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Mapping regional land cover with MODIS data for biological conservation: examples from the greater Yellowstone ecosystem, USA and PARA state, Brazil / K.J. Wessels in Remote sensing of environment, vol 92 n° 1 (15 July 2004)
[article]
Titre : Mapping regional land cover with MODIS data for biological conservation: examples from the greater Yellowstone ecosystem, USA and PARA state, Brazil Type de document : Article/Communication Auteurs : K.J. Wessels, Auteur ; R.S. de Fries, Auteur ; et al., Auteur Année de publication : 2004 Article en page(s) : pp 67 - 83 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] biodiversité
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification dirigée
[Termes IGN] classification par arbre de décision
[Termes IGN] déboisement
[Termes IGN] fractionnement
[Termes IGN] habitat animal
[Termes IGN] image Landsat-TM
[Termes IGN] image Terra-MODIS
[Termes IGN] limite de résolution géométrique
[Termes IGN] occupation du sol
[Termes IGN] Para (Brésil)
[Termes IGN] parc naturel nationalRésumé : (Auteur) The paper investigated the application of MODIS data for mapping regional land cover at moderate resolutions (250 and 500 m), for regional conservation purposes. Land cover maps were generated for two major conservation areas (Greater Yellowstone Ecosystem-GYE, USA and the Pard State, Brazil) using MODIS data and decision tree classifications. The MODIS land cover products were evaluated using existing Landsat TM land cover maps as reference data. The Landsat TM land cover maps were processed to their fractional composition at the MODIS resolution (250 and 500 m). In GYE, the MODIS land cover was very successful at mapping extensive cover types (e.g. coniferous forest and grasslands) and far less successful at mapping smaller habitats (e.g. wetlands, deciduous tree cover) that typically occur in patches that are smaller than the MODIS pixels, but are reported to be very important to biodiversity conservation. The MODIS classification for Pard State was successful at producing a regional forest/non-forest product which is useful for monitoring the extreme human impacts such as deforestation. The ability of MODIS data to map secondary forest remains to be tested, since regrowth typically harbors reduced levels of biodiversity. The two case studies showed the value of using multi-date 250 m data with only two spectral bands, as well as single day 500 m data with seven spectral bands, thus illustrating the versatile use of MODIS data in two contrasting environments. MODIS data provide new options for regional land cover mapping that are less labor-intensive than Landsat and have higher resolution than previous 1km AVHRR or the current 1 km global land cover product. The usefulness of the MODIS data in addressing biodiversity conservation questions will ultimately depend upon the patch sizes of important habitats and the land cover transformations that threaten them. Numéro de notice : A2004-299 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2004.05.002 En ligne : https://doi.org/10.1016/j.rse.2004.05.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26826
in Remote sensing of environment > vol 92 n° 1 (15 July 2004) . - pp 67 - 83[article]Mapping vegetation in a heterogeneous mountain rangeland using Landsat data: an alternative method to define and classify land-cover units / A.M. Cingolani in Remote sensing of environment, vol 92 n° 1 (15 July 2004)
[article]
Titre : Mapping vegetation in a heterogeneous mountain rangeland using Landsat data: an alternative method to define and classify land-cover units Type de document : Article/Communication Auteurs : A.M. Cingolani, Auteur ; D. Renison, Auteur ; et al., Auteur Année de publication : 2004 Article en page(s) : pp 84 - 97 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] analyse discriminante
[Termes IGN] Argentine
[Termes IGN] bande spectrale
[Termes IGN] carte de la végétation
[Termes IGN] classification dirigée
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] données de terrain
[Termes IGN] état de conservation
[Termes IGN] flore locale
[Termes IGN] image Landsat
[Termes IGN] limite de résolution géométrique
[Termes IGN] montagne
[Termes IGN] occupation du sol
