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Spatial biodiversity modeling using high-performance computing cluster: A case study to access biological richness in Indian landscape / Hariom Singh in Geocarto international, vol 36 n° 18 ([01/10/2021])  

Public [article]  inGeocarto international > vol 36 n° 18 [01/10/2021] . - pp 2023 - 2043 Titre : Spatial biodiversity modeling using high-performance computing cluster: A case study to access biological richness in Indian landscape Type de document : Article/Communication Auteurs : Hariom Singh, Auteur ; R.D. Garg, Auteur ; Harish Chandra Karnatak, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 2023 - 2043 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] autocorrélation spatiale [Termes IGN] biodiversité [Termes IGN] coefficient de corrélation [Termes IGN] distribution spatiale [Termes IGN] Inde [Termes IGN] processus de hiérarchisation analytique [Termes IGN] regroupement de données [Termes IGN] relevé phytosociologique [Termes IGN] SIG participatif Résumé : (auteur) The parallel processing and distributed GIServices provide an efficient approach to address the geocomputation challenges in biodiversity modeling. Using the widely applied Spatial Biodiversity Model (SBM) as an illustration, this study demonstrates parallelization of the spatial landscape algorithms based on Message Passing Interface (MPI) in cluster computing. The geocomputation based on MPI is performed to characterize the spatial distribution of Biological Richness (BR) for Indian landscape using developed high-performance cluster computing-based model named as SBM-HPC. In performance analysis, the execution time is reduced by 56.42%–81.41% (or the speedups of 2.29–5.38) using the parallel and cluster computing environment. Also, the spatial landscape algorithms of the model are extended to integrate large-scale geodata from online map services archives using distributed GIServices. To validate BR map, the phytosociological data is collected using participatory GIS approach. Furthermore, regression analysis between derived BR map and Shannon-Wiener index (Hˈ) represents high correlation coefficient R2 values. Highlights : - Development of spatial biodiversity model using parallel computing on the cluster. - Geocomputation of spatial landscape indices using large-scale geospatial datasets. - Distributed GIService integration in model to compute distributed data archives. - Prediction of biological richness pattern and validation using participatory GIS. - Characterize correlations between biological richness and bioclimatic patterns. Numéro de notice : A2021-763 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1678679 Date de publication en ligne : 21/10/2019 En ligne : https://doi.org/10.1080/10106049.2019.1678679 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98798 [article]

An automated and optimized approach for online spatial biodiversity model: a case study of OGC web processing service / Hariom Singh in Geocarto international, vol 34 n° 2 ([01/02/2019])  

Public [article]  inGeocarto international > vol 34 n° 2 [01/02/2019] . - pp 194 - 214 Titre : An automated and optimized approach for online spatial biodiversity model: a case study of OGC web processing service Type de document : Article/Communication Auteurs : Hariom Singh, Auteur ; Harish Chandra Karnatak, Auteur ; Rahul Dev Garg, Auteur Année de publication : 2019 Article en page(s) : pp 194 - 214 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] analyse de sensibilité [Termes IGN] biodiversité [Termes IGN] données localisées [Termes IGN] indicateur biologique [Termes IGN] indicateur de biodiversité [Termes IGN] interface web [Termes IGN] modèle conceptuel de données localisées [Termes IGN] processus de hiérarchisation analytique floue [Termes IGN] service web géographique [Termes IGN] SIG participatif [Termes IGN] traitement parallèle [Termes IGN] Uttarakhand (Inde ; état) [Termes IGN] Web Processing Service Résumé : (auteur) An online spatial biodiversity model (SBM) for optimized and automated spatial modelling and analysis of geospatial data is proposed, which is based on web processing service (WPS) and web service orchestration (WSO) in parallel computing environment. The developed model integrates distributed geospatial data in geoscientific processing workflow to compute the algorithms of spatial landscape indices over the web using free and open source software. A case study for Uttarakhand state of India demonstrates the model outputs such as spatial biodiversity disturbance index (SBDI) and spatial biological richness index (SBRI). In order to optimize and automate, an interactive web interface is developed using participatory GIS approaches for implementing fuzzy AHP. In addition, sensitivity analysis and geosimulation experiments are also performed under distributed GIS environment. Results suggest that parallel algorithms in SBM execute faster than sequential algorithms and validation of SBRI with biological diversity shows significant correlation by indicating high R2 values. Numéro de notice : A2019-222 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2017.1381178 Date de publication en ligne : 06/10/2017 En ligne : https://doi.org/10.1080/10106049.2017.1381178 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92742 [article]