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Landslide displacement mapping based on ALOS-2/PALSAR-2 data using image correlation techniques and SAR interferometry: application to the Hell-Bourg landslide (Salazie Circle, La Réunion Island) / Daniel Raucoules in Geocarto international, vol 35 n° 2 ([01/02/2020])
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Titre : Landslide displacement mapping based on ALOS-2/PALSAR-2 data using image correlation techniques and SAR interferometry: application to the Hell-Bourg landslide (Salazie Circle, La Réunion Island) Type de document : Article/Communication Auteurs : Daniel Raucoules, Auteur ; Marcello De Michele, Auteur ; Bertrand Aunay, Auteur Année de publication : 2020 Article en page(s) : pp 113 - 127 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] analyse comparative
[Termes IGN] appariement d'images
[Termes IGN] bande L
[Termes IGN] cartographie géomorphologique
[Termes IGN] déformation de surface
[Termes IGN] données GNSS
[Termes IGN] données spatiotemporelles
[Termes IGN] effondrement de terrain
[Termes IGN] image à haute résolution
[Termes IGN] image ALOS-PALSAR
[Termes IGN] Réunion, île de laRésumé : (Auteur) In the study described here, the capability of space-borne high-resolution L-band synthetic aperture radar (SAR) images (ALOS-2/PALSAR2 data in StripMap SM1 mode) for deriving and mapping two components of the deformation of slow landslides has been investigated. The deformation characterization was carried out on the basis of sub-pixel correlation offset tracking techniques and differential SAR interferometry. On the Hell-Bourg landslide (located on La Réunion Island, with displacements up to about 1 m/year), the deformation maps produced performed significantly better than the C-band or lower-resolution SAR data used in previous studies. A comparison was carried out with Global Navigation Satellite System data acquired on the test site. Even with a reduced image set (seven acquisitions), detailed deformation maps and information on deformation evolution during 2014–2016 could be generated. The combination of L-band data and high resolution was the source of the improved performance provided by this new kind of data. Numéro de notice : A2020-034 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1508311 Date de publication en ligne : 24/09/2018 En ligne : https://doi.org/10.1080/10106049.2018.1508311 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94515
in Geocarto international > vol 35 n° 2 [01/02/2020] . - pp 113 - 127[article]Landslide susceptibility mapping using maximum entropy and support vector machine models along the highway corridor, Garhwal Himalaya / Vijendra Kumar Pandey in Geocarto international, vol 35 n° 2 ([01/02/2020])
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Titre : Landslide susceptibility mapping using maximum entropy and support vector machine models along the highway corridor, Garhwal Himalaya Type de document : Article/Communication Auteurs : Vijendra Kumar Pandey, Auteur ; Hamid Reza Pourghasemi, Auteur ; Milap Chand Sharma, Auteur Année de publication : 2020 Article en page(s) : pp 168 - 187 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage automatique
[Termes IGN] autoroute
[Termes IGN] classification dirigée
[Termes IGN] effondrement de terrain
[Termes IGN] entropie maximale
[Termes IGN] Himalaya
[Termes IGN] image IRS-LISS
[Termes IGN] image Landsat-8
[Termes IGN] Linear Imaging Self-Scanning System
[Termes IGN] modèle statistique
[Termes IGN] mousson
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] séparateur à vaste marge
[Termes IGN] test statistiqueRésumé : (Auteur) The main objective of this study to produce landslide susceptibility zones using maximum entropy (MaxEnt) and support vector machine (SVM) data-driven models along the Tipari to Ghuttu highway corridors in the Garhwal Himalaya. A landslide inventory has been prepared through field surveys and LISS-IV and Landsat 8 satellite images. The datasets of 85 landslides were categorised into training and test sets. In this study 11 landslide conditioning variables were used that are; altitude, slope angle, aspect, plan curvature, topographic wetness index, normalised difference vegetation index (NDVI), land use, soil texture, distance to rivers, distance to faults, and distance to the road. The result produced using MaxEnt and SVM model were subsequently validated using receiver operating characteristics curve (ROC) with test sets of landslide dataset. Both the models have good prediction capabilities. MaxEnt has ROC value of 0.78 while SVM has the highest prediction rate of 0.85. Numéro de notice : A2020-036 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1510038 Date de publication en ligne : 20/09/2018 En ligne : https://doi.org/10.1080/10106049.2018.1510038 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94519
in Geocarto international > vol 35 n° 2 [01/02/2020] . - pp 168 - 187[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)
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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 IGN] Alabama (Etats-Unis)
[Termes IGN] barrage
[Termes IGN] cours d'eau
[Termes IGN] données lidar
[Termes IGN] écosystème
[Termes IGN] fusion de données
[Termes IGN] image à haute résolution
[Termes IGN] image optique
[Termes IGN] image Sentinel-MSI
[Termes IGN] modèle numérique de surface
[Termes IGN] Normalized Difference Water Index
[Termes IGN] ressources en eau
[Termes IGN] semis de points
[Termes IGN] surveillance hydrologique
[Termes IGN] système d'information géographiqueRésumé : (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 Affiliation des auteurs : non IGN 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
in Transactions in GIS > Vol 24 n° 1 (February 2020) . - pp 174 - 188[article]Mapping precipitable water vapor time series from Sentinel-1 interferometric SAR / Pedro Mateus in IEEE Transactions on geoscience and remote sensing, vol 58 n° 2 (February 2020)
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Titre : Mapping precipitable water vapor time series from Sentinel-1 interferometric SAR Type de document : Article/Communication Auteurs : Pedro Mateus, Auteur ; João Catalão, Auteur ; Giovanni Nico, Auteur ; Pedro Benevides, Auteur Année de publication : 2020 Article en page(s) : pp 1373 - 1379 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] Appalaches
