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Extraction des zones cohérentes par l’analyse spatio-temporelle d’images de télédétection / Thomas Guyet in Revue internationale de géomatique, vol 25 n° 4 (octobre - décembre 2015)
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Titre : Extraction des zones cohérentes par l’analyse spatio-temporelle d’images de télédétection Type de document : Article/Communication Auteurs : Thomas Guyet, Auteur ; Simon Malinowski, Auteur ; Mohand Cherif Benyounès, Auteur Année de publication : 2015 Article en page(s) : pp 473 - 494 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse spatio-temporelle
[Termes IGN] caractérisation
[Termes IGN] cohérence des données
[Termes IGN] écologie
[Termes IGN] extraction de données
[Termes IGN] fusion de données
[Termes IGN] image Aqua-MODIS
[Termes IGN] image Terra-MODIS
[Termes IGN] partition d'image
[Termes IGN] Sénégal
[Termes IGN] série temporelle
[Termes IGN] surface cultivéeRésumé : (auteur) Cet article présente une méthode de segmentation de séries temporelles d’images satellite (SITS) en zones cohérentes, c’est-à-dire en des régions géographiques ayant des comportements temporels homogènes. L’objectif de cette méthode est, d’une part, d’extraire des caractéristiques spatio-temporelles d’une région observée et, d’autre part, d’obtenir cette caractérisation de manière efficace en temps de calcul pour traiter de grandes masses de données. Cette méthode est appliquée à la caractérisation des régions agro-écologiques du Sénégal par l’analyse des images MODIS sur un an (23 dates). Numéro de notice : A2015-923 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3166/RIG.25.473-494 Date de publication en ligne : 24/02/2016 En ligne : https://doi.org/10.3166/RIG.25.473-494 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79725
in Revue internationale de géomatique > vol 25 n° 4 (octobre - décembre 2015) . - pp 473 - 494[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 047-2015041 RAB Revue Centre de documentation En réserve L003 Disponible Investigating the robustness of the new Landsat-8 Operational Land Imager derived texture metrics in estimating plantation forest aboveground biomass in resource constrained areas / Timothy Dube in ISPRS Journal of photogrammetry and remote sensing, vol 108 (October 2015)
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Titre : Investigating the robustness of the new Landsat-8 Operational Land Imager derived texture metrics in estimating plantation forest aboveground biomass in resource constrained areas Type de document : Article/Communication Auteurs : Timothy Dube, Auteur ; Onisimo Mutanga, Auteur Année de publication : 2015 Article en page(s) : pp 12 – 32 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] Afrique du sud (état)
[Termes IGN] biodiversité
[Termes IGN] biomasse aérienne
[Termes IGN] biomasse forestière
[Termes IGN] classification
[Termes IGN] classification dirigée
[Termes IGN] espèce végétale
[Termes IGN] Eucalyptus dunii
[Termes IGN] Eucalyptus grandis
[Termes IGN] image Landsat-8
[Termes IGN] image Landsat-OLI
[Termes IGN] Pinus taeda
[Termes IGN] régression
[Termes IGN] sous-étage
[Termes IGN] sylviculture
[Termes IGN] texture d'imageRésumé : (auteur) The successful launch of the 30-m Landsat-8 Operational Land Imager (OLI) pushbroom sensor offers a new primary data source necessary for aboveground biomass (AGB) estimation, especially in resource-limited environments. In this work, the strength and performance of Landsat-8 OLI image derived texture metrics (i.e. texture measures and texture ratios) in estimating plantation forest species AGB was investigated. It was hypothesized that the sensor’s pushbroom design, coupled with the presence of refined spectral properties, enhanced radiometric resolution (i.e. from 8 bits to 12 bits) and improved signal-to-noise ratio have the potential to provide detailed spectral information necessary for significantly strengthening AGB estimation in medium-density forest canopies. The relationship between image texture metrics and measurements of forest attributes can be used to help characterize complex forests, and enhance fine vegetation biophysical properties, a difficult challenge when using spectral vegetation indices especially in closed canopies. This study examines the prospects of using Landsat-8 OLI sensor derived texture metrics for estimating AGB for three medium-density plantation forest species in KwaZulu Natal, South Africa. In order to achieve this objective, three unique data pre-processing techniques were tested (analysis I: Landsat-8 OLI raw spectral-bands vs. raw texture bands; analysis II: Landsat-8 OLI raw spectral-band ratios vs. texture band ratios and analysis III: Landsat-8 OLI derived vegetation indices vs. texture band ratios). The landsat-8 OLI derived texture parameters were examined for robustness in estimating AGB using linear regression, stepwise-multiple linear regression and stochastic gradient boosting regression models. The results of this study demonstrated that all texture parameters particularly band texture ratios calculated using a 3 × 3 window size, could enhance AGB estimation when compared to simple spectral reflectance, simple band ratios and the most popular spectral vegetation indices. For instance, the use of combined texture ratios yielded the highest R2 values of 0.76 (RMSE = 9.55 t ha−1 (18.07%) and CV-RMSE of 0.18); 0.74 (RMSE = 12.81 t ha−1 (17.72%) and CV-RMSE of 0.08); 0.74 (RMSE = 12.67 t ha−1 (06.15%) and CV-RMSE of 0.06) and 0.53 (RMSE = 20.15 t ha−1 (14.40%) and CV-RMSE of 0.15) overall for Eucalyptus dunii, Eucalyptus grandis, Pinus taeda individually and all species, respectively. Overall, the findings of this study provide the necessary insight and motivation to the remote sensing community, particularly in resource constrained regions, to shift towards embracing various texture metrics obtained from the readily-available and cheap multispectral Landsat-8 OLI sensor. Numéro de notice : A2015-849 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.06.002 Date de publication en ligne : 25/06/2015 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2015.06.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79219
