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Wave period and coastal bathymetry using wave propagation on optical images / Céline Danilo in IEEE Transactions on geoscience and remote sensing, vol 54 n° 11 (November 2016)
[article]
Titre : Wave period and coastal bathymetry using wave propagation on optical images Type de document : Article/Communication Auteurs : Céline Danilo, Auteur ; Farid Melgani, Auteur Année de publication : 2016 Article en page(s) : pp 6307 - 6319 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bathymétrie
[Termes IGN] fréquence
[Termes IGN] Hawaii (Etats-Unis)
[Termes IGN] image Landsat-8
[Termes IGN] image optique
[Termes IGN] lever bathymétrique
[Termes IGN] littoral
[Termes IGN] rayonnement électromagnétique
[Termes IGN] vagueRésumé : (Auteur) We propose a method based on combining wave tracing and linear wave theory for the estimation of wave period and bathymetry in coastal areas from satellite images. The method depends on several parameters for which we provide ranges of variations adapted to the instrument. Experimental results are conducted on several sites located around the Hawaiian island of Oahu, using 13 Landsat-8 images. Results show that wave period estimations are compatible with the wave buoy measurements in all cases. In addition, bathymetry estimation results show a standard deviation of less than 15% of the observed depth out of the surf zone until 20 m for sites with a direct exposure to the swell and with an absence of clouds. The proposed method, which does not rely on ancillary data, represents a promising tool for bathymetry estimation using satellite images in which waves are present. Numéro de notice : A2016-912 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2579266 En ligne : https://doi.org/10.1109/TGRS.2016.2579266 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83134
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 11 (November 2016) . - pp 6307 - 6319[article]Estimating forest species abundance through linear unmixing of CHRIS/PROBA imagery / S. Stagakis in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)
[article]
Titre : Estimating forest species abundance through linear unmixing of CHRIS/PROBA imagery Type de document : Article/Communication Auteurs : S. Stagakis, Auteur ; Theofilos Vanikiotis, Auteur ; Olga Sykioti, Auteur Année de publication : 2016 Article en page(s) : pp 79 - 89 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse des mélanges spectraux
[Termes IGN] carte de la végétation
[Termes IGN] classification bayesienne
[Termes IGN] effet d'ombre
[Termes IGN] espèce végétale
[Termes IGN] Fagus sylvatica
[Termes IGN] Grèce
[Termes IGN] image hyperspectrale
[Termes IGN] image Landsat-8
[Termes IGN] image PROBA-CHRIS
[Termes IGN] orthoimage
[Termes IGN] parc naturel national
[Termes IGN] partition d'image
[Termes IGN] Pinus nigra
[Termes IGN] richesse floristique
[Vedettes matières IGN] Inventaire forestierRésumé : (Auteur) The advancing technology of hyperspectral remote sensing offers the opportunity of accurate land cover characterization of complex natural environments. In this study, a linear spectral unmixing algorithm that incorporates a novel hierarchical Bayesian approach (BI-ICE) was applied on two spatially and temporally adjacent CHRIS/PROBA images over a forest in North Pindos National Park (Epirus, Greece). The scope is to investigate the potential of this algorithm to discriminate two different forest species (i.e. beech – Fagus sylvatica, pine – Pinus nigra) and produce accurate species-specific abundance maps. The unmixing results were evaluated in uniformly distributed plots across the test site using measured fractions of each species derived by very high resolution aerial orthophotos. Landsat-8 images were also used to produce a conventional discrete-type classification map of the test site. This map was used to define the exact borders of the test site and compare the thematic information of the two mapping approaches (discrete vs abundance mapping). The required ground truth information, regarding training and validation of the applied mapping methodologies, was collected during a field campaign across the study site. Abundance estimates reached very good overall accuracy (R2 = 0.98, RMSE = 0.06). The most significant source of error in our results was due to the shadowing effects that were very intense in some areas of the test site due to the low solar elevation