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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]Synthesizing urban remote sensing through application, scale, data and case studies / E.A. Wentz in Geocarto international, vol 27 n° 5 (August 2012)
[article]
Titre : Synthesizing urban remote sensing through application, scale, data and case studies Type de document : Article/Communication Auteurs : E.A. Wentz, Auteur ; D.A. Quattrochi, Auteur ; M. Netzband, Auteur ; S.W. Myint, Auteur Année de publication : 2012 Article en page(s) : pp 425 - 442 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] Atlanta (Géorgie)
[Termes IGN] chaleur
[Termes IGN] classification barycentrique
[Termes IGN] classification ISODATA
[Termes IGN] image Landsat-MSS
[Termes IGN] image Landsat-TM
[Termes IGN] image Quickbird
[Termes IGN] image Terra-ASTER
[Termes IGN] milieu urbain
[Termes IGN] Phoenix
[Termes IGN] villeRésumé : (Auteur) This article describes the outcomes of an international workshop on urban remote sensing. The workshop synthesized the needs of remote sensing scientists to better monitor and analyse urban physical and social dynamics. The workshop was held with urban land use forecasting workshop in April 2011 in Arizona. The four major themes of the jointly held workshops were application, data, scale and case studies. Application refers to how data are used to address urban problems. Data refers to the sources and types of raw data available. Scale is the ever-present concern over data reduction and resolution. Case studies examine a single urban area, typically based on one or two primary themes. One outcome was to integrate multiple case studies to form an urban typology. To respond to this need, this article integrates two case studies on the urban heat island in Atlanta, GA and Phoenix, AZ based on the four themes. Numéro de notice : A2012-372 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2012.687400 Date de publication en ligne : 24/05/2012 En ligne : https://doi.org/10.1080/10106049.2012.687400 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31818
in Geocarto international > vol 27 n° 5 (August 2012) . - pp 425 - 442[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2012051 RAB Revue Centre de documentation En réserve L003 Disponible Temporal mixture analysis for estimating impervious surface area from multi-temporal MODIS NDVI data in Japan / F. Yang in ISPRS Journal of photogrammetry and remote sensing, vol 72 (August 2012)
[article]
Titre : Temporal mixture analysis for estimating impervious surface area from multi-temporal MODIS NDVI data in Japan Type de document : Article/Communication Auteurs : F. Yang, Auteur ; B. Matsushita, Auteur ; T. Fukushima, Auteur ; W. Yang, Auteur Année de publication : 2012 Article en page(s) : pp 90 - 98 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse des mélanges temporels
[Termes IGN] image Aqua-MODIS
[Termes IGN] image Landsat-TM
[Termes IGN] image optique
[Termes IGN] Japon
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] série temporelle
[Termes IGN] surface imperméableRésumé : (Auteur) As a proxy measure of the human ecological footprint, impervious surface area (ISA) has recently become a key concept in the field of urban remote sensing, with a focus on estimation of the ISA at a city-scale by using Landsat-style satellite images. However, ISA estimation is also in demand in disciplines such as the environmental assessment and policy making at a national scale. This paper proposes a new method for estimating the ISA fraction in Japan based on a temporal mixture analysis (TMA) technique. The required inputs for the proposed method are rearranged MODIS NDVI time-series datasets at the temporal stable zone (i.e., the first to the sixth largest NDVI values in a year). Three ISA distribution maps obtained from Landsat-5 TM data were used as reference maps to evaluate the performance of the proposed method. The results showed that the proposed TMA-based method achieved a large reduction in the effects of endmember variability compared with the previous methods (e.g., SMA and NSMA), and thus the new method has promising accuracy for estimating ISA in Japan. The overall root mean square error (RMSE) of the proposed method was 8.7%, with a coefficient of determination of 0.86, and there was no obvious underestimation or overestimation for the whole ISA range. Numéro de notice : A2012-495 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2012.05.016 En ligne : https://doi.org/10.1016/j.isprsjprs.2012.05.016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31941
in ISPRS Journal of photogrammetry and remote sensing > vol 72 (August 2012) . - pp 90 - 98[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2012061 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
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Code-barres Cote Support Localisation Section Disponibilité 081-2012051 SL Revue Centre de documentation Revues en salle Disponible Estimating tropical forest biomass with a combination of SAR image texture and Landsat TM data: An assessment of predictions between regions / M. Cutler in ISPRS Journal of photogrammetry and remote sensing, vol 70 (June 2012)
