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Monitoring forest conditions in a protected Mediterranean coastal area by the analysis of multiyear NDVI data / F. Maselli in Remote sensing of environment, vol 89 n° 4 (29/02/2004)
[article]
Titre : Monitoring forest conditions in a protected Mediterranean coastal area by the analysis of multiyear NDVI data Type de document : Article/Communication Auteurs : F. Maselli, Auteur Année de publication : 2004 Article en page(s) : pp 423 - 433 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse diachronique
[Termes IGN] forêt
[Termes IGN] image Landsat-TM
[Termes IGN] image NOAA-AVHRR
[Termes IGN] littoral méditerranéen
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] surveillance forestièreRésumé : (Auteur) The operational utilization of remote sensing techniques for monitoring terrestrial ecosystems is often constrained by problems of undersampling in space and time, particularly in heterogeneous and unstable Mediterranean environments. The current work deals with the use of the NOAA-AVHRR and LandsatTM/ETM+ images to produce long-term NDVI data series characterising coniferous and broadleaved forests in a protected coastal area in Tuscany (Central Italy). Two methods to extract NDVI values of relatively small vegetated areas from NOAA-AVHRR data were first evaluated by comparison to estimates from higher resolution LandsatTM/ETM+ images. The optimal method was then applied to multitemporal AVHRR data series to derive 10-day NDVI profiles of coniferous and broadleaved forests over a 15-year period (19862000). Trend analyses performed on these data series showed that notable NDVI decreases occurred during the study period, particularly for the coniferous forest in summer and early fall. Further analysis carried out on local meteorological measurements led to identify the likely causes of these negative trends in contemporaneous winter rainfall decreases which were significantly correlated with the found NDVI variations. Numéro de notice : A2004-069 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2003.10.020 En ligne : https://doi.org/10.1016/j.rse.2003.10.020 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26597
in Remote sensing of environment > vol 89 n° 4 (29/02/2004) . - pp 423 - 433[article]Improving tropical forest mapping using multi-date Landsat TM data and pre-classification image smoothing / C. Tottrup in International Journal of Remote Sensing IJRS, vol 25 n° 4 (February 2004)
[article]
Titre : Improving tropical forest mapping using multi-date Landsat TM data and pre-classification image smoothing Type de document : Article/Communication Auteurs : C. Tottrup, Auteur Année de publication : 2004 Article en page(s) : pp 717 - 730 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse diachronique
[Termes IGN] canopée
[Termes IGN] carte de la végétation
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] écosystème
[Termes IGN] forêt tropicale
[Termes IGN] image Landsat-TM
[Termes IGN] image multitemporelle
[Termes IGN] lissage de donnéesRésumé : (Auteur) The present study explores the possibility of using Landsat imagery for mapping tropical forest types with relevance to forest ecosystem services. The central part in the classification process is the use of multi-date image data and pre-classification image smoothing. The study argues that multi-date imagery contains information on phenological and canopy structural properties and shows how the use of multi-date imagery has a significant impact on classification accuracy. Furthermore, the study shows the value of applying small kernel smoothing filters to reduce in-class spectral variability and enhance between-class spectral separability. Making use of these approaches and a maximum likehood algorithm, six tropical forest types were classified with an overall accuracy of 90.94%, and with individual forest classes mapped with accuracies above 75.19% (user's accuracy) and above 74.17% (producer accuracy). Numéro de notice : A2004-074 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160310001598926 En ligne : https://doi.org/10.1080/01431160310001598926 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26602
in International Journal of Remote Sensing IJRS > vol 25 n° 4 (February 2004) . - pp 717 - 730[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-04041 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Delineation of forest/nonforest land use classes using nearest neighbor methods / R. Haapanen in Remote sensing of environment, vol 89 n° 3 (15/02/2004)
[article]
