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Signature extension through space for northern landcover classification: a comparison of radiometric correction methods / I. Olthof in Remote sensing of environment, vol 95 n° 3 (15/04/2005)
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[article]
Titre : Signature extension through space for northern landcover classification: a comparison of radiometric correction methods Type de document : Article/Communication Auteurs : I. Olthof, Auteur ; C. Butson, Auteur ; R. Fraser, Auteur Année de publication : 2005 Article en page(s) : pp 290 - 302 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] agriculture
[Termes IGN] analyse comparative
[Termes IGN] classificateur paramétrique
[Termes IGN] correction radiométrique
[Termes IGN] image Landsat
[Termes IGN] limite de résolution géométrique
[Termes IGN] occupation du sol
[Termes IGN] phénologie
[Termes IGN] prévision
[Termes IGN] signature spectraleRésumé : (Auteur) Northern landcover mapping for climate change and carbon modeling requires greater detail than what is available from coarse resolution data. Mapping landcover with medium resolution data from Landsat presents challenges due to differences in time and space between scene acquisitions required for full coverage. These differences cause landcover signatures to vary due to haze, solar geometry and phenology, among other factors. One way to circumvent this problem is to have an image interpreter classify each scene independently, however, this is not an optimal solution in the north due to a lack of spatially extensive reference data and resources required to label scenes individually. Another possible approach is to stabilize signatures in space and time so that they may be extracted from one scene and extended to others, thereby reducing the amount of reference data and user input required for mapping large areas. A radiometric normalization approach was developed that exploits the high temporal frequency with which coarse resolution data are acquired and the high spatial frequency of medium resolution data. The current paper compares this radiometric correction methodology with an established absolute calibration methodology for signature extension for landcover classification and explores factors that affect extension performance to recommend how and when signature extension can be applied. Overall, the new normalization method produced better extension and classification results than absolute calibration. Results also showed that extension performance was affected more by geographical distance than by differences in anniversary dates between acquisitions for the range of data examined. Geographical distance in the north-south direction leads to poorer extension performance than distance in the cast west direction due in part to differences in vegetation composition assigned the same class label in the latitudinal direction. While extension performance was somewhat variable and in some cases did not produce a best classification result by itself, it provided an initial best guess of landcover that can subsequently be refined by an expert image interpreter. Numéro de notice : A2005-170 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2004.12.015 En ligne : https://doi.org/10.1016/j.rse.2004.12.015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27308
in Remote sensing of environment > vol 95 n° 3 (15/04/2005) . - pp 290 - 302[article]Land covers update by supervised classification of segmented ASTER images / A.R.S. Marcal in International Journal of Remote Sensing IJRS, vol 26 n° 7 (April 2005)
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Titre : Land covers update by supervised classification of segmented ASTER images Type de document : Article/Communication Auteurs : A.R.S. Marcal, Auteur ; J.S. Borges, Auteur ; et al., Auteur Année de publication : 2005 Article en page(s) : pp 1347 - 1362 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse discriminante
[Termes IGN] carte d'occupation du sol
[Termes IGN] classificateur paramétrique
[Termes IGN] classification barycentrique
[Termes IGN] classification dirigée
[Termes IGN] classification floue
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] image multibande
[Termes IGN] image Terra-ASTER
[Termes IGN] mise à jour cartographique
[Termes IGN] Portugal
[Termes IGN] segmentation d'imageRésumé : (Auteur) The revision of the 1995 land cover dataset for the Vale do Sousa region, in the northwest of Portugal, was carried out by supervised classification of a multispectral image from the Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER) sensor. The nine reflective bands of ASTER were used, covering the spectral range from 0.52-2.43 um. The image was initially ortho-rectified and segmented into 51 186 objects, with an average object size of 135 pixels (about 3 ha). A total of 582 of these objects were identified for training nine land cover classes. The image was classified using an algorithm based on a fuzzy classifier, Support Vector Machines (SVM), K Nearest Neighbours (K-NN) and a Logistic Discrimination (LD) classifier. The results from the classification were evaluated using a set of 277 validation sites, independently gathered. The overall accuracy was 44.6%, for the fuzzy classifier. 70.5%, for the SVM, 60.9% for the K-NN and 72.2% for the LD classifier. The difficulty in discriminating between some of the forest land cover classes was examined by separability analysis and unsupervised classification with hierarchical clustering. The forest classes were found to overlap in the multi-spectral space defined by the nine ASTER bands used. Numéro de notice : A2005-179 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160412331291233 En ligne : https://doi.org/10.1080/01431160412331291233 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27316