during CHRIS acquisitions. It is also demonstrated that the two mapping approaches are in accordance across pure and dense forest areas, but the conventional classification map fails to describe the natural spatial gradients of each species and the actual species mixture across the test site. Overall, the BI-ICE algorithm presented increased potential to unmix challenging objects with high spectral similarity, such as different vegetation species, under real and not optimum acquisition conditions. Its full potential remains to be investigated in further and more complex study sites in view of the upcoming satellite hyperspectral missions. Numéro de notice : A2016-778 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2016.05.013 En ligne : https://doi.org/10.1016/j.isprsjprs.2016.05.013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82473
in ISPRS Journal of photogrammetry and remote sensing > vol 119 (September 2016) . - pp 79 - 89[article]A superresolution land-cover change detection method using remotely sensed images with different spatial resolutions / Xiaodong Li in IEEE Transactions on geoscience and remote sensing, vol 54 n° 7 (July 2016)
[article]
Titre : A superresolution land-cover change detection method using remotely sensed images with different spatial resolutions Type de document : Article/Communication Auteurs : Xiaodong Li, Auteur ; Feng Ling, Auteur ; Giles M. Foody, Auteur ; Yun Du, Auteur Année de publication : 2016 Article en page(s) : pp 3822 - 3841 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] changement d'occupation du sol
[Termes IGN] classification pixellaire
[Termes IGN] détection de changement
[Termes IGN] image à moyenne résolution
[Termes IGN] image à très haute résolution
[Termes IGN] image Landsat-OLI
[Termes IGN] image multibande
[Termes IGN] image Terra-MODIS
[Termes IGN] itérationRésumé : (auteur) The development of remote sensing has enabled the acquisition of information on land-cover change at different spatial scales. However, a trade-off between spatial and temporal resolutions normally exists. Fine-spatial-resolution images have low temporal resolutions, whereas coarse spatial resolution images have high temporal repetition rates. A novel super-resolution change detection method (SRCD) is proposed to detect land-cover changes at both fine spatial and temporal resolutions with the use of a coarse-resolution image and a fine-resolution land-cover map acquired at different times. SRCD is an iterative method that involves endmember estimation, spectral unmixing, land-cover fraction change detection, and super-resolution land-cover mapping. Both the land-cover change/no-change map and from–to change map at fine spatial resolution can be generated by SRCD. In this study, SRCD was applied to synthetic multispectral image, Moderate-Resolution Imaging Spectroradiometer (MODIS) multispectral image and Landsat-8 Operational Land Imager (OLI) multispectral image. The land-cover from–to change maps are found to have the highest overall accuracy (higher than 85%) in all the three experiments. Most of the changed land-cover patches, which were larger than the coarse-resolution pixel, were correctly detected. Numéro de notice : A2016--122 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2528583 En ligne : https://doi.org/10.1109/TGRS.2016.2528583 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84900
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 7 (July 2016) . - pp 3822 - 3841[article]Estimating forest and woodland aboveground biomass using active and passive remote sensing / Zhuoting Wu in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 4 (April 2016)
[article]
Titre : Estimating forest and woodland aboveground biomass using active and passive remote sensing Type de document : Article/Communication Auteurs : Zhuoting Wu, Auteur ; Dennis Dye, Auteur ; John Vogel, Auteur ; Barry Middleton, Auteur Année de publication : 2016 Article en page(s) : pp 271 - 281 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Arizona (Etats-Unis)
[Termes IGN] biomasse aérienne
[Termes IGN] biomasse forestière
[Termes IGN] capteur actif
[Termes IGN] capteur passif
[Termes IGN] données lidar
[Termes IGN] écosystème forestier
[Termes IGN] hauteur des arbres
[Termes IGN] image Landsat-8
