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Uncertainty analysis of remotely-acquired thermal infrared data to extract the thermal Properties of active lava surfaces / James A. Thompson in Remote sensing, vol 12 n° 1 (January 2020)
[article]
Titre : Uncertainty analysis of remotely-acquired thermal infrared data to extract the thermal Properties of active lava surfaces Type de document : Article/Communication Auteurs : James A. Thompson, Auteur ; Michael S. Ramsey, Auteur Année de publication : 2020 Article en page(s) : 21 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Advanced Spaceborne Thermal Emission and Reflection Radiometer
[Termes IGN] classification pixellaire
[Termes IGN] éruption volcanique
[Termes IGN] image MASTER
[Termes IGN] image thermique
[Termes IGN] incertitude des données
[Termes IGN] Kilauea (volcan)
[Termes IGN] lave
[Termes IGN] rayonnement infrarouge thermique
[Termes IGN] surveillance géologique
[Termes IGN] température
[Termes IGN] volcanRésumé : (auteur) Using thermal infrared (TIR) data from multiple instruments and platforms for analysis of an entire active volcanic system is becoming more common with the increasing availability of new data. However, the accuracy and uncertainty associated with these combined datasets are poorly constrained over the full range of eruption temperatures and possible volcanic products. Here, four TIR datasets acquired over active lava surfaces are compared to quantify the uncertainty, accuracy, and variability in derived surface radiance, emissivity, and kinetic temperature. These data were acquired at Kīlauea volcano in Hawai’i, USA, in January/February 2017 and 2018. The analysis reveals that spatial resolution strongly limits the accuracy of the derived surface thermal properties, resulting in values that are significantly below the expected values for molten basaltic lava at its liquidus temperature. The surface radiance is ~2400% underestimated in the orbital data compared to only ~200% in ground-based data. As a result, the surface emissivity is overestimated and the kinetic temperature is underestimated by at least 30% and 200% in the airborne and orbital datasets, respectively. A thermal mixed pixel separation analysis is conducted to extract only the molten fraction within each pixel in an attempt to mitigate this complicating factor. This improved the orbital and airborne surface radiance values to within 15% of the expected values and the derived emissivity and kinetic temperature within 8% and 12%, respectively. It is, therefore, possible to use moderate spatial resolution TIR data to derive accurate and reliable emissivity and kinetic temperatures of a molten lava surface that are comparable to the higher resolution data from airborne and ground-based instruments. This approach, resulting in more accurate kinetic temperature and emissivity of the active surfaces, can improve estimates of flow hazards by greatly improving lava flow propagation models that rely on these data. Numéro de notice : A2020-224 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs12010193 Date de publication en ligne : 05/01/2020 En ligne : https://doi.org/10.3390/rs12010193 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94939
in Remote sensing > vol 12 n° 1 (January 2020) . - 21 p.[article]Novel adaptive histogram trend similarity approach for land cover change detection by using bitemporal very-high-resolution remote sensing images / Zhi Yong Lv in IEEE Transactions on geoscience and remote sensing, vol 57 n° 12 (December 2019)
[article]
Titre : Novel adaptive histogram trend similarity approach for land cover change detection by using bitemporal very-high-resolution remote sensing images Type de document : Article/Communication Auteurs : Zhi Yong Lv, Auteur ; Tong Fei Liu, Auteur ; Zhang Penglin, Auteur ; Jon Atli Benediktsson, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 9554 - 9574 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse diachronique
[Termes IGN] changement d'occupation du sol
[Termes IGN] Chine
[Termes IGN] classification pixellaire
[Termes IGN] détection de changement
[Termes IGN] histogramme
[Termes IGN] Hong-Kong
[Termes IGN] image à très haute résolution
[Termes IGN] phénologie
[Termes IGN] seuillage de pointsRésumé : (auteur) Detecting land cover change through very-high-resolution (VHR) remote sensing images is helpful in supporting urban sustainable development, natural disaster evaluation, and environmental assessment. However, the intraclass spectral variance in VHR remote sensing images is usually larger than that of median-low remote sensing images. Furthermore, the bitemporal images are usually acquired under different atmospheric conditions, sun height, soil moisture, and other factors. Consequently, in practical applications, many pseudo changes are presented in the detected map. In this paper, an adaptive histogram trend (AHT) similarity approach is promoted to quantitatively measure the magnitude between the corresponding pixels in bitemporal images in terms of change semantic. In the proposed approach, to reduce the phenological effect on the bitemporal images of land cover change detection (LCCD), we first define the quantitative description of AHT. Second, the change magnitudes between pairwise pixels are quantitatively measured by an improved bin-to-bin (B2B) distance between the corresponding AHTs. Then, the