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GSICS inter-calibration of infrared channels of geostationary imagers using Metop-IASI / Tim J. Hewison in IEEE Transactions on geoscience and remote sensing, vol 51 n° 3 Tome 1 (March 2013)
[article]
Titre : GSICS inter-calibration of infrared channels of geostationary imagers using Metop-IASI Type de document : Article/Communication Auteurs : Tim J. Hewison, Auteur ; Xiangqian Wu, Auteur ; Fangfang Yu, Auteur ; et al., Auteur Année de publication : 2013 Article en page(s) : pp 1160 - 1170 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] erreur systématique
[Termes IGN] étalonnage relatif
[Termes IGN] image Feng-Yun
[Termes IGN] image GOES
[Termes IGN] image hyperspectrale
[Termes IGN] image Météosat
[Termes IGN] image MetOp-IASI
[Termes IGN] image thermique
[Termes IGN] rayonnement infrarouge thermique
[Termes IGN] régression linéaireRésumé : (Auteur) The first products of the Global Space-based Inter-Calibration System (GSICS) include bias monitoring and calibration corrections for the thermal infrared (IR) channels of current meteorological sensors on geostationary satellites. These use the hyperspectral Infrared Atmospheric Sounding Interferometer (IASI) on the low Earth orbit (LEO) Metop satellite as a common cross-calibration reference. This paper describes the algorithm, which uses a weighted linear regression, to compare collocated radiances observed from each pair of geostationary-LEO instruments. The regression coefficients define the GSICS Correction, and their uncertainties provide quality indicators, ensuring traceability to the selected community reference, IASI. Examples are given for the Meteosat, GOES, MTSAT, Fengyun-2, and COMS imagers. Some channels of these instruments show biases that vary with time due to variations in the thermal environment, stray light, and optical contamination. These results demonstrate how inter-calibration can be a powerful tool to monitor and correct biases, and help diagnose their root causes. Numéro de notice : A2013-123 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2238544 En ligne : https://doi.org/10.1109/TGRS.2013.2238544 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32261
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 3 Tome 1 (March 2013) . - pp 1160 - 1170[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2013031A RAB Revue Centre de documentation En réserve L003 Disponible Airborne GNSS-R wind retrievals using delay–Doppler maps / N. Rodriguez-Alvarez in IEEE Transactions on geoscience and remote sensing, vol 51 n° 1 Tome 2 (January 2013)
[article]
Titre : Airborne GNSS-R wind retrievals using delay–Doppler maps Type de document : Article/Communication Auteurs : N. Rodriguez-Alvarez, Auteur ; Dennis M. Akos, Auteur ; V. Zavorotny, Auteur ; et al., Auteur Année de publication : 2013 Article en page(s) : pp 626 - 641 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale
[Termes IGN] bande L
[Termes IGN] effet Doppler
[Termes IGN] réflectométrie par GNSS
[Termes IGN] régression linéaire
[Termes IGN] vent
[Termes IGN] vitesseRésumé : (Auteur) Global navigation satellite system (GNSS) reflectometry has emerged recently as a promising remote sensing tool to retrieve various geophysical parameters of the Earth's surface. GNSS-reflected signals, after being received and processed by the airborne or spaceborne receiver, are available as delay correlation waveforms or as delay-Doppler maps (DDMs). In the case of a rough ocean surface, those characteristics can be related to the rms of the L-band limited slopes of the surface waves and, from there, to the surface wind speed. The raw GNSS-reflected signal can be either processed in real time by the receiver or recorded and stored on board and postprocessed in a laboratory. The latter approach leveraging a software receiver allows more flexibility while processing the raw data. This work analyzes DDMs obtained as a result of processing of the data collected by the Global Positioning System (GPS) data logger/software receiver on board the National Oceanic and Atmospheric Administration Gulfstream-IV jet aircraft. Thereafter, the DDMs were used to retrieve surface wind speed employing several different metrics that characterize the DDM extent in the Doppler frequency-delay domain. In contrast to previous works in which winds have been retrieved by fitting the theoretically modeled curves into measured correlation waveforms, here, we do not rely on any model for the determination. Instead, the approach is based on a linear regression between DDM observables and the wind speeds obtained in simultaneous GPS dropsonde measurements. Numéro de notice : A2013-019 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2196437 En ligne : https://doi.org/10.1109/TGRS.2012.2196437 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32157