[article]
Titre : Estimating tropical forest biomass with a combination of SAR image texture and Landsat TM data: An assessment of predictions between regions Type de document : Article/Communication Auteurs : M. Cutler, Auteur ; D. Boyd, Auteur ; Giles M. Foody, Auteur ; A. Vetrivel, Auteur Année de publication : 2012 Article en page(s) : pp 66 - 77 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] analyse comparative
[Termes IGN] analyse texturale
[Termes IGN] biomasse
[Termes IGN] biomasse (combustible)
[Termes IGN] Brésil
[Termes IGN] classification par réseau neuronal
[Termes IGN] déboisement
[Termes IGN] forêt tropicale
[Termes IGN] image JERS
[Termes IGN] image Landsat-TM
[Termes IGN] image multibande
[Termes IGN] image radar
[Termes IGN] Malaisie
[Termes IGN] matrice de co-occurrence
[Termes IGN] niveau de gris (image)
[Termes IGN] ondelette
[Termes IGN] texture d'image
[Termes IGN] ThaïlandeRésumé : (Auteur) Quantifying the above ground biomass of tropical forests is critical for understanding the dynamics of carbon fluxes between terrestrial ecosystems and the atmosphere, as well as monitoring ecosystem responses to environmental change. Remote sensing remains an attractive tool for estimating tropical forest biomass but relationships and methods used at one site have not always proved applicable to other locations. This lack of a widely applicable general relationship limits the operational use of remote sensing as a method for biomass estimation, particularly in high biomass ecosystems. Here, multispectral Landsat TM and JERS-1 SAR data were used together to estimate tropical forest biomass at three separate geographical locations: Brazil, Malaysia and Thailand. Texture measures were derived from the JERS-1 SAR data using both wavelet analysis and Grey Level Co-occurrence Matrix methods, and coupled with multispectral data to provide inputs to artificial neural networks that were trained under four different training scenarios and validated using biomass measured from 144 field plots. When trained and tested with data collected from the same location, the addition of SAR texture to multispectral data showed strong correlations with above ground biomass (r = 0.79, 0.79 and 0.84 for Thailand, Malaysia and Brazil respectively). Also, when networks were trained and tested with data from all three sites, the strength of correlation (r = 0.55) was stronger than previously reported results from the same sites that used multispectral data only. Uncertainty in estimating AGB from different allometric equations was also tested but found to have little effect on the strength of the relationships observed. The results suggest that the inclusion of SAR texture with multispectral data can go someway towards providing relationships that are transferable across time and space, but that further work is required if satellite remote sensing is to provide robust and reliable methodologies for initiatives such as Reducing Emissions from Deforestation and Degradation (REDD+). Numéro de notice : A2012-289 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2012.03.011 En ligne : https://doi.org/10.1016/j.isprsjprs.2012.03.011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31735
in ISPRS Journal of photogrammetry and remote sensing > vol 70 (June 2012) . - pp 66 - 77[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2012041 SL Revue Centre de documentation Revues en salle Disponible Estimating forest attribute parameters for small areas using nearest neighbors techniques / Ronald E. McRoberts in Forest ecology and management, vol 272 (mai 2012)PermalinkA 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)PermalinkAn edge-oriented approach to thematic map error assessment / S. Sweeney in Geocarto international, vol 27 n° 1 (February 2012)PermalinkPermalinkJoint processing of Landsat and ALOS-PALSAR data for forest mapping and monitoring / E. Lehmann in IEEE Transactions on geoscience and remote sensing, vol 50 n° 1 (January 2012)PermalinkDevelopment of a modified neural network-based land cover classification system using automated data selector and multiresolution remotely sensed data / S. Khorram in Geocarto international, vol 26 n° 6 (October 2011)PermalinkImage fusion by spatially adaptive filtering using downscaling cokriging / E. Pardo-Iguzquiza in ISPRS Journal of photogrammetry and remote sensing, vol 66 n° 3 (May - June 2011)PermalinkElectromagnetic land surface classification through integration of optical and radar remote sensing data / J. Baek in IEEE Transactions on geoscience and remote sensing, vol 49 n° 4 (April 2011)PermalinkApproches par télédétection et cartographie des espaces sahéliens mauritaniens / A. Cotonnec in Le monde des cartes, n° 207 (mars 2011)PermalinkLand 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)Permalink