in International Journal of Remote Sensing IJRS > vol 26 n° 7 (April 2005) . - pp 1347 - 1362[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-05071 RAB Revue Centre de documentation En réserve L003 Exclu du prêt SPOT-4 Vegetation multi-temporal compositing for land cover change studies over tropical regions / João M.B. Carreiras in International Journal of Remote Sensing IJRS, vol 26 n° 7 (April 2005)
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Titre : SPOT-4 Vegetation multi-temporal compositing for land cover change studies over tropical regions Type de document : Article/Communication Auteurs : João M.B. Carreiras, Auteur ; J.M.C. Pereira, Auteur Année de publication : 2005 Article en page(s) : pp 1323 - 1346 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse en composantes principales
[Termes IGN] autocorrélation spatiale
[Termes IGN] cohérence des données
[Termes IGN] détection de changement
[Termes IGN] filtrage du bruit
[Termes IGN] forêt tropicale
[Termes IGN] image multitemporelle
[Termes IGN] image optique
[Termes IGN] image SPOT-Végétation
[Termes IGN] Mato Grosso
[Termes IGN] nébulosité
[Termes IGN] rapport signal sur bruit
[Termes IGN] Soil Adjusted Vegetation Index
[Termes IGN] surveillance agricole
[Termes IGN] utilisation du sol
[Termes IGN] zone intertropicaleRésumé : (Auteur) Multi-temporal compositing of SPOT-4 VEGETATION imagery over tropical regions was tested to produce spatially coherent monthly composite images with reduced cloud contamination, for the year 2000. Monthly composite images generated from daily images (S1 product, 1-km) encompassing different land cover. types of the state of Mato Grosso, Brazil, were evaluated in terms of cloud contamination and spatial consistency. A new multi-temporal compositing algorithm was tested which uses different criteria for vegetated and non-vegetated or sparsely vegetated land cover types. Furthermore, a principal components transformation that rescales the noise in the image-Maximum Noise Fraction (MNF)- was applied to a multi-temporal dataset of monthly composite images and tested as a method of additional signal-to-noise ratio improvement. The back-transformed dataset using the first 12 MNF eigenimages yielded an accurate reconstruction of monthly composite images from the dry season (May to September) and enhanced spatial coherence from wet season images (October to April), as evaluated by the Moran's 1 index of spatial autocorrelation. This approach is useful for land cover- change studies in the tropics, where it is difficult to obtain cloud-free optical remote sensing imagery. In Mato Grosso, wet season composite images are important for monitoring agricultural crop cycles. Numéro de notice : A2005-178 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160512331338005 En ligne : https://doi.org/10.1080/01431160512331338005 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27315
in International Journal of Remote Sensing IJRS > vol 26 n° 7 (April 2005) . - pp 1323 - 1346[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-05071 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Updating land cover classification using a rule-based decision system / Damien Raclot in International Journal of Remote Sensing IJRS, vol 26 n° 7 (April 2005)
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Titre : Updating land cover classification using a rule-based decision system Type de document : Article/Communication Auteurs : Damien Raclot, Auteur ; F. Colin, Auteur ; C. Puech, Auteur Année de publication : 2005 Article en page(s) : pp 1309 - 1321 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] agriculture
[Termes IGN] base de données d'occupation du sol
[Termes IGN] base de règles
[Termes IGN] classification dirigée
[Termes IGN] cultures
[Termes IGN] données auxiliaires
[Termes IGN] Gers (32)
[Termes IGN] image isolée
[Termes IGN] image multibande
[Termes IGN] image SPOT
[Termes IGN] mise à jour
[Termes IGN] occupation du sol
[Termes IGN] parcelle agricole
[Termes IGN] pixel
