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Assessment of the Baspa basin glaciers mass budget using different remote sensing methods and modeling techniques / Vinay Kumar Gaddam in Geocarto international, vol 35 n° 3 ([01/03/2020])  

Public [article]  inGeocarto international > vol 35 n° 3 [01/03/2020] . - pp 296 - 316 Titre : Assessment of the Baspa basin glaciers mass budget using different remote sensing methods and modeling techniques Type de document : Article/Communication Auteurs : Vinay Kumar Gaddam, Auteur ; Anil V. Kulkarni, Auteur ; Anil Kumar Gupta, Auteur Année de publication : 2020 Article en page(s) : pp 296 - 316 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] bande C [Termes descripteurs IGN] bilan de masse [Termes descripteurs IGN] cheminement géodésique [Termes descripteurs IGN] détection de changement [Termes descripteurs IGN] échantillonnage de données [Termes descripteurs IGN] fonte des glaces [Termes descripteurs IGN] glacier [Termes descripteurs IGN] Himalaya [Termes descripteurs IGN] MNS ASTER [Termes descripteurs IGN] MNS SRTM [Termes descripteurs IGN] précipitation [Termes descripteurs IGN] température Résumé : (auteur) Glacial melt water is the key source for various socio-industrial and domestic activities in the Himalayas. Several recent studies suggest that glaciers are experiencing rapid melt. The glaciers health can be best assessed by mass balance. However, the mass balance investigations using in-situ methods for a large sample of glaciers are highly difficult in the Himalaya. Hence, remote sensing methods and modelling techniques are preferred. However, there is a lack of information on uncertainties associated with these methods in assessing the regional scale mass balance. Hence, these methods are applied to evaluate the regional scale mass budget of Baspa basin, Western Himalaya between 2000 and 2011. The total mass loss estimated using geodetic method amounts to −0.49 ± 0.1 gigatons, temperature index method to −0.43 ± 0.012 gigatons and AAR method to −0.36 ± 0.1 gigatons. Furthermore, this study highlights the limitations of these methods in mass loss evaluation in data scarce Himalayan regions. Numéro de notice : A2020-055 Nature : Article DOI : 10.1080/10106049.2018.1516247 date de publication en ligne : 06/01/2020 En ligne : https://doi.org/10.1080/10106049.2018.1516247 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94568 [article]

Classifying physiographic regimes on terrain and hydrologic factors for adaptive generalization of stream networks / Lauwrence V. Stanislawski in International journal of cartography, Vol 6 n° 1 (March 2020)  

Public [article]  inInternational journal of cartography > Vol 6 n° 1 (March 2020) . - pp 4 - 21 Titre : Classifying physiographic regimes on terrain and hydrologic factors for adaptive generalization of stream networks Type de document : Article/Communication Auteurs : Lauwrence V. Stanislawski, Auteur ; Michael P. Finn, Auteur ; Barbara P. Buttenfield, Auteur Année de publication : 2020 Article en page(s) : pp 4 - 21 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] algorithme de généralisation [Termes descripteurs IGN] altitude [Termes descripteurs IGN] base de données hydrographiques [Termes descripteurs IGN] cartographie des flux [Termes descripteurs IGN] classification dirigée [Termes descripteurs IGN] classification par maximum de vraisemblance [Termes descripteurs IGN] cours d'eau [Termes descripteurs IGN] drainage [Termes descripteurs IGN] Etats-Unis [Termes descripteurs IGN] pente [Termes descripteurs IGN] perméabilité du sol [Termes descripteurs IGN] représentation multiple [Termes descripteurs IGN] réseau hydrographique [Termes descripteurs IGN] ruissellement [Termes descripteurs IGN] segmentation [Termes descripteurs IGN] traitement automatique de données [Vedettes matières IGN] Généralisation Résumé : (auteur) Automated generalization software must accommodate multi-scale representations of hydrographic networks across a variety of geographic landscapes, because scale-related hydrography differences are known to vary in different physical conditions. While generalization algorithms have been tailored to specific regions and landscape conditions by several researchers in recent years, the selection and characterization of regional conditions have not been formally defined nor statistically validated. This paper undertakes a systematic classification of landscape types in the conterminous United States to spatially subset the country into workable units, in preparation for systematic tailoring of generalization workflows that preserve hydrographic characteristics. The classification is based upon elevation, standard deviation of elevation, slope, runoff, drainage and bedrock density, soil and bedrock permeability, area of inland surface water, infiltration-excess of overland flow, and a base flow index. A seven class solution shows low misclassification rates except in areas of high landscape diversity such as the Appalachians, Rocky Mountains, and Western coastal regions. Numéro de notice : A2020-070 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/23729333.2018.1443759 date de publication en ligne : 20/03/2018 En ligne : https://doi.org/10.1080/23729333.2018.1443759 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94632 [article]

