianapolis, Indiana. A Landsat Enhanced Thematic Mapper Plus image of the study area, acquired on 22 June 2002, was spectrally unmixed into four fraction endmembers, namely, green vegetation, soil, high and low albedo. Impervious surface was then computed from the high and low albedo images. A hybrid classification procedure was developed to classify the fraction images into seven land-use and land-cover classes. Next, pixel-based LST measurements were related to urban surface biophysical descriptors derived from spectral mixture analysis (SMA). Correlation analyses were conducted to investigate land-cover based relationships between LST and impervious surface and green vegetation fractions for an analysis of the causes of LST variations. Results indicate that fraction images derived from SMA were effective for quantifying the urban morphology and for providing reliable measurements of biophysical variables such as vegetation abundance, soil, and impervious surface. An examination of LST variations within census block groups and their relationships with the compositions of LULC types, biophysical descriptors, and other relevant spatial data shows that LST possessed a weaker relation with the LULC compositions than with other variables (including urban biophysical descriptors, remote sensing biophysical variables, GIS-based impervious surface variables, and population density). Further research should be directed to refine spectral mixture modeling. The use of multi-temporal remote sensing data for urban time-space modeling and comparison of urban morphology in different geographical settings are also feasible. Copyright ASPRS Numéro de notice : A2006-493 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.72.11.1275 En ligne : https://doi.org/10.14358/PERS.72.11.1275 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28217
in Photogrammetric Engineering & Remote Sensing, PERS > vol 72 n° 11 (November 2006) . - pp 1275 - 1286[article]Improved estimation of aerosol optical depth from MODIS imagery over land surfaces / B. Zhong in Remote sensing of environment, vol 104 n° 4 (30/10/2006)
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Titre : Improved estimation of aerosol optical depth from MODIS imagery over land surfaces Type de document : Article/Communication Auteurs : B. Zhong, Auteur ; Shunlin Liang, Auteur ; H. Fang, Auteur Année de publication : 2006 Article en page(s) : pp 416 - 425 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] aérosol
[Termes IGN] changement climatique
[Termes IGN] épaisseur optique
[Termes IGN] image Terra-MODIS
[Termes IGN] luminance lumineuse
[Termes IGN] occupation du sol
[Termes IGN] végétationRésumé : (Auteur) Estimation of aerosol loadings is of great importance to the studies on global climate changes. The current Moderate-Resolution Imaging Spectroradiometer (MODIS) aerosol estimation algorithm over land is based on the “dark-object” approach, which works only over densely vegetated (“dark”) surfaces. In this study, we develop a new aerosol estimation algorithm that uses the temporal signatures from a sequence of MODIS imagery over land surfaces, particularly “bright” surfaces. The estimated aerosol optical depth is validated by Aerosol Robotic Network (AERONET) measurements. Case studies indicate that this algorithm can retrieve aerosol optical depths reasonably well from the winter MODIS imagery at seven sites: four sites in the greater Washington, DC area, USA; Beijing City, China; Banizoumbou, Niger, Africa; and Bratts Lake, Canada. The MODIS aerosol estimation algorithm over land (MOD04), however, does not perform well over these non-vegetated surfaces. This new algorithm has the potential to be used for other satellite images that have similar temporal resolutions. Copyright Elsevier Numéro de notice : A2006-494 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2006.05.016 En ligne : https://doi.org/10.1016/j.rse.2006.05.016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28218
in Remote sensing of environment > vol 104 n° 4 (30/10/2006) . - pp 416 - 425[article]Developing land use/land cover parameterization for climate-land modelling in East Africa / Nathan Torbick in International Journal of Remote Sensing IJRS, vol 27 n°18 - 19 - 20 (October 2006)
PermalinkSpatially explicit experiments for the exploration of land-use decision-making dynamics / Tom P. Evans in International journal of geographical information science IJGIS, vol 20 n° 9 (october 2006)
PermalinkComparative analysis of urban reflectance and surface temperature / C. Small in Remote sensing of environment, vol 104 n° 2 (30 September 2006)
PermalinkRemote sensing image-based analysis of the relationship between urban heat island and land use/cover changes / X.L. Chen in Remote sensing of environment, vol 104 n° 2 (30 September 2006)
PermalinkCoastal geomorphological and land-use and land-cover study of Sagar island, Bay of Bengal (India) using remotely sensed data / K.S. Jayappa in International Journal of Remote Sensing IJRS, vol 27 n° 17 (September 2006)
PermalinkMapping services in the European soil portal / P. Panagos in GEO: Geoconnexion international, vol 5 n° 8 (september 2006)
PermalinkComparison of computational intelligence based classification techniques for remotely sensed optical image classification / D. Stathakis in IEEE Transactions on geoscience and remote sensing, vol 44 n° 8 (August 2006)
PermalinkError assessment in two lidar-derived TIN datasets / M.H. Peng in Photogrammetric Engineering & Remote Sensing, PERS, vol 72 n° 8 (August 2006)
PermalinkLand-cover mapping in the Brazilian amazon using SPOT-4 Vegetation data and machine learning classification methods / João M.B. Carreiras in Photogrammetric Engineering & Remote Sensing, PERS, vol 72 n° 8 (August 2006)
PermalinkQuantifying spatial heterogeneity at the landscape scale using variogram models / S. Garrigues in Remote sensing of environment, vol 103 n° 1 (15 July 2006)
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