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Bathymetry and benthic habitat mapping in shallow waters from Sentinel-2A imagery: A case study in Xisha islands, China / Wei Huang in IEEE Transactions on geoscience and remote sensing, vol 60 n° 12 (December 2022)
[article]
Titre : Bathymetry and benthic habitat mapping in shallow waters from Sentinel-2A imagery: A case study in Xisha islands, China Type de document : Article/Communication Auteurs : Wei Huang, Auteur ; Jun Zhao, Auteur ; Bin Ai, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 4212412 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] bathymétrie
[Termes IGN] carte thématique
[Termes IGN] Chine
[Termes IGN] correction atmosphérique
[Termes IGN] fond marin
[Termes IGN] habitat d'espèce
[Termes IGN] image hyperspectrale
[Termes IGN] image Sentinel-MSI
[Termes IGN] profondeur
[Termes IGN] réflectance spectraleRésumé : (auteur) Mapping of benthic habitats and bathymetry is crucial for sustainable development and assessment of climate change and human activities. In this study, Hyperspectral Optimization Process Exemplar (HOPE) was modified, renamed as M-HOPE, to simultaneously obtain bathymetry and benthic habitat in shallow waters in Xisha Island, China. A local lookup table (LUT) for benthic reflectance spectra was established. Validation using in situ measurements demonstrated good performance of M-HOPE with a R2 of 0.76 for bathymetry using the local LUT. Application of M-HOPE to Sentinel-2A imagery further proved good accuracy of M-HOPE derived bathymetry with a R2 of 0.86 against in situ observations and a R2 of 0.92 against ICESat-2 measurements. M-HOPE-derived benthic classification also agreed well with field observations with probability of detection (POD) >0.6 and false alarm ratio (FAR) Numéro de notice : A2022-907 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2022.3229029 Date de publication en ligne : 14/12/2022 En ligne : https://doi.org/10.1109/TGRS.2022.3229029 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102338
in IEEE Transactions on geoscience and remote sensing > vol 60 n° 12 (December 2022) . - n° 4212412[article]Bayesian hyperspectral image super-resolution in the presence of spectral variability / Fei Ye in IEEE Transactions on geoscience and remote sensing, vol 60 n° 12 (December 2022)
[article]
Titre : Bayesian hyperspectral image super-resolution in the presence of spectral variability Type de document : Article/Communication Auteurs : Fei Ye, Auteur ; Zebin Wu, Auteur ; Yang Xu, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 5545613 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] fusion d'images
[Termes IGN] image hyperspectrale
[Termes IGN] image multibande
[Termes IGN] processus gaussien
[Termes IGN] réflectance
[Termes IGN] signature spectrale
[Termes IGN] théorème de BayesRésumé : (auteur) Synthesizing a high-resolution (HR) hyperspectral image (HSI) by merging a low-resolution (LR) HSI with a corresponding HR multispectral image (MSI) has become a promising HSI super-resolution scheme. Most existing HSI-MSI fusion methods are effective to some extent, while several challenges remain. First, the spectral response of a given material exhibits considerable variability due to different acquisition times and conditions, however, variations in spectral signatures are often neglected. Second, a majority of off-the-shelf methods require predefined degradation operators, which can be unavailable in practice. To tackle the above issues, we introduce a novel fusion approach with a Bayesian framework. Specifically, we regard the up-sampled LR-HSI as the low-frequency component of the underlying HR-HSI. We characterize the texture features of high- and low-frequency components, respectively, which can enlarge modeling capacity and bypass the absence of degradation operators. Furthermore, we depict the relative smoothness of reflectance spectra with the Gaussian process. Extensive experiments on synthesized and real datasets illustrate the superiority of the proposed strategy in terms of fusion performance and robustness to spectral variability. Numéro de notice : A2022-908 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2022.3228313 Date de publication en ligne : 12/12/2022 En ligne : https://doi.org/10.1109/TGRS.2022.3228313 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102339
in IEEE Transactions on geoscience and remote sensing > vol 60 n° 12 (December 2022) . - n° 5545613[article]Fusion of SAR and multi-spectral time series for determination of water table depth and lake area in peatlands / Katrin Krzepek in PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science, vol 90 n° 6 (December 2022)
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Titre : Fusion of SAR and multi-spectral time series for determination of water table depth and lake area in peatlands Type de document : Article/Communication Auteurs : Katrin Krzepek, Auteur ; Jacob Schmidt, Auteur ; Dorota Iwaszczuk, Auteur Année de publication : 2022 Article en page(s) : pp 561 - 575 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] apprentissage non-dirigé
[Termes IGN] aquifère
[Termes IGN] Bade-Wurtemberg (Allemagne)
[Termes IGN] bande C
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] fusion d'images
[Termes IGN] image multibande
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Sentinel-SAR
[Termes IGN] Normalized Difference Water Index
[Termes IGN] puits de carbone
[Termes IGN] seuillage d'image
[Termes IGN] théorie de Dempster-Shafer