in ISPRS Journal of photogrammetry and remote sensing > vol 108 (October 2015) . - pp 12 – 32[article]Land cover changes assessment using object-based image analysis in the Binah River watershed (Togo and Benin) / Hèou Maléki Badjana in Earth and space science, vol 2 n° 10 (October 2015)
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Titre : Land cover changes assessment using object-based image analysis in the Binah River watershed (Togo and Benin) Type de document : Article/Communication Auteurs : Hèou Maléki Badjana, Auteur ; Jörg Helmschrot, Auteur ; Peter Selsam, Auteur ; Kperkouma Wala, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 403 - 416 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse d'image orientée objet
[Termes IGN] analyse diachronique
[Termes IGN] bassin hydrographique
[Termes IGN] Bénin
[Termes IGN] changement d'occupation du sol
[Termes IGN] déboisement
[Termes IGN] détection de changement
[Termes IGN] image Landsat-MSS
[Termes IGN] image Landsat-OLI
[Termes IGN] image Landsat-TM
[Termes IGN] occupation du sol
[Termes IGN] savane
[Termes IGN] TogoRésumé : (auteur) In this study, land cover changes between 1972 and 2013 were investigated in the Binah River watershed (North of Togo and Benin) using remote sensing and geographic information system technologies. Multitemporal satellite images—Landsat MSS (1972), TM (1987), and OLI-TIRS (2013)—were processed using object-based image analysis and post–classification comparison methods including landscape metrics and changes trajectories analysis. Land cover maps referring to five main land cover classes, namely, agricultural land, forest land, savannah, settlements, and water bodies, were produced for each acquisition date. The overall accuracies were 76.64% (1972), 83.52% (1987), and 88.84% (2013) with respective Kappa statistics of 0.69, 0.78, and 0.86. The assessment of the spatiotemporal pattern of land cover changes indicates that savannah, the main vegetation type, has undergone the most dominant change, decreasing from 67% of the basin area in 1972 to 56% in 1987 and 33% in 2013. At the same time, agricultural land has significantly increased from 15% in 1972 to 24% in 1987 and 43% in 2013, while some proportions of agricultural land were converted to savannah relating to fallow agriculture. In total, more than 55% of the landscape experienced changes between 1972 and 2013. These changes are primarily due to human activities and population growth. In addition, agricultural activities significantly contributed to the increase in the number of patches, degree of division, and splitting index of forest and savannah vegetations and the decrease in their effective mesh sizes. These results indicate further fragmentation of forest and savannah vegetations between 1972 and 2013. Further research is needed to quantitatively evaluate the influences of individual factors of human activities and to separate these from the impacts of climate change-driven disturbances. Numéro de notice : A2015--042 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : doi.org/10.1002/2014EA000083 En ligne : http://dx.doi.org/10.1002/2014EA000083 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81804
in Earth and space science > vol 2 n° 10 (October 2015) . - pp 403 - 416[article]Stochastic geometrical model and Monte Carlo optimization methods for building reconstruction from InSAR data / Yue Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 108 (October 2015)
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Titre : Stochastic geometrical model and Monte Carlo optimization methods for building reconstruction from InSAR data Type de document : Article/Communication Auteurs : Yue Zhang, Auteur ; Xuan Sun, Auteur ; Antje Thiele, Auteur ; Stefan Hinz, Auteur Année de publication : 2015 Article en page(s) : pp 49 – 61 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] image radar moirée
[Termes IGN] image TanDEM-X
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] méthode de Monte-Carlo
[Termes IGN] modèle stochastique
[Termes IGN] optimisation (mathématiques)
[Termes IGN] reconstruction 3D du bâtiRésumé : (auteur) Synthetic aperture radar (SAR) systems, such as TanDEM-X, TerraSAR-X and Cosmo-SkyMed, acquire imagery with high spatial resolution (HR), making it possible to observe objects in urban areas with high detail. In this paper, we propose a new top-down framework for three-dimensional (3D) building reconstruction from HR interferometric SAR (InSAR) data. Unlike most methods proposed before, we adopt a generative model and utilize the reconstruction process by maximizing a posteriori estimation (MAP) through Monte Carlo methods. The reason for this strategy refers to the fact that the noisiness of SAR images calls for a thorough prior model to better cope with the inherent amplitude and phase fluctuations.