[Termes IGN] photo-interprétation assistée par ordinateurRésumé : (Auteur) Three major problems are faced when mapping natural vegetation with mid-resolution satellite images using conventional supervised classification techniques: defining the adequate hierarchical level for mapping; defining discrete land cover units discernible by the satellite; and selecting representative training sites. In order to solve these problems, we developed an approach based on the: (1) definition of ecologically meaningful units as mosaics or repetitive combinations of structural types, (2) utilization of spectral information (indirectly) to define the units, (3) exploration of two alternative methods to classify the units once they are defined: the traditional, Maximum Likelihood method, which was enhanced by analyzing objective ways of selecting the best training sites, and an alternative method using Discriminant Functions directly obtained from the statistical analysis of signatures. The study was carried out in a heterogeneous mountain rangeland in central Argentina using Landsat data and 251 field sampling sites. On the basis of our analysis combining terrain information (a matrix of 251 stands X 14 land cover attributes) and satellite data (a matrix of 251 stands x 8 bands), we defined 8 land cover units (mosaics of structural types) for mapping, emphasizing the structural types which had stronger effects on reflectance. The comparison through field validation of both methods for mapping units showed that classification based on Discriminant Functions produced better results than the traditional Maximum Likelihood method (accuracy of 86% vs. 78%). Numéro de notice : A2004-300 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2004.05.008 En ligne : https://doi.org/10.1016/j.rse.2004.05.008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26827
in Remote sensing of environment > vol 92 n° 1 (15 July 2004) . - pp 84 - 97[article]Using Thematic Mapper data for change detection and sustainable use of cultivated land: a case study in the Yellow River delta, China / G.X. Zhao in International Journal of Remote Sensing IJRS, vol 25 n° 13 (July 2004)
[article]
Titre : Using Thematic Mapper data for change detection and sustainable use of cultivated land: a case study in the Yellow River delta, China Type de document : Article/Communication Auteurs : G.X. Zhao, Auteur ; G. Lin, Auteur Année de publication : 2004 Article en page(s) : pp 2509 - 2522 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] agriculture
[Termes IGN] analyse diachronique
[Termes IGN] Chine
[Termes IGN] classification à base de connaissances
[Termes IGN] classification dirigée
[Termes IGN] classification non dirigée
[Termes IGN] delta
[Termes IGN] détection de changement
[Termes IGN] développement durable
[Termes IGN] Fleuve jaune (Chine)
[Termes IGN] image Landsat-TM
[Termes IGN] surface cultivée
[Termes IGN] utilisation du solRésumé : (Auteur) Preservation of cultivated land is one of China's four basic strategic policies. Timely land use monitoring is a prerequisite of cultivated land management and sustainable utilization. Using digital satellite remote sensing techniques, the intention is to develop a workable procedure for cultivated land change detection in the Yellow River delta region. Four detection methods were assessed. The assessment, in general, suggests that it is difficult to find a single efficient method for cultivated land change detection in the study area, where spectral confusion is widespread due to soil salinization and juxtaposed land use patterns. The knowledge-based visual change detection and classification-result overlay methods are more appropriate than the multi-temporal composite and classification, and image ratioing. The latter two methods are useful and efficient when remote sensing data acquired in the suitable season are available, and distinct spectral characteristics of different land use types exist. The results show that the area of cultivated land in this region decreased by 5321.8 ha over the period 1987 to 1998, i.e. 483.8ha every year, mainly concentrated in the central paddy field region and northeast dry land region. Numéro de notice : A2004-258 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160310001619571 En ligne : https://doi.org/10.1080/01431160310001619571 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26785