change magnitudes between two entire bitemporal images are measured AHT-by-AHT. Finally, binary threshold methods, such as the Otsu method or the double-window flexible pace search (DFPS) method, are used to divide the change magnitude image into binary change detection maps and obtain the final change detection map. The performance of the AHT-based LCCD approach is verified by four pairs of VHR remote-sensing images that correspond to two types of real land cover change cases. The detected results based on the four pairs of bitemporal VHR images outperformed the compared state-of-the-art LCCD methods. Numéro de notice : A2019-599 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2927659 Date de publication en ligne : 01/08/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2927659 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94593
in IEEE Transactions on geoscience and remote sensing > vol 57 n° 12 (December 2019) . - pp 9554 - 9574[article]A temporal phase coherence estimation algorithm and its application on DInSAR pixel selection / Feng Zhao in IEEE Transactions on geoscience and remote sensing, vol 57 n° 11 (November 2019)
[article]
Titre : A temporal phase coherence estimation algorithm and its application on DInSAR pixel selection Type de document : Article/Communication Auteurs : Feng Zhao, Auteur ; Jordi J. Mallorquí, Auteur Année de publication : 2019 Article en page(s) : pp 8350 - 8361 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] amplitude
[Termes IGN] Barcelone
[Termes IGN] classification pixellaire
[Termes IGN] cohérence temporelle
[Termes IGN] image radar moirée
[Termes IGN] image Radarsat
[Termes IGN] interferométrie différentielle
[Termes IGN] mesurage de phaseRésumé : (auteur) Pixel selection is a crucial step of all advanced Differential Interferometric Synthetic Aperture Radar (DInSAR) techniques that have a direct impact on the quality of the final DInSAR products. In this paper, a full-resolution phase quality estimator, i.e., the temporal phase coherence (TPC), is proposed for DInSAR pixel selection. The method is able to work with both distributed scatterers (DSs) and permanent scatterers (PSs). The influence of different neighboring window sizes and types of interferograms combinations [both the single-master (SM) and the multi-master (MM)] on TPC has been studied. The relationship between TPC and phase standard deviation (STD) of the selected pixels has also been derived. Together with the classical coherence and amplitude dispersion methods, the TPC pixel selection algorithm has been tested on 37 VV polarization Radarsat-2 images of Barcelona Airport. Results show the feasibility and effectiveness of TPC pixel selection algorithm. Besides obvious improvements in the number of selected pixels, the new method shows some other advantages comparing with the other classical two. The proposed pixel selection algorithm, which presents an affordable computational cost, is easy to be implemented and incorporated into any advanced DInSAR processing chain for high-quality pixels' identification. Numéro de notice : A2019-593 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2920536 Date de publication en ligne : 16/07/2019 En ligne : http://doi.org/10.1109/TGRS.2019.2920536 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94585
in IEEE Transactions on geoscience and remote sensing > vol 57 n° 11 (November 2019) . - pp 8350 - 8361[article]Segmenting mangrove ecosystems drone images using SLIC superpixels / Edward Zimudzi in Geocarto international, vol 34 n° 14 ([30/10/2019])
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Titre : Segmenting mangrove ecosystems drone images using SLIC superpixels Type de document : Article/Communication Auteurs : Edward Zimudzi, Auteur ; Ian Sanders, Auteur ; Nicholas Rollings, Auteur ; Christian Omlin, Auteur Année de publication : 2019 Article en page(s) : pp 1648 - 1662 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] algorithme SLIC
[Termes IGN] classification par nuées dynamiques
[Termes IGN] classification pixellaire
[Termes IGN] écosystème
[Termes IGN] Fidji
[Termes IGN] image captée par drone
[Termes IGN] mangrove
[Termes IGN] modèle numérique de surface
[Termes IGN] orthophotoplan numérique
[Termes IGN] segmentation d'image
[Termes IGN] superpixelRésumé : (auteur) Mangrove ecosystems play a very important ecological role on land–ocean interfaces in tropical regions. These ecosystems comprise of various tree species and aquatic animals, protecting the environment and providing a habitat that supports many living organisms including humans. The identification of image regions in mangrove ecosystems plays a significant role in ecosystem monitoring and conservation. Recent studies have suggested oversegmentation of colour images using superpixels as a solution to the segmentation of image regions. This study used the SLIC superpixel algorithm and k-means clustering to segment images taken from a camera mounted on a drone from a mangrove ecosystem in Fiji. The SLIC superpixel algorithm performed well to demarcate image regions with similar colour and texture information into patches and to use k-means for the segmentation of the whole image. These results lend support to the use of superpixel algorithms for the segmentation of mangrove ecosystems. Understanding how superpixels can be used for the segmentation of drone images will assist conservation efforts in mangrove ecosystems. Numéro de notice : A2019-539 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1497093 Date de publication en ligne : 22/10/2018 En ligne : https://doi.org/10.1080/10106049.2018.1497093 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94114