[Termes IGN] tourbièreRésumé : (auteur) Peatlands as natural carbon sinks have a major impact on the climate balance and should therefore be monitored and protected. The hydrology of the peatland serves as an indicator of the carbon storage capacity. Hence, we investigate the question how suitable different remote sensing data are for monitoring the size of open water surface and the water table depth (WTD) of a peatland ecosystem. Furthermore, we examine the potential of combining remote sensing data for this purpose. We use C-band synthetic aperture radar (SAR) data from Sentinel-1 and multi-spectral data from Sentinel-2. The radar backscatter σ0, the normalized difference water index (NDWI) and the modified normalized difference water index (MNDWI) are calculated and used for consideration of the WTD and the lake size. For the measurement of the lake size, we implement and investigate the methods: random forest, adaptive thresholding and an analysis according to the Dempster–Shafer theory. Correlations between WTD and the remote sensing data σ0 as well as NDWI are investigated. When looking at the individual data sets the results of our case study show that the VH polarized σ0 data produces the clearest delineation of the peatland lake. However the adaptive thresholding of the weighted fusion image of σ0-VH, σ0-VV and MNDWI, and the random forest algorithm with all three data sets as input proves to be the most suitable for determining the lake area. The correlation coefficients between σ0/NDWI and WTD vary greatly and lie in ranges of low to moderate correlation. Numéro de notice : A2022-942 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s41064-022-00216-w Date de publication en ligne : 06/09/2022 En ligne : https://doi.org/10.1007/s41064-022-00216-w Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102876
in PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science > vol 90 n° 6 (December 2022) . - pp 561 - 575[article]Georeferencing accuracy assessment of historical aerial photos using a custom-built online georeferencing tool / Su Zhang in ISPRS International journal of geo-information, vol 11 n° 12 (December 2022)
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Titre : Georeferencing accuracy assessment of historical aerial photos using a custom-built online georeferencing tool Type de document : Article/Communication Auteurs : Su Zhang, Auteur ; Hays A. Barrett, Auteur ; Shirley V. Baros, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 582 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie
[Termes IGN] application web
[Termes IGN] ArcGIS
[Termes IGN] ArcMap
[Termes IGN] géoréférencement indirect
[Termes IGN] image ancienne
[Termes IGN] photographie aérienne
[Termes IGN] point d'appui
[Termes IGN] précision du positionnement
[Termes IGN] standard OGCRésumé : (auteur) As one of the earliest forms of remote sensing, aerial photography has been regarded as an important part of the mapmaking process. Aerial photos, especially historical aerial photos, provide significant amount of valuable information for many applications and fields. However, due to limited funding support, most historical aerial photos have not been digitized and georeferenced yet, which substantially limits their utility for today’s computer-based image processing and analysis. Traditionally, historical aerial photos are georeferenced with desktop GIS software applications. However, this method is expensive, time-consuming, and labor-intensive. To address these limitations, this research developed a custom-built online georeferencing tool to enable georeferencing digitized historical aerial photos in a web environment, which is able to georeference historical aerial photos in a rapid and cost-effective manner. To evaluate the georeferencing performance, a set of 50 historical aerial photos were georeferenced with not only the developed online georeferencing tool but also two commercial desktop software programs. Research results revealed the custom-built online georeferencing tool provided the highest degree of accuracy while maximizing its accessibility. Numéro de notice : A2022-860 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/ijgi11120582 Date de publication en ligne : 22/11/2022 En ligne : https://doi.org/10.3390/ijgi11120582 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102177
in ISPRS International journal of geo-information > vol 11 n° 12 (December 2022) . - n° 582[article]Hyperspectral imagery and urban areas: results of the HYEP project / Christiane Weber in Revue Française de Photogrammétrie et de Télédétection, n° 224 (2022)
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Titre : Hyperspectral imagery and urban areas: results of the HYEP project Type de document : Article/Communication Auteurs : Christiane Weber, Auteur ; Xavier Briottet , Auteur ; Thomas Houet, Auteur ; Sébastien Gadal, Auteur ; Rahim Aguejdad, Auteur ; Yannick Deville, Auteur ; Mauro Dalla Mura, Auteur ; Clément Mallet , Auteur ; Arnaud Le Bris , Auteur ; et al., Auteur Année de publication : 2022 Projets : HYEP / Weber, Christiane Article en page(s) : pp 75 - 92 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse comparative
[Termes IGN] détection d'objet
[Termes IGN] fusion d'images
[Termes IGN] image hyperspectrale
[Termes IGN] Lituanie
[Termes IGN] milieu urbain
[Termes IGN] panneau photovoltaïque
[Termes IGN] surface imperméable