in International Journal of Remote Sensing IJRS > vol 25 n° 13 (July 2004) . - pp 2509 - 2522[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-04111 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Wavelet for urban spatial feature discrimination: comparisons with fractal, spatial autocorrelation, and spatial co-occurrence approaches / Nina S.N. Lam in Photogrammetric Engineering & Remote Sensing, PERS, vol 70 n° 7 (July 2004)
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Titre : Wavelet for urban spatial feature discrimination: comparisons with fractal, spatial autocorrelation, and spatial co-occurrence approaches Type de document : Article/Communication Auteurs : Nina S.N. Lam, Auteur ; S.W. Myint, Auteur ; J.M. Tyler, Auteur Année de publication : 2004 Article en page(s) : pp 803 - 812 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse fractale
[Termes IGN] autocorrélation spatiale
[Termes IGN] classification dirigée
[Termes IGN] image multibande
[Termes IGN] matrice
[Termes IGN] milieu urbain
[Termes IGN] précision de la classification
[Termes IGN] transformation en ondelettesRésumé : (Auteur) Traditional image processing techniques have proven inadequate for urban mapping using high spatial resolution remote-sensing images. This study examined and evaluated wavelet transforms for urban texture analysis and image classification using high spatial resolution ATLAS imagery. For the purpose of comparison and to evaluate the effectiveness of the wavelet approaches, two different fractal approaches (isarithm and triangular prism), spatial autocorrelation (Moran's I and Geary's C), and spatial co-occurrence matrix of the selected urban classes were examined using 65 X 65, 33 X 33, and 17 X 17 samples with a pixel size of 2.5 m. Results from this study suggest that a multi-band and multi-level wavelet approach can be used to drastically increase the classification accuracy. The fractal techniques did not provide satisfactory classification accuracy. Spatial autocorrelation and spatial co-occurrence techniques were found to be relatively effective when compared to the fractal approaches. It can be concluded that the wavelet transform approach is the most accurate of all four approaches. Numéro de notice : A2004-273 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.70.7.803 En ligne : https://doi.org/10.14358/PERS.70.7.803 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26800
in Photogrammetric Engineering & Remote Sensing, PERS > vol 70 n° 7 (July 2004) . - pp 803 - 812[article]Change detection techniques / Dong Lu in International Journal of Remote Sensing IJRS, vol 25 n° 12 (June 2004)
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Titre : Change detection techniques Type de document : Article/Communication Auteurs : Dong Lu, Auteur ; P. Mausel, Auteur ; et al., Auteur Année de publication : 2004 Article en page(s) : pp 2365 - 2407 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse comparative
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] analyse en composantes principales
[Termes IGN] capteur (télédétection)
[Termes IGN] classification dirigée
[Termes IGN] classification par réseau neuronal
[Termes IGN] détection de changement
[Termes IGN] limite de résolution géométrique
[Termes IGN] seuillage d'image
[Termes IGN] système d'information géographique
[Termes IGN] traitement d'imageRésumé : (Auteur) Timely and accurate change detection of Earth's surface features is extremely important for understanding relationships and interactions between human and natural phenomena in order to promote better decision making. Remote sensing data are primary sources extensively used for change detection in recent decades. Many change detection techniques have been developed. This paper summarizes and reviews these techniques. Previous literature has shown that image differencing, principal component analysis and post-classification comparison are the most common methods used for change detection. In recent years, spectral mixture analysis, artificial neural networks and integration of geographical information system and remote sensing data have become important techniques for change detection applications. Different change detection algorithms have their own merits and no single approach is optimal and applicable to all cases. In practice, different algorithms are often compared to find the best change detection results for a specific application. Research of change detection techniques is still an active topic and new techniques are needed to effectively use the increasingly diverse and complex remotely sensed data available or projected to be soon available from satellite and airborne sensors. This paper is a comprehensive exploration of all the major change detection approaches implemented as found in the literature. Numéro de notice : A2004-223 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/0143116031000139863 En ligne : https://doi.org/10.1080/0143116031000139863 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26750
