Descripteur
Documents disponibles dans cette catégorie (1547)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
Land covers change detection at coarse spatial scales based on iterative estimation and previous state information / Sylvie Le Hégarat-Mascle in Remote sensing of environment, vol 95 n° 4 (30/04/2005)
[article]
Titre : Land covers change detection at coarse spatial scales based on iterative estimation and previous state information Type de document : Article/Communication Auteurs : Sylvie Le Hégarat-Mascle, Auteur ; Catherine Ottle, Auteur ; Christiane Guérin, Auteur Année de publication : 2005 Article en page(s) : pp 464 - 479 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse diachronique
[Termes IGN] bassin hydrographique
[Termes IGN] chaîne de Markov
[Termes IGN] détection de changement
[Termes IGN] estimation statistique
[Termes IGN] image à basse résolution
[Termes IGN] image NOAA-AVHRR
[Termes IGN] image SPOT-Végétation
[Termes IGN] itération
[Termes IGN] occupation du sol
[Termes IGN] pixel
[Termes IGN] Saône (rivière)
[Termes IGN] sylvicultureRésumé : (Auteur) This study focuses on the use of coarse spatial resolution (CR, pixel size about 1kM2) remote sensing data for land cover change detection and qualification. Assuming the linear mixing model for CR pixels, the problem is that both the multitemporal class feature and the pixel composition in terms of classes are unknown. The proposed algorithm is then based on the iterative alternate estimation of each unknown variable. At each iteration, the class features are estimated, thanks to the knowledge of the composition of so pixels, and then the pixel composition is re-estimated knowing the class features. The subset of known composition pixels is the sub of pixels where no change has occurred, i.e. the previous land cover map is still valid. It is derived automatically by removing at each iteration the pixels where the new composition estimation disagrees with the former one. Finally, for the final estimation of the pixel composition, a Markovian chain model is used to guide the solution, i.e. the previous land cover map is used as a 'reminder' 'memory' term. This approach has been first validated using simulated data with different spatial resolution ratios. Then, the detection of forest change with SPOT-VGT-S 10 has been considered as an actual application case. Finally, the method has been applied to change detection on the Val de Saône watershed between the 1980s and 2000. The results obtained from three coarse resolution series, NOAA/AVHRR, SPOT/VGT-S 10 and SPOT/VGT-P, have been compared. Numéro de notice : A2005-187 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2005.01.011 En ligne : https://doi.org/10.1016/j.rse.2005.01.011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27324
in Remote sensing of environment > vol 95 n° 4 (30/04/2005) . - pp 464 - 479[article]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)
[article]
Titre : A method for detecting large-scale forest covers change using coarse spatial resolution imagery Type de document : Article/Communication Auteurs : R.H. Fraser, Auteur ; A. Abuelgasim, Auteur ; R. Latifovic, Auteur Année de publication : 2005 Article en page(s) : pp 414 - 427 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] Canada
[Termes IGN] classificateur paramétrique
[Termes IGN] classification par arbre de décision
[Termes IGN] couvert forestier
[Termes IGN] détection de changement
[Termes IGN] données auxiliaires
[Termes IGN] grande échelle
[Termes IGN] image à basse résolution
[Termes IGN] image à moyenne résolution
[Termes IGN] image NOAA-AVHRR
[Termes IGN] image SPOT-Végétation
[Termes IGN] modèle de régression
[Termes IGN] régression
[Termes IGN] surveillance forestièreRésumé : (Auteur) Many large countries, including Canada, rely on earth observation as a practical and cost-effective means of monitoring their vast inland ecosystems. A potentially efficient approach is one that detects vegetation changes over a hierarchy of spatial scales ranging from coarse to fine. This paper presents a Change Screening Analysis Technique (Change-SAT) designed as a coarse filter to identify the location and timing of large (>5-1 0 kM2) forest cover changes caused by anthropogenic and natural disturbances at an annual, continental scale. The method uses change metrics derived from 1-km multi-temporal SPOT VEGETATION and NOAA AVHRR imagery (reflectance, temperature, and texture information) and ancillary spatial variables (proximity to active fires, roads, and forest tenures) in combination with logistic regression and decision tree classifiers. Major forest changes of interest include wildfires, insect defoliation, forest harvesting and flooding. Change-SAT was tested for 1998-2000 using an independent sample of change and no-change sites over Canada. Overall accuracy was 94% and commission error, especially critical for large-area change applications, was less than 1%. Regions identified as having major or widespread changes could be targeted for more detailed investigation and mapping using field visits, aerial survey or fine resolution EO methods, such as those being applied under Canadian monitoring programs. This multi-resolution approach could be used as pan of a forest monitoring system to report on carbon stocks and forest stewardship. Numéro de notice : A2005-186 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2004.12.014 En ligne : https://doi.org/10.1016/j.rse.2004.12.014 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27323