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 1 Tome 2 (January 2013) . - pp 626 - 641[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2013011B RAB Revue Centre de documentation En réserve L003 Disponible The spatial prediction of tree species diversity in savanna woodlands of Southern Africa / G. Mutowo in Geocarto international, vol 27 n° 8 (December 2012)
[article]
Titre : The spatial prediction of tree species diversity in savanna woodlands of Southern Africa Type de document : Article/Communication Auteurs : G. Mutowo, Auteur ; Amon Murwira, Auteur Année de publication : 2012 Article en page(s) : pp 627 - 645 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] arbre (flore)
[Termes IGN] biodiversité
[Termes IGN] image Ikonos
[Termes IGN] image Terra-ASTER
[Termes IGN] indice de végétation
[Termes IGN] prédiction
[Termes IGN] radiance
[Termes IGN] rayonnement proche infrarouge
[Termes IGN] régression linéaire
[Termes IGN] savane
[Termes IGN] ZimbabweRésumé : (Auteur) In this study, we tested the utility of remotely sensed data in predicting tree species diversity in savanna woodlands. Specifically, we developed linear regression functions based on a combination of the coefficient of variation of near infrared (NIR) radiance and the soil-adjusted vegetation index (SAVI), both derived from advanced space-borne thermal emission and reflection radiometer satellite imagery. Using the regression functions in a Geographic Information System (GIS), we predicted the spatial variations in tree species diversity. Our results showed that tree species diversity can be predicted using a combination of the coefficient of variation of NIR radiance and SAVI. We conclude that remotely sensed data can be used to spatially predict tree species diversity in savanna woodlands. Numéro de notice : A2012-550 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2012.662530 Date de publication en ligne : 29/02/2012 En ligne : https://doi.org/10.1080/10106049.2012.662530 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31996
in Geocarto international > vol 27 n° 8 (December 2012) . - pp 627 - 645[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2012081 RAB Revue Centre de documentation En réserve L003 Disponible A complete processing chain for shadow detection and reconstruction in VHR images / L. Lorenzi in IEEE Transactions on geoscience and remote sensing, vol 50 n° 9 (October 2012)
[article]
Titre : A complete processing chain for shadow detection and reconstruction in VHR images Type de document : Article/Communication Auteurs : L. Lorenzi, Auteur ; F. Melgani, Auteur ; Grégoire Mercier, Auteur Année de publication : 2012 Article en page(s) : pp 3440 - 3452 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] détection d'ombre
[Termes IGN] image à très haute résolution
[Termes IGN] interpolation linéaire
[Termes IGN] reconstruction d'image
[Termes IGN] régression linéaireRésumé : (Auteur) The presence of shadows in very high resolution (VHR) images can represent a serious obstacle for their full exploitation. This paper proposes to face this problem as a whole through the proposal of a complete processing chain, which relies on various advanced image processing and pattern recognition tools. The first key point of the chain is that shadow areas are not only detected but also classified to allow their customized compensation. The detection and classification tasks are implemented by means of the state-of-the-art support vector machine approach. A quality check mechanism is integrated in order to reduce subsequent misreconstruction problems. The reconstruction is based on a linear regression method to compensate shadow regions by adjusting the intensities of the shaded pixels according to the statistical characteristics of the corresponding nonshadow regions. Moreover, borders are explicitly handled by making use of adaptive morphological filters and linear interpolation for the prevention of possible border artifacts in the reconstructed image. Experimental results obtained on three VHR images representing different shadow conditions are reported, discussed, and compared with two other reconstruction techniques. Numéro de notice : A2012-450 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2183876 Date de publication en ligne : 05/03/2012 En ligne : https://doi.org/10.1109/TGRS.2012.2183876 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31896