in International Journal of Remote Sensing IJRS > vol 25 n° 12 (June 2004) . - pp 2365 - 2407[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 080-04101 RAB Revue Centre de documentation En réserve L003 Disponible Probabilistic landslide hazard mapping using GIS and remote sensing data at Boun, Korea / S. Lee in International Journal of Remote Sensing IJRS, vol 25 n° 11 (June 2004)PermalinkTélédétection et géo-archéologie : Comparaison des potentialités naturelles d'accueil des gebels Siman et Zawiye, vis-à-vis des sites antiques romano-byzantins de Syrie du nord / M. Abdulkarim in Photo interprétation, vol 40 n° 2 - 3 (Juin 2004)PermalinkLand cover characterization of temperate east Asia using multi-temporal vegetation sensor data / S.H. Boles in Remote sensing of environment, vol 90 n° 4 (30/04/2004)PermalinkTree model based eco-climatic vegetation classification and fuzzy mapping in diverse tropical deciduous ecosystems using multi-season NDVI / J. Krishnaswamy in International Journal of Remote Sensing IJRS, vol 25 n° 6 (March 2004)PermalinkCartographie des rizières d'une zone des hautes terres centrales de Madagascar pour la détermination des zones à risque du paludisme / F. Thomas (2004)PermalinkTraitement des données de télédétection / Michel-Claude Girard (2004)PermalinkA cognitive pyramid for contextual classification of remote sensing images / E. Binaghi in IEEE Transactions on geoscience and remote sensing, vol 41 n° 12 (December 2003)PermalinkMapping urban areas by fusing multiple sources of coarse resolution remotely sensed data / A.M. Schneider in Photogrammetric Engineering & Remote Sensing, PERS, vol 69 n° 12 (December 2003)PermalinkStudy of urban spatial patterns from SPOT panchromatic imagery using textural analysis / Qian Zhang in International Journal of Remote Sensing IJRS, vol 24 n° 21 (November 2003)PermalinkA neural adaptive model for feature extraction and recognition in high resolution remote sensing imagery / E. Binaghi in International Journal of Remote Sensing IJRS, vol 24 n° 20 (October 2003)PermalinkA Markov random field-based approach to decision-level fusion for remote sensing image classification / Ryuei Nishii in IEEE Transactions on geoscience and remote sensing, vol 41 n° 10 (October 2003)PermalinkMultitemporal/multiband SAR classification of urban areas using spatial analysis: statistical versus neural kernel-based approach / T. Macri Pellizzei in IEEE Transactions on geoscience and remote sensing, vol 41 n° 10 (October 2003)PermalinkA comparison of urban mapping methods using high-resolution digital imagery / N. Thomas in Photogrammetric Engineering & Remote Sensing, PERS, vol 69 n° 9 (September 2003)PermalinkImpact of topographic normalization on land-cover classification accuracy / S.R. Hale in Photogrammetric Engineering & Remote Sensing, PERS, vol 69 n° 7 (July 2003)PermalinkEstimating local variations in land use statistics / A. Geddes in International journal of geographical information science IJGIS, vol 17 n° 4 (june 2003)PermalinkEvaluation of airborne video data for land-cover classification accuracy assessment / I.T. Grierson in Geocarto international, vol 18 n° 2 (June - August 2003)PermalinkProcessing Hyperion and ALI for forest classification / D.G. Goodenough in IEEE Transactions on geoscience and remote sensing, vol 41 n° 6 (June 2003)PermalinkSatellite multi-sensor data analysis of urban surface temperatures and Landcover / B. Dousset in ISPRS Journal of photogrammetry and remote sensing, vol 58 n° 1-2 (June - December 2003)PermalinkImage calibration to like-values in mapping shallow water quality from multitemporal data / M.A.. Islam in Photogrammetric Engineering & Remote Sensing, PERS, vol 69 n° 5 (May 2003)PermalinkAn algorithm for mapping burnt areas in Australia using SPOT-Vegetation data / D. Stroppiana in IEEE Transactions on geoscience and remote sensing, vol 41 n° 4 (April 2003)Permalink