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Analytic hierarchy process based spatial biodiversity impact assessment model of highway broadening in Sikkim Himalaya / Polash Banerjee in Geocarto international, vol 35 n° 5 ([01/04/2020])  

Public [article]  inGeocarto international > vol 35 n° 5 [01/04/2020] . - pp 470 - 493 Titre : Analytic hierarchy process based spatial biodiversity impact assessment model of highway broadening in Sikkim Himalaya Type de document : Article/Communication Auteurs : Polash Banerjee, Auteur ; Mrinal K. Ghose, Auteur ; Ratika Pradham, Auteur Année de publication : 2020 Article en page(s) : pp 470 - 493 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] analyse de sensibilité [Termes descripteurs IGN] autoroute [Termes descripteurs IGN] biodiversité [Termes descripteurs IGN] étude d'impact [Termes descripteurs IGN] Himalaya [Termes descripteurs IGN] montagne [Termes descripteurs IGN] parcelle forestière [Termes descripteurs IGN] processus d'analyse hiérarchisée [Termes descripteurs IGN] projet routier Résumé : (auteur) Spatial impacts of highway projects on biodiversity of North-Eastern Himalaya remains largely unexplored. Usually a number of ecological criteria are required in biodiversity impact assessment. However, a wide set of such criteria can be overwhelming for the decision-makers to assess the viability of such projects. SBIAM uses landscape metrics and experts’ opinion to create a single composite biodiversity value map. The weighted area loss under various project alternatives estimated from Biodiversity Value Map is compared to identify the most viable alternative. SBIAM uses AHP and curve fitting method in the biodiversity estimation. The study indicates that the highway broadening project in the study area will cause a moderate biodiversity loss. Sensitivity analysis of SBIAM indicates its robustness, and shows that forest patches near the highway are most sensitive to disturbances and patch proximity. SBIAM can be applied in varied spatial scales, terrains and development projects as a decision support tool. Numéro de notice : A2020-142 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1520924 date de publication en ligne : 22/10/2018 En ligne : https://doi.org/10.1080/10106049.2018.1520924 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94768 [article]

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]

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])  

Public [article]  inGeocarto international > vol 35 n° 2 [01/02/2020] . - pp 168 - 187 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 descripteurs IGN] apprentissage automatique [Termes descripteurs IGN] autoroute [Termes descripteurs IGN] classification dirigée [Termes descripteurs IGN] effondrement de terrain [Termes descripteurs IGN] entropie maximale [Termes descripteurs IGN] Himalaya [Termes descripteurs IGN] image IRS-LISS [Termes descripteurs IGN] image Landsat-8 [Termes descripteurs IGN] Linear Imaging Self-Scanning System [Termes descripteurs IGN] modèle statistique [Termes descripteurs IGN] mousson [Termes descripteurs IGN] Normalized Difference Vegetation Index [Termes descripteurs IGN] séparateur à vaste marge [Termes descripteurs IGN] test statistique Résumé : (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 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 [article]

Assessment of ArcGIS based extraction of geoidal undulation compared to National Geospatial Intelligence Agency (NGA) model – A case study / Sher Muhammad in Journal of applied geodesy, vol 14 n° 1 (January 2020)  

Public [article]  inJournal of applied geodesy > vol 14 n° 1 (January 2020) . - pp 77 - 81 Titre : Assessment of ArcGIS based extraction of geoidal undulation compared to National Geospatial Intelligence Agency (NGA) model – A case study Type de document : Article/Communication Auteurs : Sher Muhammad, Auteur ; Lide Tian, Auteur Année de publication : 2020 Article en page(s) : pp 77 - 81 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique [Termes descripteurs IGN] altitude orthométrique [Termes descripteurs IGN] détection d'erreur [Termes descripteurs IGN] Earth Gravity Model 1996 [Termes descripteurs IGN] ellipsoïde (géodésie) [Termes descripteurs IGN] géoïde altimétrique [Termes descripteurs IGN] Himalaya [Termes descripteurs IGN] interpolation [Termes descripteurs IGN] Matlab [Termes descripteurs IGN] modèle numérique de surface [Termes descripteurs IGN] niveau moyen des mers [Termes descripteurs IGN] Tibet Résumé : (auteur) Global Navigation Satellite System (GNSS) and remote sensing Digital Elevation Models (DEMs) represent earth’s surface elevation with reference to ellipsoid and orthometric heights. Proper estimation of the geoid (difference of ellipsoid and orthometric heights) is necessary before comparing data referenced to the different vertical datum. In this paper, an error in estimating EGM96 orthometric height is highlighted, verified by NGA/NASA developed model and MATLAB®. A significant error was found in the ArcGIS derived EGM96 orthometric heights range between ±6.9 meters. In addition, interpolation of low-resolution geoid data also produces significant biases depending on geographic location and the number of the interpolation data point. The bias was maximum negative in the central part of Tibetan Plateau and Himalaya. Therefore, estimation of orthometric height similar to NGA/NASA model precision is necessary for comparison of DEMs for natural resources management, 3D modelling and glaciers mass balance mainly in the mountainous regions. Numéro de notice : A2020-041 Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1515/jag-2019-0030 En ligne : https://doi.org/10.1515/jag-2019-0030 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94512 [article]