in Remote sensing of environment > vol 95 n° 4 (30/04/2005) . - pp 414 - 427[article]A comparison of local variance, fractal dimension, and Moran's index as aids to multispectral image classification / C.W. Emerson in International Journal of Remote Sensing IJRS, vol 26 n° 8 (April 2005)
[article]
Titre : A comparison of local variance, fractal dimension, and Moran's index as aids to multispectral image classification Type de document : Article/Communication Auteurs : C.W. Emerson, Auteur ; N. Siu-Ngan Lam, Auteur ; D.A. Quattrochi, Auteur Année de publication : 2005 Article en page(s) : pp 1575 - 1588 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] Atlanta (Géorgie)
[Termes IGN] autocorrélation spatiale
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] ERDAS Imagine
[Termes IGN] image Landsat-ETM+
[Termes IGN] image multibande
[Termes IGN] milieu urbain
[Termes IGN] occupation du sol
[Termes IGN] précision de la classification
[Termes IGN] segmentation d'image
[Termes IGN] texture d'imageRésumé : (Auteur) The accuracy of traditional multispectral maximum-likelihood image classification is limited by the multi-modal statistical distributions of digital numbers from the complex, heterogenous mixture of land cover types in urban areas. This work examines the utility of local variance, fractal dimension and Moran's I index of spatial autocorrelation in segmenting multispectral satellite imagery with the goal of improving urban land cover classification accuracy. Tools available in the ERDAS Imagine™ software package and the Image Characterization and Modeling System (ICAMS) were used to analyse Landsat ETM+ imagery of Atlanta, Georgia. Images were created from the ETM+ panchromatic band using the three texture indices. These texture images were added to the stack of multispectral bands and classified using a supervised, maximum likelihood technique. Although each texture band improved the classification accuracy over a multispectral only effort, the addition of fractal dimension measures is particularly effective at resolving land cover classes within urbanized areas, as compared to per-pixel spectral classification techniques. Numéro de notice : A2005-204 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160512331326765 En ligne : https://doi.org/10.1080/01431160512331326765 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27341
in International Journal of Remote Sensing IJRS > vol 26 n° 8 (April 2005) . - pp 1575 - 1588[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-05081 RAB Revue Centre de documentation En réserve L003 Exclu du prêt A whole image approach using field measurements for transforming EO1 Hyperion hyperspectral data into canopy reflectance spectra / E.W. Ramsey in International Journal of Remote Sensing IJRS, vol 26 n° 8 (April 2005)
[article]
Titre : A whole image approach using field measurements for transforming EO1 Hyperion hyperspectral data into canopy reflectance spectra Type de document : Article/Communication Auteurs : E.W. Ramsey, Auteur ; G. Nelson, Auteur Année de publication : 2005 Article en page(s) : pp 1589 - 1610 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] correction atmosphérique
[Termes IGN] diffusion du rayonnement
[Termes IGN] données de terrain
[Termes IGN] éclairement énergétique
[Termes IGN] image EO1-Hyperion
[Termes IGN] image hyperspectrale
[Termes IGN] réflectance végétale
[Termes IGN] transfert radiatifRésumé : (Auteur) To maximize the spectral distinctiveness (information) of the canopy reflectance, an atmospheric correction strategy was implemented to provide accurate estimates of the intrinsic reflectance from the Earth Observing 1 (EO1) satellite Hyperion sensor signal. In rendering the canopy reflectance, an estimate of optical depth derived from a measurement of downwelling irradiance was used to drive a radiative transfer simulation of atmospheric scattering and attenuation. During the atmospheric model simulation, the input whole-terrain background reflectance estimate was changed to minimize the differences between the model predicted and the observed canopy reflectance spectra at 34 sites. Lacking appropriate spectrally invariant scene targets, inclusion of the field and predicted comparison maximized the model accuracy and, thereby, the detail and precision in the canopy reflectance necessary to detect low percentage occurrences of invasive plants. After accounting for artifacts surrounding prominent absorption features from about 400nm to 1000nm, the atmospheric adjustment strategy correctly explained 99% of the observed canopy reflectance spectra variance. Separately, model simulation explained an average of 88% + 9% of the observed variance in the visible and 98% + 1 % in the near-infrared wavelengths. In the 34 model simulations, maximum différences between the observed and predicted reflectances were typically less than + 1% in the visible ; however, maximum reflectance différences higher than +1.6% ( Numéro de notice : A2005-205 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/0431160512331326729 En ligne : https://doi.org/10.1080/0431160512331326729 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27342