[Termes IGN] cartographie
[Termes IGN] données GNSS
[Termes IGN] image Sentinel-SAR
[Termes IGN] interferométrie différentielle
[Termes IGN] itération
[Termes IGN] méthode des moindres carrés
[Termes IGN] modèle atmosphérique
[Termes IGN] optimisation (mathématiques)
[Termes IGN] phase GNSS
[Termes IGN] prévision météorologique
[Termes IGN] série temporelle
[Termes IGN] vapeur d'eauRésumé : (auteur) In this article, a methodology to retrieve the precipitable water vapor (PWV) from a differential interferometric time series is presented. We used external data provided by atmospheric weather models (e.g., ERA-Interim reanalysis) to constrain the initial state and by Global Navigation Satellite System (GNSS) to phase ambiguities elimination introduced by phase unwrapping algorithm. An iterative least-square is then used to solve the optimization problem. We applied the presented methodology to two time series of differential PWV maps estimated from synthetic aperture radar (SAR) images acquired by the Sentinel-1A, over the southwest part of the Appalachian Mountains (USA). The results were validated using an independent GNSS data set and also compared with atmospheric weather prediction data. The GNSS PWV observations show a strong correlation with the estimated PWV maps with a root-mean-square error less than 1 mm. These results are very encouraging, particularly for the meteorology community, providing crucial information to assimilate into numerical weather models and potentially improve the forecasts. Numéro de notice : A2020-098 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2946077 Date de publication en ligne : 28/10/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2946077 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94672
in IEEE Transactions on geoscience and remote sensing > vol 58 n° 2 (February 2020) . - pp 1373 - 1379[article]MODIS-based land surface temperature for climate variability and change research: the tale of a typical semi-arid to arid environment / Salahuddin M. Jaber in European journal of remote sensing, vol 53 n° 1 (2020)
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Titre : MODIS-based land surface temperature for climate variability and change research: the tale of a typical semi-arid to arid environment Type de document : Article/Communication Auteurs : Salahuddin M. Jaber, Auteur ; Mahmoud M. Abu-Allaban, Auteur Année de publication : 2020 Article en page(s) : pp 81 - 90 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] anthropisation
[Termes IGN] changement climatique
[Termes IGN] climat aride
[Termes IGN] image Aqua-MODIS
[Termes IGN] image Terra-MODIS
[Termes IGN] image thermique
[Termes IGN] Jordanie
[Termes IGN] MNS ASTER
[Termes IGN] nuit
[Termes IGN] régression linéaire
[Termes IGN] série temporelle
[Termes IGN] température au sol
[Termes IGN] variation diurne
[Termes IGN] zone semi-arideRésumé : (auteur) This study aims to (1) determine the seasonalities and spatial and temporal rates of change of MODIS-based daytime and nighttime land surface temperature (LST) for the last 19 years from 2000 to 2018 and (2) investigate whether these rates are induced by natural (represented by elevation) or anthropogenic (represented by population counts) forcing. The study area is Jordan – a typical Middle Eastern semi-arid to arid country. Time-series additive seasonal decomposition and simple linear regression produced the following results. (1) For both daytime and nighttime the highest LST values were observed in June while the lowest LST values were observed in December. (2) No significant linear rates of change of LST were noticed in daytime, while significant linear rates of increase of LST, which varied from 0.041°C/year to 0.119°C/year, were observed in nighttime in about one-third of the area of the country mainly in the western parts. (3) The significant linear rates of increase of nighttime LST increased significantly by 0.005°C/year for every 1,000 m increase in elevation and by 0.003°C/year for every 1,000 people increase in population counts. (4) Both natural and anthropogenic factors affected LST in nighttime; however, anthropogenic factors seemed to be more important than natural factors. Numéro de notice : A2020-166 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/22797254.2020.1735264 Date de publication en ligne : 06/03/2020 En ligne : https://doi.org/10.1080/22797254.2020.1735264 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94834
in European journal of remote sensing > vol 53 n° 1 (2020) . - pp 81 - 90[article]Multi-Spatial Resolution Satellite and sUAS Imagery for Precision Agriculture on Smallholder Farms in Malawi / Brad G. Peter in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 2 (February 2020)
PermalinkA novel fire index-based burned area change detection approach using Landsat-8 OLI data / Sicong Liu in European journal of remote sensing, vol 53 n° 1 (2020)
PermalinkPrediction of plant diversity in grasslands using Sentinel-1 and -2 satellite image time series / Mathieu Fauvel in Remote sensing of environment, Vol 237 (February 2020)
PermalinkRed-edge band vegetation indices for leaf area index estimation from Sentinel-2/MSI imagery / Yuanheng Sun in IEEE Transactions on geoscience and remote sensing, vol 58 n° 2 (February 2020)
PermalinkSome thoughts on measuring earthquake deformation using optical imagery / Min Huang in IEEE Transactions on geoscience and remote sensing, vol 58 n° 2 (February 2020)
PermalinkStatistical assessment of cartographic product from photogrammetry and fixed-wing UAV acquisition / Ademir Marques Junior in European journal of remote sensing, vol 53 n° 1 (2020)
PermalinkThe "Incense Road" from Petra to Gaza: an analysis using GIS and Cost functions / Motti Zohar in International journal of geographical information science IJGIS, vol 34 n° 2 (February 2020)
PermalinkThe potentiality of Sentinel-2 to assess the effect of fire events on Mediterranean mountain vegetation / Walter de Simone in Plant sociology, vol 57 n° 1 ([01/02/2020])
PermalinkTransferring deep learning models for cloud detection between Landsat-8 and Proba-V / Gonzalo Mateo-García in ISPRS Journal of photogrammetry and remote sensing, vol 160 (February 2020)
PermalinkUsing 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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