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)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 58 n° 1 (January 2020) . - pp 691 - 703 Titre : Identification of alpine glaciers in the central Himalayas using fully polarimetric L-Band SAR data Type de document : Article/Communication Auteurs : Guo-Hui Yao, Auteur ; Chang-qing Ke, Auteur ; Xiaobing Zhou, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 691 - 703 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] analyse multiéchelle [Termes descripteurs IGN] bande L [Termes descripteurs IGN] classification orientée objet [Termes descripteurs IGN] classification par séparateurs à vaste marge [Termes descripteurs IGN] données polarimétriques [Termes descripteurs IGN] échantillonnage [Termes descripteurs IGN] glacier [Termes descripteurs IGN] Himalaya [Termes descripteurs IGN] image ALOS-PALSAR [Termes descripteurs IGN] image Landsat-OLI [Termes descripteurs IGN] image radar moirée [Termes descripteurs IGN] interferométrie différentielle [Termes descripteurs IGN] matrice de covariance [Termes descripteurs IGN] précision de la classification [Termes descripteurs IGN] segmentation Résumé : (auteur) To study the applicability of full polarimetric synthetic aperture radar (SAR) data to identify alpine glaciers in the central Himalayas, six polarimetric decomposition methods were used to obtain 20 polarimetric characteristic parameters based on the Advanced Land Observing Satellite 2 (ALOS-2) Phased Array type L-band SAR (PALSAR) data. Object-oriented multiscale segmentation was performed on a Landsat 8 Operational Land Imager (OLI) image prior to classification, and the vector boundaries of different types of training samples were selected from the segmented results. We performed a support vector machine (SVM)-based classification on the characteristic parameters from each polarimetric decomposition. All 20 parameters were then screened and combined according to different requirements: the degree of separability of different types of training samples and the type of scattering mechanisms. The results show that the classification accuracy of the incoherent decomposition characteristics based on the covariance matrix is the best, reaching 87%, and it can exceed 91% after adding the local incidence angle to the suite of classifiers. Eventually, more than 93% accuracy was achieved using a combination of multiple polarimetric parameters, which reduced the misclassification between bare ice and rock. We also analyzed the use of controlling factors on the accuracy of alpine glacier identification and found that the polarimetric information and aspect of the glacier surface are the most important factors. The former is the main basis for identification but the latter will confuse the feature distributions of different categories and cause misclassification. Numéro de notice : A2020-077 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2939430 date de publication en ligne : 25/09/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2939430 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94613 [article]

Classification of glacial lakes using integrated approach of DFPS technique and gradient analysis using Sentinel 2A data / Prateek Verma in Geocarto international, vol 34 n° 10 ([15/07/2019])  

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Identification and extraction of seasonal geodetic signals due to surface load variations / Stacy Larochelle in Journal of geophysical research : Solid Earth, vol 123 n° 12 (December 2018)  

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Multi-scale assessment of invasive plant species diversity using Pléiades 1A, RapidEye and Landsat-8 data / Siddhartha Khare in Geocarto international, vol 33 n° 7 (July 2018)  

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GIS-based MCDA–AHP modelling for avalanche susceptibility mapping of Nubra valley region, Indian Himalaya / Satish Kumar in Geocarto international, vol 32 n° 11 (November 2017)  

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Recent variations of supraglacial lakes on the Baltoro Glacier in the central Karakoram Himalaya and its possible teleconnections with the pacific decadal oscillation / Bijeesh Kozhikkodan Veettil in Geocarto international, vol 31 n° 1 - 2 (January - February 2016)  

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GPS and the 2015 Gorkha Earthquake / Mathias Lemmens in GIM international [en ligne], vol 29 n° 11 (November 2015)

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Accuracy assessment of MODIS/Terra snow cover product for parts of Indian Himalayas / Hari Prasad Chelamallu in Geocarto international, vol 29 n° 5 - 6 (August - October 2014)  

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Demarcation of potential avalanche sites using remote sensing and ground observations: a case study of Gangotri glacier / Snehmani A. Bhardwaj in Geocarto international, vol 29 n° 5 - 6 (August - October 2014)  

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Glacier changes using satellite data and effect of climate in Tirungkhad basin located in western Himalaya / Riyaz Ahmad Mir in Geocarto international, vol 29 n° 3 - 4 (June - July 2014)

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Application of frequency ratio and likelihood ratio model for geo-spatial modelling of landslide hazard vulnerability assessment and zonation: a case study from the Sikkim Himalayas in India / L.P. Sharma in Geocarto international, vol 29 n° 1 - 2 (February - April 2014)  

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