Titre : Delineation of forest/nonforest land use classes using nearest neighbor methods Type de document : Article/Communication Auteurs : R. Haapanen, Auteur ; A.R. Ek, Auteur ; Andrew O. Finley, Auteur ; M.E. Bauer, Auteur Année de publication : 2004 Article en page(s) : pp 265 - 271 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification barycentrique
[Termes IGN] délimitation
[Termes IGN] forêt
[Termes IGN] image Landsat-ETM+
[Termes IGN] image Landsat-TM
[Termes IGN] Minnesota (Etats-Unis)
[Termes IGN] occupation du solRésumé : (Auteur) The k-Nearest Neighbor (kNN) method of forest attribute estimation and mapping has become an integral part of national forest inventory methods in Finland in the last decade. This success of kNN method in facilitating multisource inventory has encouraged trials of the method in the Great Lakes Region of the United States. Here we present results from applying the method to Landsat TM and ETM+ data and land cover data collected by the USDA Forest Service's Forest Inventory and Analysis (FIA) program. In 1999, the FIA program in the state of Minnesota moved to a new annual inventory design to reach its targeted full sampling intensity over a 5-year period. This inventory design also utilizes a new 4-subplot cluster plot configuration. Using this new plot design together with 1 year of field plot observations, the kNN classification of forest/nonforest/water achieved overall accuracies ranging from 87% to 91%. Our analysis revealed several important behavioral features associated with kNN classification using the new FIA sample plot design. Results demonstrate the simplicity and utility of using kNN to produce FIA defined forest/nonforest/water classifications. Numéro de notice : A2004-017 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2003.10.002 En ligne : https://doi.org/10.1016/j.rse.2003.10.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26545
in Remote sensing of environment > vol 89 n° 3 (15/02/2004) . - pp 265 - 271[article]Application of stereoscopic satellite images for studying Quaternary tectonics in arid regions / B. Fu in International Journal of Remote Sensing IJRS, vol 25 n° 3 (February 2004)
[article]
Titre : Application of stereoscopic satellite images for studying Quaternary tectonics in arid regions Type de document : Article/Communication Auteurs : B. Fu, Auteur ; A. Lin, Auteur ; K.I. Kano, Auteur ; et al., Auteur Année de publication : 2004 Article en page(s) : pp 537 - 547 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Chine
[Termes IGN] couple stéréoscopique
[Termes IGN] déformation de la croute terrestre
[Termes IGN] ère quaternaire
[Termes IGN] faille géologique
[Termes IGN] géologie structurale
[Termes IGN] image IRS
[Termes IGN] image Landsat-ETM+
[Termes IGN] image Landsat-TM
[Termes IGN] tectonique
[Termes IGN] zone aride
[Termes IGN] zone semi-arideRésumé : (Auteur) We introduce a flexible method for creating stereoscopic pairs of images from any interesting sub-area of the same scene of Landsat Thematic Mapper (TM) / Enhanced Thematic Mapper (ETM) and Indian Remote Sensing (IRS)-IC Pan remote sensing data by setting the Z scale. As a test of this method, stereoscopic images were used to study Quaternary deformation along the Tian Shan Orogenic Belt, north-west China. The new stereoscopic images can then provide detailed information of Quaternary deformation structures, including spatial distribution and arrangement pattern of fold structures, fault scarps and displacement of alluvial fans, terraces and drainage systems along active faults, in three dimensions. The strike-slip partitioning has been revealed by interpretation of stereoscopic images within Chinese Tian Shan. Structural interpretations derived from stereoscopic analysis were confirmed to a high degree of accuracy during a subsequent field study. The satellite remote sensing stereoscopic technique is an effective method of analysing Quaternary tectonic deformation in remote and to semi-arid regions such as the Tian Shan. Numéro de notice : A2004-062 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/0143116031000150031 En ligne : https://doi.org/10.1080/0143116031000150031 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26590
in International Journal of Remote Sensing IJRS > vol 25 n° 3 (February 2004) . - pp 537 - 547[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-04031 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Approaches to fractional land cover and continuous field mapping: a comparative assessment over the BOREAS [BOReal Ecosystem Atmosphere Study] study region / R. Fernandes in Remote sensing of environment, vol 89 n° 2 (30/01/2004)
[article]
Titre : Approaches to fractional land cover and continuous field mapping: a comparative assessment over the BOREAS [BOReal Ecosystem Atmosphere Study] study region Type de document : Article/Communication Auteurs : R. Fernandes, Auteur ; R. Fraser, Auteur ; et al., Auteur Année de publication : 2004 Article en page(s) : pp 234 - 251 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse comparative