In the reconstruction process, according to the radar configuration and the building geometry, a 3D building hypothesis is mapped to the SAR image plane and decomposed to feature regions such as layover, corner line, and shadow. Then, the statistical properties of intensity, interferometric phase and coherence of each region are explored respectively, and are included as region terms. Roofs are not directly considered as they are mixed with wall into layover area in most cases. When estimating the similarity between the building hypothesis and the real data, the prior, the region term, together with the edge term related to the contours of layover and corner line, are taken into consideration. In the optimization step, in order to achieve convergent reconstruction outputs and get rid of local extrema, special transition kernels are designed. The proposed framework is evaluated on the TanDEM-X dataset and performs well for buildings reconstruction.Numéro de notice : A2015-851 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.06.004 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2015.06.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79221
in ISPRS Journal of photogrammetry and remote sensing > vol 108 (October 2015) . - pp 49 – 61[article]Tropical forest canopy cover estimation using satellite imagery and airborne lidar reference data / Lauri Korhonen in Silva fennica, vol 49 n° 5 ([01/10/2015])
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Titre : Tropical forest canopy cover estimation using satellite imagery and airborne lidar reference data Type de document : Article/Communication Auteurs : Lauri Korhonen, Auteur ; Daniela Ali-Sisto, Auteur ; Timo Tokola, Auteur Année de publication : 2015 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] canopée
[Termes IGN] couvert forestier
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt tropicale
[Termes IGN] image ALOS-AVNIR2
[Termes IGN] image optique
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] Laos
[Termes IGN] placette d'échantillonnage
[Termes IGN] régression logistique
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) The fusion of optical satellite imagery, strips of lidar data and field plots is a promising approach for the inventory of tropical forests. Airborne lidars also enable an accurate direct estimation of the forest canopy cover (CC), and thus a sample of lidar strips can be used as reference data for creating CC maps which are based on satellite images. In this study, our objective was to validate CC maps obtained from an ALOS AVNIR-2 satellite image wall-to-wall, against a lidar-based CC map of a tropical forest area located in Laos. The reference CC values which were needed for model training were obtained from a sample of four lidar strips. Zero-and-one inflated beta regression (ZOINBR) models were applied to link the spectral vegetation indices derived from the ALOS image with the lidar-based CC estimates. In addition, we compared ZOINBR and logistic regression models in the forest area estimation by using >20% CC as a forest definition. Using a total of 409 217 30 × 30 m population units as validation, our model showed a strong correlation between lidar-based CC and spectral satellite features (root mean square error = 12.8%, R2 = 0.82). In the forest area estimation, a direct classification using logistic regression provided better accuracy than the estimation of CC values as an intermediate step (kappa = 0.61 vs. 0.53). It is important to obtain sufficient training data from both ends of the CC range. The forest area estimation should be done before the CC estimation, rather than vice versa. Numéro de notice : A2015-673 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.14214/sf.1405 En ligne : http://www.silvafennica.fi/article/1405 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78293
in Silva fennica > vol 49 n° 5 [01/10/2015][article]Analysis of different methods for 3D reconstruction of natural surfaces from parallel-axes UAV images / Annette Eltner in Photogrammetric record, vol 30 n° 151 (September - November 2015)
PermalinkLe contrôle de la végétation dans les emprises ferroviaires : une approche multi-scalaire / Flavien Viguier in XYZ, n° 144 (septembre - novembre 2015)
PermalinkEstimation of forest biomass from two-level model inversion of single-pass InSAR data / M.J. Soja in IEEE Transactions on geoscience and remote sensing, vol 53 n° 9 (September 2015)
PermalinkImages satellite : de nouveaux capteurs, un accès facilité aux données et des produits innovants / H. Heisig in Géomatique suisse, vol 113 n° 9 (septembre 2015)
PermalinkMeasuring the effectiveness of various features for thematic information extraction from very high resolution remote sensing imagery / X. Chen in IEEE Transactions on geoscience and remote sensing, vol 53 n° 9 (September 2015)
PermalinkMonitoring forest cover loss using multiple data streams, a case study of a tropical dry forest in Bolivia / Loïc Paul Dutrieux in ISPRS Journal of photogrammetry and remote sensing, vol 107 (September 2015)
PermalinkMonitoring of chronological stages of deforestation-afforestation: the case of Southern Chile / Nicolas Maestripieri in Photo interprétation, European journal of applied remote sensing, vol 51 n° 3 (septembre 2015)
PermalinkRemoval of thin clouds using cirrus and QA bands of Landsat-8 / Yang Shen in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 9 (September 2015)
PermalinkA robust fixed rank kriging method for improving the spatial completeness and accuracy of satellite SST products / Yuxin Zhu in IEEE Transactions on geoscience and remote sensing, vol 53 n° 9 (September 2015)
PermalinkTerraSAR-X dual-pol time-series for mapping of wetland vegetation / Julie Betbeder in ISPRS Journal of photogrammetry and remote sensing, vol 107 (September 2015)
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