Integrated edge detection and terrain analysis for agricultural terrace delineation from remote sensing images / Wen Dai in International journal of geographical information science IJGIS, vol 34 n° 3 (March 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 3 (March 2020) . - pp 484 - 503 Titre : Integrated edge detection and terrain analysis for agricultural terrace delineation from remote sensing images Type de document : Article/Communication Auteurs : Wen Dai, Auteur ; Jiaming Na, Auteur ; Nan Huang, Auteur Année de publication : 2020 Article en page(s) : pp 484 - 503 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes descripteurs IGN] analyse des risques [Termes descripteurs IGN] cartographie automatique [Termes descripteurs IGN] Chine [Termes descripteurs IGN] délimitation [Termes descripteurs IGN] détection de contours [Termes descripteurs IGN] effet d'ombre [Termes descripteurs IGN] érosion [Termes descripteurs IGN] Google Earth [Termes descripteurs IGN] humidité du sol [Termes descripteurs IGN] image satellite [Termes descripteurs IGN] image Worldview [Termes descripteurs IGN] méthode robuste [Termes descripteurs IGN] MNS ASTER [Termes descripteurs IGN] modèle numérique de surface [Termes descripteurs IGN] modèle numérique de terrain [Termes descripteurs IGN] production agricole [Termes descripteurs IGN] superposition d'images [Termes descripteurs IGN] terrasse Résumé : (auteur) Agricultural terraces are important for agricultural production and soil-and-water conservation. They comprise treads and risers that require manual construction and maintenance. If managed improperly, risers will collapse, causing soil loss, gully erosion, and cultivation threats. However, mapping terrace risers remains a challenge. This study presents a novel approach to automatically map terrace risers by combining remote sensing images and digital elevation models (DEMs). First, a terraced hillslope was extracted via a hill-shading method and edges in the image were detected using a Canny edge detector. Next, the DEM was used to generate the contour direction, and edges along this direction were searched and coded as candidate terrace risers via directional detection. Finally, the results of directional detection and the edge image obtained from the Canny detector were overlaid to backtrack complete terrace risers. The approach was validated using four study areas with different topographic characteristics in the Loess Plateau, China. The results verify that the approach achieves outstanding performance and robustness in mapping terrace risers. The precision, recall, and F-measure were 90.81%–97.57%, 88.53%–94.10%, and 90.13%–95.80%, respectively. This approach is flexible and applicable with freely available images and DEM sources. Numéro de notice : A2020-105 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1650363 date de publication en ligne : 22/08/2019 En ligne : https://doi.org/10.1080/13658816.2019.1650363 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94701 [article]

A LiDAR–optical data fusion approach for identifying and measuring small stream impoundments and dams / Benjamin Swan in Transactions in GIS, Vol 24 n° 1 (February 2020)  

Public [article]  inTransactions in GIS > Vol 24 n° 1 (February 2020) . - pp 174 - 188 Titre : A LiDAR–optical data fusion approach for identifying and measuring small stream impoundments and dams Type de document : Article/Communication Auteurs : Benjamin Swan, Auteur ; Robert Griffin, Auteur Année de publication : 2020 Article en page(s) : pp 174 - 188 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte [Termes descripteurs IGN] Alabama (Etats-Unis) [Termes descripteurs IGN] barrage [Termes descripteurs IGN] cours d'eau [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] écosystème [Termes descripteurs IGN] fusion de données [Termes descripteurs IGN] image à haute résolution [Termes descripteurs IGN] image optique [Termes descripteurs IGN] image Sentinel-MSI [Termes descripteurs IGN] modèle numérique de surface [Termes descripteurs IGN] Normalized Difference Water Index [Termes descripteurs IGN] ressources en eau [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] surveillance hydrologique [Termes descripteurs IGN] système d'information géographique Résumé : (auteur) This article outlines a semi‐autonomous approach for using a fusion of light detection and ranging (LiDAR) and optical remote sensing data to identify and measure small impoundments (SIs) and their dams. Quantifying such water bodies as hydrologic network features is critical for ecosystem and species conservation, emergency management, and water resource planning; however, such features are incompletely mapped at national and state levels. By merging an airborne LiDAR‐derived point cloud with a normalized water index using airborne optical imagery we demonstrate an improvement upon single‐source methods for identifying these water bodies; classification accuracies increased over 10% by using this multi‐source fusion method. Furthermore, the method presented here illustrates a cost‐effective pathway to improve the National Inventory of Dams (NID) and includes a framework for estimating dam heights, with results showing strong correlations between derived dam heights and those recorded in the NID (r=.78). With the steady increase in available LiDAR coverage, the 87,000+ dams in the NID could be updated using this technique, a method which could also be expanded for global inventories of SIs and dams. Numéro de notice : A2020-103 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12595 date de publication en ligne : 13/11/2019 En ligne : https://doi.org/10.1111/tgis.12595 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94694 [article]