[Termes IGN] analyse de groupement
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification par réseau neuronal
[Termes IGN] image Landsat-TM
[Termes IGN] image SPOT-Végétation
[Termes IGN] inversion
[Termes IGN] méthode des moindres carrés
[Termes IGN] précision infrapixellaire
[Termes IGN] régression multiple
[Termes IGN] tâche image d'un point
[Termes IGN] zone boréaleRésumé : (Auteur) Subpixel land cover mapping involves the estimation of surface properties using sensors whose spatial sampling is coarse enough to produce mixtures of the properties within each pixel. This study evaluates five algorithms for mapping subpixel land cover fractions and continuous fields of vegetation properties within the BOREAS study area. The algorithms include a conventional "hard", perpixel classifier, a neural network, a clustering/look-up-table approach, multivariate regression, and linear least squares inversion. A land cover map prepared using a Landsat TM mosaic was adopted as the source of fine scale calibration and validation data. Coarse scale mixtures of five basic land cover classes and continuous vegetation fields, both corresponding to the field of view of SPOT-VEGETATION imagery (1.15-km pixel size), were synthesised from the TM mosaic using a modelled point spread function. Two measures of land cover distribution were used. fractions of fine scale land cover categories and continuous fields of vegetation structural characteristics. The subpixel algorithms were applied using both proximate ( 400 km) separation between training and validation regions. "Hard" classification performed poorly in estimating proportions or continuous fields. The neural network, look-up-table and multivariate regression algorithms produced good matches of spatial patterns and regional land cover composition for the proximate treatment. However, all three methods exhibited substantial biases with the distant treatment due to the characteristics of the training data. Linear least squares inversion offers a relatively unbiased but less precise alternative for subpixel proportion and fraction mapping as it avoids calibration to the a priori distribution of land cover in the training data. In general, a combination of multivariate regression for proximate training data and linear least squares inversion for distant training data resulted in woody fraction estimates within 20% of the Landsat TM classification-based estimates. Numéro de notice : A2004-026 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2002.06.006 En ligne : https://doi.org/10.1016/j.rse.2002.06.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26554
in Remote sensing of environment > vol 89 n° 2 (30/01/2004) . - pp 234 - 251[article]Systematic corrections of AVHRR image composites for temporal studies / J. Cihlar in Remote sensing of environment, vol 89 n° 2 (30/01/2004)PermalinkNarrowband-to-broadband albedo conversion for glacier ice and snow: equations based on modeling and ranges of validity of the equations / W. Greuell in Remote sensing of environment, vol 89 n° 1 (15/01/2004)PermalinkQuantitative remote sensing of land surfaces / Shunlin Liang (2004)PermalinkSpatial resolution improvement of remote sensing images by fusion of subpixel-shifted multi-observation images / Y. Lu in International Journal of Remote Sensing IJRS, vol 24 n° 23 (December 2003)PermalinkExiste-t-il une "mémoire" de l'espace en Roumanie post-communiste ? / Simona Niculescu in Revue internationale de géomatique, vol 13 n° 4 (décembre 2003 – février 2004)PermalinkSpectral enhancement of selected pixels in Thematic Mapper images of the Guanajuato district (Mexico) to identify hydrothermally altered rocks / M.A. Torres-Verra in International Journal of Remote Sensing IJRS, vol 24 n° 22 (November 2003)PermalinkA Markov random field approach to spatio-temporal contextual image classification / F. Melgani in IEEE Transactions on geoscience and remote sensing, vol 41 n° 11 (November 2003)PermalinkA new maximum-likelihood joint segmentation technique for multitemporal SAR and multiband optical images / P. Lombardo in IEEE Transactions on geoscience and remote sensing, vol 41 n° 11 (November 2003)PermalinkContribution de la télédétection dans l'étude de la fracturation du horst de Ghar Rouban (l'Oranie-Algérie) / M. Tabeliouna in Bulletin des sciences géographiques, n° 12 (octobre 2003)PermalinkIncreasing the spatial resolution of agricultural land cover maps using a Hopfield neural network / A.J. Tatem in International journal of geographical information science IJGIS, vol 17 n° 7 (october 2003)Permalink