in Geocarto international > vol 34 n° 14 [30/10/2019] . - pp 1648 - 1662[article]Large scale semi-automatic detection of forest roads from low density LiDAR data on steep terrain in Northern Spain / Convadonga Prendes in iForest, biogeosciences and forestry, vol 12 n° 4 (July 2019)
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Titre : Large scale semi-automatic detection of forest roads from low density LiDAR data on steep terrain in Northern Spain Type de document : Article/Communication Auteurs : Convadonga Prendes, Auteur ; Sandra Bujan, Auteur ; Celestino Ordóñez, Auteur ; Elena Canga, Auteur Année de publication : 2019 Article en page(s) : pp 366 - 374 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse d'image orientée objet
[Termes IGN] axe médian
[Termes IGN] chemin forestier
[Termes IGN] classification pixellaire
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] Espagne
[Termes IGN] montagneRésumé : (auteur) While forest roads are important to forest managers in terms of facilitating the exploitation of wood and timber, their role is far more multifunctional. They permit access to emergency services in the case of forest fires as well as acting as fire breaks, enhance biodiversity, and provide access to the public to enjoy recreational activities. Detailed maps of forest roads are an essential tool for better and more timely forest management and automatic/semi-automatic tools allow not only the creation of forest road databases, but also enable these to be updated. In Spain, LiDAR data for the entire national territory is freely available, and the capture of higher density data is planned in the next few years. As such, the development of a forest road detection methodology based on LiDAR data would allow maps of all forest roads to be developed and regularly updated. The general objective of this work was to establish a low density LiDAR data-based methodology for the semi-automatic detection of the centerline of forest roads on steep terrain with various types of canopy cover. Intensity and slope images were generated using the currently available LiDAR data of the study area (0.5 points m-2). Two image classification approaches were evaluated: pixel-based and object-oriented classification (OBIA). The LiDAR-derived centerlines obtained with the two approaches were compared with the real centerlines which had previously been digitized in the field. The road width, type of surface and type of vegetation cover were also recorded. The effectiveness of the two approaches was evaluated through three quality indicators: correctness, completeness and quality. In addition, the accuracy of the LiDAR-derived centerlines was also evaluated by combining GIS analysis and statistical methods. The pixel-based approach obtained higher values than OBIA for two of the three quality measures (correctness: 93% compared to 90%; and quality: 60% compared to 56%) as well as in terms of positional accuracy (± 5.5 m vs. ± 6.8 for OBIA). The results obtained in this study demonstrate that producing road maps is among the most valuable and easily attainable products of LiDAR data analysis. Numéro de notice : A2019-659 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3832/ifor2989-012 Date de publication en ligne : 05/07/2019 En ligne : https://doi.org/10.3832/ifor2989-012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98528
in iForest, biogeosciences and forestry > vol 12 n° 4 (July 2019) . - pp 366 - 374[article]Potentialités de l’imagerie couleur embarquée pour la détection et la cartographie des maladies fongiques de la vigne / Florent Abdelghafour (2019)PermalinkA review of accuracy assesment for object-based image analysis: from per pixel to per-polygon approaches [review article] / Su Ye in ISPRS Journal of photogrammetry and remote sensing, vol 141 (July 2018)PermalinkFusion tardive d’images SPOT 6/7 et de données multitemporelles Sentinel-2 pour la détection de la tache urbaine / Cyril Wendl in Revue Française de Photogrammétrie et de Télédétection, n° 217-218 (juin - septembre 2018)PermalinkEuropean Forest Types: toward an automated classification / Francesca Giannetti in Annals of Forest Science, vol 75 n° 1 (March 2018)PermalinkConception d’une méthode radar de suivi bimensuel des déforestations et d’une méthode optique de classification d’occupation des sols / Luc Baudoux (2018)PermalinkDecision fusion of SPOT6 and multitemporal Sentinel2 images for urban area detection / Cyril Wendl (2018)PermalinkFusion tardive d’images SPOT-6/7 et de données multitemporelles Sentinel-2 pour la détection de la tache urbaine / Cyril Wendl (2018)PermalinkObject-based superresolution land-cover mapping from remotely sensed imagery / Yuehong Chen in IEEE Transactions on geoscience and remote sensing, vol 56 n° 1 (January 2018)PermalinkSuperpixel partitioning of very high resolution satellite images for large-scale classification perspectives with deep convolutional neural networks / Tristan Postadjian (2018)PermalinkTélédétection multispectrale et hyperspectrale des eaux littorales turbides / Morgane Larnicol (2018)Permalink