in IEEE Transactions on geoscience and remote sensing > vol 50 n° 9 (October 2012) . - pp 3440 - 3452[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2012091 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Integration of remote sensing and GIS for evaluating soil erosion risk in northwestern Zhejiang, China / Jianqin Huang in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 9 (September 2012)
[article]
Titre : Integration of remote sensing and GIS for evaluating soil erosion risk in northwestern Zhejiang, China Type de document : Article/Communication Auteurs : Jianqin Huang, Auteur ; Dong Lu, Auteur ; Jin Li, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 935 - 946 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] carte pédologique
[Termes IGN] Chine
[Termes IGN] écosystème forestier
[Termes IGN] érosion
[Termes IGN] estimation statistique
[Termes IGN] forêt tropicale
[Termes IGN] gradient de pente
[Termes IGN] image Landsat-TM
[Termes IGN] modèle numérique de surface
[Termes IGN] modèle RUSLE
[Termes IGN] régression multiple
[Termes IGN] risque naturel
[Termes IGN] système d'information géographiqueRésumé : (Auteur) Estimation of soil loss using the Revised Universal Soil Loss Equation (rusle) has long been an active research topic, but its application in a large area is a challenge due to data availability and quality. In this study, the RUSLE model was used to evaluate soil erosion risk based on soil samples, a soil type map, digital elevation model (dem) data, and Landsat Thematic Mapper (tm) images. Multiple regression analysis was used to identify major factors influencing soil erosion risks. A regression model based on DEM-derived slope gradient and TM-derived fractional soil and vegetation images was developed to map soil erosion risk distribution in a forest ecosystem in Zhejiang, China. The developed method has the potential to quickly examine spatial distri-bution of soil erosion risks. This study provides a new insight for evaluating soil erosion risks in forest ecosystems with the integration of remote sensing and GIS. Numéro de notice : A2012-441 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE/IMAGERIE Nature : Article DOI : 10.14358/PERS.78.9.935 En ligne : https://doi.org/10.14358/PERS.78.9.935 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31887
in Photogrammetric Engineering & Remote Sensing, PERS > vol 78 n° 9 (September 2012) . - pp 935 - 946[article]3-D mapping of a multi-layered Mediterranean forest using ALS data / António Ferraz in Remote sensing of environment, vol 121 (June 2012)PermalinkDoes natural regeneration determine the limit of European beech distribution under climatic stress? / Daniel E. Silva in Forest ecology and management, vol 266 (15 February 2012)PermalinkCarbon Stock of European Beech Forest : A Case at M. Pizzalto, Italy / Aida Taghavi Bayat in APCBEE Procedia, vol 1 (2-20)PermalinkComparing small-footprint lidar and forest inventory data for single strata biomass estimation : A case study over a multi-layered mediterranean forest / António Ferraz (2012)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)PermalinkMining boundary effects in areally referenced spatial data using the Bayesian information criterion / Sudipto Banerjee in Geoinformatica, vol 15 n° 3 (July 2011)PermalinkDonnées géographiques / Pierre Dumolard (2011)PermalinkLocal entropy map : a nonparametric approach to detecting spatially varying multivariate relationships / D. Guo in International journal of geographical information science IJGIS, vol 24 n° 9 (september 2010)PermalinkSpatial autoregressive model for population estimation at the census block level using lidar-derived building volume information / F. Qiu in Cartography and Geographic Information Science, vol 37 n° 3 (July 2010)PermalinkEstimating crown base height for Scots pine by means of the 3D geometry of airborne laser scanning data / Jari Vauhkonen in International Journal of Remote Sensing IJRS, vol 31 n° 5 (March 2010)Permalink