[Termes IGN] ToulouseRésumé : (Auteur) The HYEP project (ANR HYEP 14-CE22-0016-01 Hyperspectral imagery for Environmental urban Planning - Mobility and Urban Systems Programme - 2014) confirmed the interest of a global approach to the urban environment by remote sensing and in particular by using hyperspectral imaging (HI). The interest of hyperspectral images lies in the range of information provided over wavelengths from 0.4 to 4 μm; they thus provide access to spectral quantities of interest and to chemical or biophysical parameters of the surface. HYEP's objective was to specify this and to propose a panel of methods and treatments taking into account the characteristics of other existing sensors in order to compare their performance. The developments carried out were applied and evaluated on hyperspectral airborne images acquired in Toulouse and Kaunas (Lithuania), also used to synthesize space systems: Sentinel-2, Hypxim/Biodiversity and Pleiades. Among the locks identified were those related to improving the spatial capabilities of the sensors and spatial scale changes, which were partially overcome by fusion and sharpening approaches, which proved to be successful. After a description of our hyperspectral data set acquired over Toulouse, an analysis is conducted on several existing and accessible spectral databases. Then, the chosen methods are presented. They include extraction, fusion and classification methods, which are then applied on our dataset synthetized at different spatial resolution to evaluate the benefits and the complementarity of hyperspectral imagery in comparison with other traditional sensors. Some specific applications are investigated of interest for urban planners: impervious soil map, vegetation species cartography and detection of solar panels. Finally, discussion and perspectives are presented. Numéro de notice : A2022-941 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Autre URL associée : Hal Thématique : IMAGERIE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : 10.52638/rfpt.2022.589 Date de publication en ligne : 22/12/2022 En ligne : https://dx.doi.org/10.52638/rfpt.2022.589 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102831
in Revue Française de Photogrammétrie et de Télédétection > n° 224 (2022) . - pp 75 - 92[article]Instance segmentation of standing dead trees in dense forest from aerial imagery using deep learning / Aboubakar Sani-Mohammed in ISPRS Open Journal of Photogrammetry and Remote Sensing, vol 6 (December 2022)PermalinkMapping impervious surfaces with a hierarchical spectral mixture analysis incorporating endmember spatial distribution / Zhenfeng Shao in Geo-spatial Information Science, vol 25 n° 4 (December 2022)PermalinkCross-guided pyramid attention-based residual hyperdense network for hyperspectral image pansharpening / Jiahui Qu in IEEE Transactions on geoscience and remote sensing, vol 60 n° 11 (November 2022)PermalinkForeground-aware refinement network for building extraction from remote sensing images / Zhang Yan in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 11 (November 2022)PermalinkA high-resolution panchromatic-multispectral satellite image fusion method assisted with building segmentation / Fang Gao in Computers & geosciences, vol 168 (November 2022)PermalinkA joint deep learning network of point clouds and multiple views for roadside object classification from lidar point clouds / Lina Fang in ISPRS Journal of photogrammetry and remote sensing, vol 193 (November 2022)PermalinkMapping forest in the Swiss Alps treeline ecotone with explainable deep learning / Thiên-Anh Nguyen in Remote sensing of environment, vol 281 (November 2022)PermalinkMeasuring visual walkability perception using panoramic street view images, virtual reality, and deep learning / Yunqin Li in Sustainable Cities and Society, vol 86 (November 2022)PermalinkA deep 2D/3D Feature-Level fusion for classification of UAV multispectral imagery in urban areas / Hossein Pourazar in Geocarto international, vol 37 n° 23 ([15/10/2022])PermalinkLand use/land cover mapping from airborne hyperspectral images with machine learning algorithms and contextual information / Ozlem Akar in Geocarto international, vol 37 n° 22 ([10/10/2022])PermalinkApplication of a graph convolutional network with visual and semantic features to classify urban scenes / Yongyang Xu in International journal of geographical information science IJGIS, vol 36 n° 10 (October 2022)PermalinkChallenges and limitations of earthquake-induced building damage mapping techniques using remote sensing images : A systematic review / Sahar S. Matin in Geocarto international, Vol 37 n° 21 ([01/10/2022])PermalinkChallenging the link between functional and spectral diversity with radiative transfer modeling and data / Javier Pacheco-Labradora in Remote sensing of environment, vol 280 (October 2022)PermalinkEvaluation of Landsat 8 image pansharpening in estimating soil organic matter using multiple linear regression and artificial neural networks / Abdelkrim Bouasria in Geo-spatial Information Science, vol 25 n° 3 (October 2022)PermalinkInvestigation of recognition and classification of forest fires based on fusion color and textural features of images / Cong Li in Forests, vol 13 n° 10 (October 2022)PermalinkAttention mechanisms in computer vision: A survey / Meng-Hao Guo in Computational Visual Media, vol 8 n° 3 (September 2022)PermalinkClassification of pine wilt disease at different infection stages by diagnostic hyperspectral bands / Niwen Li in Ecological indicators, vol 142 (September 2022)PermalinkCrowdsourcing-based application to solve the problem of insufficient training data in deep learning-based classification of satellite images / Ekrem Saralioglu in Geocarto international, vol 37 n° 18 ([01/09/2022])PermalinkLearning indoor point cloud semantic segmentation from image-level labels / Youcheng Song in The Visual Computer, vol 38 n° 9 (September 2022)PermalinkDetection of potential gold mineralization areas using MF-fuzzy approach on multispectral data / Tohid Nouri in Geocarto international, Vol 37 n° 17 ([20/08/2022])Permalink