Descripteur
Termes IGN > imagerie > image spatiale > image satellite > image Landsat > image Landsat-ETM+
image Landsat-ETM+Voir aussi |
Documents disponibles dans cette catégorie (200)
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
Phenology-based crop classification algorithm and its implications on agricultural water use assessments in California's central valley / L. Zhong in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 8 (August 2012)
[article]
Titre : Phenology-based crop classification algorithm and its implications on agricultural water use assessments in California's central valley Type de document : Article/Communication Auteurs : L. Zhong, Auteur ; P. Gong, Auteur ; Gregory S. Biging, Auteur Année de publication : 2012 Article en page(s) : pp 799 - 813 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Californie (Etats-Unis)
[Termes IGN] carte agricole
[Termes IGN] classification par arbre de décision
[Termes IGN] cultures
[Termes IGN] Enhanced vegetation index
[Termes IGN] évapotranspiration
[Termes IGN] fusion d'images
[Termes IGN] image Landsat-ETM+
[Termes IGN] image Landsat-TM
[Termes IGN] image Terra-MODIS
[Termes IGN] phénologie
[Termes IGN] segmentation d'imageRésumé : (Auteur) The overarching goal of this study was to map specific crop types in the Central Valley, California and estimate the effect of classification uncertainty on the calculation of crop evapotranspiration (ETc). A phenology-based classification (PBC) approach was developed to identify crop types based on phenological and spectral metrics derived from the time series of Landsat TM/ETM_ imagery. Phenological metrics, calculated by fitting asymmetric double sigmoid functions to temporal profiles of enhanced vegetation index (EVI), were capable of separating crop types with distinct crop calendars. An innovative method was used to compute spectral metrics to represent crops' spectral characteristics at certain phenological stages instead of any specific imaging date. Crop mapping using these metrics showed a stable performance without influences of low-quality data and inter-annual differences in imaging dates. The requirement for ground reference data by the PBC approach was low because classification algorithms were mostly built according to the knowledge on crop calendars and agricultural practices. Techniques including image segmentation, data fusion with MODIS imagery, and decision tree were incorporated to make the approach effective and efficient. Though moderate accuracy (~65.0 percent) was achieved, ETc calculated by the Food and Agriculture Organization (FAO) 56 method showed that the estimate of water use was not likely to be significantly affected by the classification error in PBC. All these advantages imply the strength of the PBC approach in the regular crop mapping of the Central Valley. Numéro de notice : A2012-428 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.78.8.799 En ligne : https://doi.org/10.14358/PERS.78.8.799 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31874
in Photogrammetric Engineering & Remote Sensing, PERS > vol 78 n° 8 (August 2012) . - pp 799 - 813[article]An automated approach for updating land cover maps based on integrated change detection and classification methods / X. Chen in ISPRS Journal of photogrammetry and remote sensing, vol 71 (July 2012)
[article]
Titre : An automated approach for updating land cover maps based on integrated change detection and classification methods Type de document : Article/Communication Auteurs : X. Chen, Auteur ; J. Chen, Auteur ; Y. Shi, Auteur ; Yasushi Yamaguchi, Auteur Année de publication : 2012 Article en page(s) : pp 86 - 95 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] carte d'occupation du sol
[Termes IGN] champ aléatoire de Markov
[Termes IGN] Chensi (Chine)
[Termes IGN] détection de changement
[Termes IGN] image Landsat-ETM+
[Termes IGN] mise à jour de base de donnéesRésumé : (Auteur) Updating land cover maps from remotely sensed data in a timely manner is important for many areas of scientific research. Unfortunately, traditional classification procedures are very labor intensive and subjective because of the required human interaction. Based on the strategy of updating land cover data only for the changed area, we proposed an integrated, automated approach to update land cover maps without human interaction. The proposed method consists primarily of the following three parts: a change detection technique, a Markov Random Fields (MRFs) model, and an iterated training sample selecting procedure. In the proposed approach, remotely sensed data acquired in different seasons or from different remote sensors can be used. Meanwhile, the approach is completely unsupervised. Therefore, the methodology has a wide scope of application. A case study of Landsat data was conducted to test the performance of this method. The experimental results show that several sub-modules in this method work effectively and that reasonable classification accuracy can be achieved. Numéro de notice : A2012-350 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2012.05.006 En ligne : https://doi.org/10.1016/j.isprsjprs.2012.05.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31796