[Termes IGN] Sousson (rivière)Résumé : (Auteur) This paper proposes a land cover classification methodology in agricultural contexts that provides satisfactory results with a single satellite image per year acquired during the growing period. Our approach incorporates ancillary data such as cropping history (inter-annual crop rotations), context (altitude, soil type) and structure (parcels size and shape) to compensate for the lack of radiometric data resulting from the use of a single image. The originality of the proposed method resides in the three successive steps used: S1: per-pixel classification of a single SPOT XS image with a restricted number of land cover classes (RL) chosen to ensure good accuracy; S2: conversion of RLs into a per-parcel classification system using ancillary parcel boundaries: and S3: parcel allocation using exhaustive land cover classes (EL) and its refinement through the application of decision rules. The method was tested on a 120 km2 area (Sousson river basin, Gers, France) where exhaustive knowledge of land cover for two successive years allowed complete validation of our method. It allocated 87% of the parcels with a 75% accuracy rate according to the exhaustive list (EL). This is a satisfactory result obtained with one SPOT XS image in a small agricultural parcel context. Numéro de notice : A2005-177 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160512331326774 En ligne : https://doi.org/10.1080/01431160512331326774 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27314
in International Journal of Remote Sensing IJRS > vol 26 n° 7 (April 2005) . - pp 1309 - 1321[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-05071 RAB Revue Centre de documentation En réserve L003 Exclu du prêt An unsupervised approach based on the generalized Gaussian model to automatic change detection in multitemporal SAR images / Y. Bazi in IEEE Transactions on geoscience and remote sensing, vol 43 n° 4 (April 2005)
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Titre : An unsupervised approach based on the generalized Gaussian model to automatic change detection in multitemporal SAR images Type de document : Article/Communication Auteurs : Y. Bazi, Auteur ; Lorenzo Bruzzone, Auteur ; F. Melgani, Auteur Année de publication : 2005 Article en page(s) : pp 874 - 887 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] chatoiement
[Termes IGN] détection de changement
[Termes IGN] distribution de Gauss
[Termes IGN] filtrage numérique d'image
[Termes IGN] image ERS-SAR
[Termes IGN] image multitemporelle
[Termes IGN] image radar
[Termes IGN] seuillage d'imageRésumé : (Auteur) In this paper, we present a novel automatic and unsupervised change-detection approach specifically oriented to the analysis of multitemporal single-channel single-polarization synthetic aperture radar (SAR) images. This approach is based on a closed-loop process made up of three main steps: 1) a novel preprocessing based on a controlled adaptive iterative filtering; 2) a comparison between multitemporal images carried out according to a standard log-ratio operator; and 3) a novel approach to the automatic analysis of the log-ratio image for generating the change-detection map. The first step aims at reducing the speckle noise in a controlled way in order to maximize the discrimination capability between changed and unchanged classes. In the second step, the two filtered multitemporal images are compared to generate a log-ratio image that contains explicit information on changed areas. The third step produces the change-detection map according to a thresholding procedure based on a reformulation of the Kittler-Illingworth (KI) threshold selection criterion. In particular, the modified KI criterion is derived under the generalized Gaussian assumption for modeling the distributions of changed and unchanged classes. This parametric model was chosen because it is capable of better fitting the conditional densities of classes in the log-ratio image. In order to control the filtering step and, accordingly, the effects of the filtering process on change-detection accuracy, we propose to identify automatically the optimal number of despeckling filter iterations [Step 1)] by analyzing the behavior of the modified KI criterion. This results in a completely automatic and self-consistent change-detection approach that avoids the use of empirical methods for the selection of the best number of filtering iterations. Experiments carried out on two sets of multitemporal images (characterized by different levels of speckle noise) acquired by the European Remote Sensing 2 satellite SAR sensor confirm the effectiveness of the proposed unsupervised approach, which results in change-detection accuracies very similar to those that can be achieved by a manual supervised thresholding. Numéro de notice : A2005-194 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2004.842441 En ligne : https://doi.org/10.1109/TGRS.2004.842441 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27331
in IEEE Transactions on geoscience and remote sensing > vol 43 n° 4 (April 2005) . - pp 874 - 887[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-05042 RAB Revue Centre de documentation En réserve L003 Disponible Colour-coded pixel-based highly interactive web mapping for georeferenced data exploration / H. Zhao in International journal of geographical information science IJGIS, vol 19 n° 4 (april 2005)
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