in International Journal of Remote Sensing IJRS > vol 26 n° 8 (April 2005) . - pp 1589 - 1610[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-05081 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Landsat-7 ETM+ radiometric normalization comparison for northern mapping application / I. Olthof in Remote sensing of environment, vol 95 n° 3 (15/04/2005)
[article]
Titre : Landsat-7 ETM+ radiometric normalization comparison for northern mapping application Type de document : Article/Communication Auteurs : I. Olthof, Auteur ; D. Pouliot, Auteur ; R. Fernandes, Auteur ; R. Latifovic, Auteur Année de publication : 2005 Article en page(s) : pp 388 - 398 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] cartographie numérique
[Termes IGN] correction radiométrique
[Termes IGN] image Landsat-ETM+
[Termes IGN] image SPOT-Végétation
[Termes IGN] méthode robuste
[Termes IGN] mosaïque d'images
[Termes IGN] propagation d'erreur
[Termes IGN] régressionRésumé : (Auteur) Relative radiometric normalization has long been performed to generate consistency among individual Landsat scenes for production of composites containing multiple scenes. Normalization methods have relied on matching identical and assumed invariant features in both images of an overlapping pair, or on invariant targets that are not necessarily the same features. Problems with overlap normalization methods include sensitivity to outliers in overlap data caused by atmospheric or land cover change between scenes, which can lead to radiometric error propagation across a mosaic caused by a normalized scene becoming a reference for the subsequent scene entered into the mosaic. Solutions to such problems include interactive outlier removal to generate a normalization function using a 'no change' data set and methods that are robust against outliers to automatically generate normalization functions with minimal user input. This paper compares two normalization methods that use a robust regression technique called Theil-Sen with an established overlap normalization method. The first method uses Theil-Sen regression to generate a normalization function between overlap regions, while the second uses Theil-Sen to normalize to coarse-resolution composite reflectance data from the SPOT VEGETATION (VGT) sensor. The results of the normalizations were evaluated in two ways: (1) using statistics generated between overlap regions; and (2) separately using coarse-resolution data as a reference. Both overlap normalization methods performed almost identically; however, Theil-Sen was faster and easier to implement than its traditional counterpart due to its insensitivity to outliers and capability for full automation. While overlap and coarse-resolution normalizations each outperformed the other when evaluated against its calibration set, error propagation caused by outliers in overlap samples was avoided in the normalization to coarse-resolution imagery. Advantages offered by normalization to coarse-resolution data using robust regression, including full automation, make this method particularly attractive for generation of large area mosaics containing 100 Landsat scenes or more. Numéro de notice : A2005-171 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2004.06.024 En ligne : https://doi.org/10.1016/j.rse.2004.06.024 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27309
in Remote sensing of environment > vol 95 n° 3 (15/04/2005) . - pp 388 - 398[article]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)PermalinkLand 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)PermalinkSPOT-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)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)PermalinkIntegration of spatial and spectral information by means of unsupervised extraction and classification for homogenous objects applied to multispectral and hyperspectral data / L.O. Jimenez in IEEE Transactions on geoscience and remote sensing, vol 43 n° 4 (April 2005)PermalinkUse of the Bradley-Terry model to quantify association in remotely sensed images / Alfred Stein in IEEE Transactions on geoscience and remote sensing, vol 43 n° 4 (April 2005)PermalinkExtension of retrospective datasets using multiple sensors: an approach to radiometric intercalibration of Landsat TM and MSS data / Arno Röder in Remote sensing of environment, vol 95 n° 2 (30/03/2005)PermalinkA land cover distribution composite image from coarse spatial resolution images using an unmixing method / T.M. Uenishi in International Journal of Remote Sensing IJRS, vol 26 n° 5 (March 2005)PermalinkA Bayesian approach to classification of multiresolution remote sensing data / G. Storvik in IEEE Transactions on geoscience and remote sensing, vol 43 n° 3 (March 2005)PermalinkNested hyper-rectangle learning model for remote sensing: land-cover classification / L. Chen in Photogrammetric Engineering & Remote Sensing, PERS, vol 71 n° 3 (March 2005)Permalink