[Termes IGN] surface forestièreRésumé : (auteur) Aboveground biomass was estimated from active and passive remote sensing sources, including airborne lidar and Landsat-8 satellites, in an eastern Arizona (USA) study area comprised of forest and woodland ecosystems. Compared to field measurements, airborne lidar enabled direct estimation of individual tree height with a slope of 0.98 (R2 = 0.98). At the plot-level, lidar-derived height and intensity metrics provided the most robust estimate for aboveground biomass, producing dominant species-based aboveground models with errors ranging from 4 to 14 Mg ha –1 across all woodland and forest species. Landsat-8 imagery produced dominant species-based aboveground biomass models with errors ranging from 10 to 28 Mg ha –1. Thus, airborne lidar allowed for estimates for fine-scale aboveground biomass mapping with low uncertainty, while Landsat-8 seems best suited for broader spatial scale products such as a national biomass essential climate variable (ECV) based on land cover types for the United States. Numéro de notice : A2016-179 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14358/PERS.82.4.271 En ligne : http://dx.doi.org/10.14358/PERS.82.4.271 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80521
in Photogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 4 (April 2016) . - pp 271 - 281[article]An assessment of image features and random forest for land cover mapping over large areas using high resolution Satellite Image Time Series / Charlotte Pelletier (2016)
Titre : An assessment of image features and random forest for land cover mapping over large areas using high resolution Satellite Image Time Series Type de document : Article/Communication Auteurs : Charlotte Pelletier, Auteur ; Silvia Valero, Auteur ; Jordi Inglada, Auteur ; Gérard Dedieu, Auteur ; Nicolas Champion , Auteur Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2016 Conférence : IGARSS 2016, International Geoscience And Remote Sensing Symposium 10/07/2016 15/07/2016 Pékin Chine Proceedings IEEE Importance : pp 3338 - 3341 Note générale : bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] image à haute résolution
[Termes IGN] image Landsat-8
[Termes IGN] image SPOT 4
[Termes IGN] série temporelleRésumé : (auteur) New high resolution Satellite Image Time Series (SITS) are becoming crucial to land cover mapping over large areas. Their high temporal resolution will allow to better depict scene dynamics. However, it will also increase the amount of data to process. The classification of these data involves therefore new challenges such as: (1) selecting the best feature set to use as input data, (2) dealing with data variability coming from landscape diversity, and (3) establishing the robustness of existing classifiers over large areas. This work aims at addressing these questions through three different studies. Experimental results are obtained by using SPOT-4 and Landsat-8 SITS. Numéro de notice : C2016-034 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/IGARSS.2016.7729863 Date de publication en ligne : 03/11/2016 En ligne : https://doi.org/10.1109/IGARSS.2016.7729863 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91791 Automatic detection of clouds and shadows using high resolution satellite image time series / Nicolas Champion (2016)PermalinkA Bayesian network-based method to alleviate the ill-posed inverse problem: A case study on leaf area index and canopy water content retrieval / Xingwen Quan in IEEE Transactions on geoscience and remote sensing, vol 53 n° 12 (December 2015)PermalinkExamining the potential of Sentinel-2 MSI spectral resolution in quantifying above ground biomass across different fertilizer treatments / Mbulisi Sibanda in ISPRS Journal of photogrammetry and remote sensing, vol 110 (December 2015)PermalinkInvestigating 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)PermalinkLand 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)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)PermalinkEvaluating the utility of the medium-spatial resolution Landsat 8 multispectral sensor in quantifying aboveground biomass in uMgeni catchment, South Africa / Timothy Dube in ISPRS Journal of photogrammetry and remote sensing, vol 101 (March 2015)PermalinkSensitivity analysis of a bio-optical model for Italian lakes focused on Landsat-8, Sentinel-2 and Sentinel-3 / Ciro Manzo in European journal of remote sensing, vol 48 n° 1 (2015)PermalinkVegetation Burn Severity Mapping Using Landsat-8 and WorldView-2 / Zhuoting Wu in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 2 (February 2015)Permalink