in ISPRS Journal of photogrammetry and remote sensing > vol 71 (July 2012) . - pp 86 - 95[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-2012051 SL Revue Centre de documentation Revues en salle Disponible Long term land cover and seagrass mapping using Landsat and object-based image analysis from 1972 to 2010 in the coastal environment of South East Queensland, Australia / M. Lyons in ISPRS Journal of photogrammetry and remote sensing, vol 71 (July 2012)
[article]
Titre : Long term land cover and seagrass mapping using Landsat and object-based image analysis from 1972 to 2010 in the coastal environment of South East Queensland, Australia Type de document : Article/Communication Auteurs : M. Lyons, Auteur ; S. Phinn, Auteur ; C. Roelfsema, Auteur Année de publication : 2012 Article en page(s) : pp 34 - 46 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse diachronique
[Termes IGN] distribution spatiale
[Termes IGN] herbier marin
[Termes IGN] image Landsat-ETM+
[Termes IGN] image Landsat-MSS
[Termes IGN] image Landsat-TM
[Termes IGN] littoral
[Termes IGN] occupation du sol
[Termes IGN] Queensland (Australie)
[Termes IGN] répartition géographique
[Termes IGN] série temporelleRésumé : (Auteur) Long term global archives of high-moderate spatial resolution, multi-spectral satellite imagery are now readily accessible, but are not being fully utilised by management agencies due to the lack of appropriate methods to consistently produce accurate and timely management ready information. This work developed an object-based remote sensing approach to map land cover and seagrass distribution in an Australian coastal environment for a 38 year Landsat image time-series archive (1972–2010). Landsat Multi-Spectral Scanner (MSS), Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM+) imagery were used without in situ field data input (but still using field knowledge) to produce land and seagrass cover maps every year data were available, resulting in over 60 map products over the 38 year archive. Land cover was mapped annually using vegetation, bare ground, urban and agricultural classes. Seagrass distribution was also mapped annually, and in some years monthly, via horizontal projected foliage cover classes, sand and deep water. Land cover products were validated using aerial photography and seagrass maps were validated with field survey data, producing several measures of accuracy. An average overall accuracy of 65% and 80% was reported for seagrass and land cover products respectively, which is consistent with other studies in the area. This study is the first to show moderate spatial resolution, long term annual changes in land cover and seagrass in an Australian environment, created without the use of in situ data; and only one of a few similar studies globally. The land cover products identify several long term trends; such as significant increases in South East Queensland’s urban density and extent, vegetation clearing in rural and rural-residential areas, and inter-annual variation in dry vegetation types in western South East Queensland. The seagrass cover products show that there has been a minimal overall change in seagrass extent, but that seagrass cover level distribution is extremely dynamic; evidenced by large scale migrations of higher seagrass cover levels and several sudden and significant changes in cover level. These mapping products will allow management agencies to build a baseline assessment of their resources, understand past changes and help inform implementation and planning of management policy to address potential future changes. Numéro de notice : A2012-346 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2012.05.002 En ligne : https://doi.org/10.1016/j.isprsjprs.2012.05.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31792
in ISPRS Journal of photogrammetry and remote sensing > vol 71 (July 2012) . - pp 34 - 46[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-2012051 SL Revue Centre de documentation Revues en salle Disponible The potential of spectral mixture analysis to improve the estimation accuracy of tropical forest biomass / T.M. Basuki in Geocarto international, vol 27 n° 4 (July 2012)
[article]
Titre : The potential of spectral mixture analysis to improve the estimation accuracy of tropical forest biomass Type de document : Article/Communication Auteurs : T.M. Basuki, Auteur ; Andrew K. Skidmore, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 329 - 345 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] biomasse
[Termes IGN] estimation statistique
[Termes IGN] forêt tropicale
[Termes IGN] image Landsat-ETM+
[Termes IGN] Indonésie
[Termes IGN] régressionRésumé : (Auteur) A main limitation of pixel-based vegetation indices or reflectance values for estimating above-ground biomass is that they do not consider the mixed spectral components on the earth's surface covered by a pixel. In this research, we decomposed mixed reflectance in each pixel before developing models to achieve higher accuracy in above-ground biomass estimation. Spectral mixture analysis was applied to decompose the mixed spectral components of Landsat-7 ETM+ imagery into fractional images. Afterwards, regression models were developed by integrating training data and fraction images. The results showed that the spectral mixture analysis improved the accuracy of biomass estimation of Dipterocarp forests. When applied to the independent validation data set, the model based on the vegetation fraction reduced 5–16% the root mean square error compared to the models using a single band 4 or 5, multiple bands 4, 5, 7 and all non-thermal bands of Landsat ETM+. Numéro de notice : A2012-334 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2011.634928 Date de publication en ligne : 05/12/2011 En ligne : https://doi.org/10.1080/10106049.2011.634928 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31780