Real-time mapping of natural disasters using citizen update streams / Iranga Subasinghe in International journal of geographical information science IJGIS, vol 34 n° 2 (February 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 2 (February 2020) . - pp 393 - 421 Titre : Real-time mapping of natural disasters using citizen update streams Type de document : Article/Communication Auteurs : Iranga Subasinghe, Auteur ; Silvia Nittel, Auteur ; Michael Cressey, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 393 - 421 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes descripteurs IGN] approche participative [Termes descripteurs IGN] cartographie collaborative [Termes descripteurs IGN] catastrophe naturelle [Termes descripteurs IGN] classification par réseau neuronal [Termes descripteurs IGN] diagramme de Voronoï [Termes descripteurs IGN] données localisées des bénévoles [Termes descripteurs IGN] effondrement de terrain [Termes descripteurs IGN] incendie [Termes descripteurs IGN] inondation [Termes descripteurs IGN] positionnement cinématique en temps réel [Termes descripteurs IGN] système multi-agents [Termes descripteurs IGN] tempête [Termes descripteurs IGN] temps réel [Termes descripteurs IGN] ville intelligente Résumé : (auteur) Natural disasters such as flooding, wildfires, and mudslides are rare events, but they affect citizens at unpredictable times and the impact on human life can be significant. Citizens located close to events can provide detailed, real-time data streams capturing their event response. Instead of visualizing individual updates, an integrated spatiotemporal map yields ‘big picture’ event information. We investigate the question of whether information from affected citizens is sufficient to generate a map of an unfolding natural disaster. We built the Citizen Disaster Reaction Multi-Agent Simulation (CDR-MAS), a multi-agent system that simulates the reaction of citizens to a natural disaster in an urban region. We proposed an rkNN classification algorithm to aggregate the update streams into a series of colored Voronoi event maps. We simulated the 2018 Montecito Creek mudslide and customized the CDR-MAS with the local environment to systematically generate stream data sets. Our experimental evaluation showed that event mapping based on citizen update streams is significantly influenced by the amount of citizen participation and movement. Compared with a baseline of 100% participation, with 40% citizen participation, the event region was predicted with 40% accuracy, showing that citizen update streams can provide timely information in a smart city. Numéro de notice : A2020-031 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1639185 date de publication en ligne : 15/07/2019 En ligne : https://doi.org/10.1080/13658816.2019.1639185 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94486 [article]

Using Ranked Probability Skill Score (RPSS) as Nonlocal Root-Mean-Square Errors (RMSEs) for Mitigating Wet Bias of Soil Moisture Ocean Salinity (SMOS) Soil Moisture / Ju Hyoung Lee in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 2 (February 2020)  

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Estimation of soil surface water contents for intertidal mudflats using a near-infrared long-range terrestrial laser scanner / Kai Tan in ISPRS Journal of photogrammetry and remote sensing, vol 159 (January 2020)  

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Identification of alpine glaciers in the central Himalayas using fully polarimetric L-Band SAR data / Guo-Hui Yao in IEEE Transactions on geoscience and remote sensing, vol 58 n° 1 (January 2020)  

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Impact of GPS processing on the estimation of snow water equivalent using refracted GPS signals / Ladina Steiner in IEEE Transactions on geoscience and remote sensing, vol 58 n° 1 (January 2020)  

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A thematic mapping method to assess and analyze potential urban hazards and risks caused by flooding / Mohammad Khalid Hossain in Computers, Environment and Urban Systems, vol 79 (January 2020)  

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Inside the ice shelf: using augmented reality to visualise 3D lidar and radar data of Antarctica / Alexandra L. Boghosian in Photogrammetric record, vol 34 n° 168 (December 2019)  

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Polarization dependence of azimuth cutoff from quad-pol SAR images / Huimin Li in IEEE Transactions on geoscience and remote sensing, vol 57 n° 12 (December 2019)  

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Soil and vegetation scattering contributions in L-Band and P-Band polarimetric SAR observations / S. Hamed Alemohammad in IEEE Transactions on geoscience and remote sensing, vol 57 n° 11 (November 2019)  

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Combining machine learning and compact polarimetry for estimating soil moisture from C-Band SAR data / Emanuele Santi in Remote sensing, Vol 11 n° 20 (2 October 2019)  

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Sea ice extent detection in the Bohai Sea using Sentinel-3 OLCI data / Hua Su in Remote sensing, Vol 11 n° 20 (2 October 2019)  

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