in Geocarto international > vol 27 n° 4 (July 2012) . - pp 329 - 345[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 059-2012041 RAB Revue Centre de documentation En réserve L003 Disponible A method for extracting burned areas from Landsat TM/ETM+ images by soft aggregation of multiple Spectral Indices and a region growing algorithm / D. Stroppiana in ISPRS Journal of photogrammetry and remote sensing, vol 69 (April 2012)
[article]
Titre : A method for extracting burned areas from Landsat TM/ETM+ images by soft aggregation of multiple Spectral Indices and a region growing algorithm Type de document : Article/Communication Auteurs : D. Stroppiana, Auteur ; Gloria Bordogna, Auteur ; P. Carrara, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 88 - 102 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse multicritère
[Termes IGN] cartographie des risques
[Termes IGN] Europe du sud
[Termes IGN] image Landsat-ETM+
[Termes IGN] image Landsat-TM
[Termes IGN] incendie de forêt
[Termes IGN] sous ensemble flou
[Termes IGN] surveillance de la végétationRésumé : (Auteur) Since fire is a major threat to forests and wooded areas in the Mediterranean environment of Southern Europe, systematic regional fire monitoring is a necessity. Satellite data constitute a unique cost-effective source of information on the occurrence of fire events and on the extent of the area burned. Our objective is to develop a (semi-)automated algorithm for mapping burned areas from medium spatial resolution (30 m) satellite data. In this article we present a multi-criteria approach based on Spectral Indices, soft computing techniques and a region growing algorithm; theoretically this approach relies on the convergence of partial evidence of burning provided by the indices. Our proposal features several innovative aspects: it is flexible in adapting to a variable number of indices and to missing data; it exploits positive and negative evidence (bipolar information) and it offers different criteria for aggregating partial evidence in order to derive the layers of candidate seeds and candidate region growing boundaries. The study was conducted on a set of Landsat TM images, acquired for the year 2003 over Southern Europe and pre-processed with the LEDAPS (Landsat Ecosystem Disturbance Adaptive Processing System) processing chain for deriving surface spectral reflectance ?i in the TM bands. The proposed method was applied to show its flexibility and the sensitivity of the accuracy of the resulting burned area maps to different aggregation criteria and thresholds for seed selection. Validation performed over an entire independent Landsat TM image shows the commission and omission errors to be below 21% and 3%, respectively. Numéro de notice : A2012-195 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2012.03.001 En ligne : https://doi.org/10.1016/j.isprsjprs.2012.03.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31642
in ISPRS Journal of photogrammetry and remote sensing > vol 69 (April 2012) . - pp 88 - 102[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-2012031 SL Revue Centre de documentation Revues en salle Disponible PermalinkAn assessment of internal neural network parameters affecting image classification accuracy / L. Zhou in Photogrammetric Engineering & Remote Sensing, PERS, vol 77 n° 12 (December 2011)PermalinkEstimation of forest stand volume, tree density and biodiversity using Landsat ETM + Data, comparison of linear and regression tree analyses / Jahangir Mohammadi in Procedia Environmental Sciences, vol 7 (2011)PermalinkA new pan-sharpening method using multiobjective particle swarm optimization and the shiftable contourlet transform / J. Saeedi in ISPRS Journal of photogrammetry and remote sensing, vol 66 n° 3 (May - June 2011)PermalinkApport de l'image satellitaire à l'analyse de la tectonique active dans les confins d'Aurès-Hodna (Atlas saharien, Algérie) / R. Marmi in Photo interprétation, European journal of applied remote sensing, vol 47 n° 1 (mars 2011)PermalinkApproches par télédétection et cartographie des espaces sahéliens mauritaniens / A. Cotonnec in Le monde des cartes, n° 207 (mars 2011)PermalinkNew data sources for completing national topographic mapping of Northern Canada at 1:50,000 / D. Clavet in Geomatica, vol 65 n° 1 (March 2011)PermalinkPermalinkLand cover classification of cloud-contaminated multitemporal high-resolution images / A. Salberg in IEEE Transactions on geoscience and remote sensing, vol 49 n° 1 Tome 2 (January 2011)PermalinkL'occupation du sol fait ses preuves en région / Françoise de Blomac in SIG la lettre, n° 123 (janvier 2011)Permalink