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Evaluating future railway-induced urban growth of twelve cities using multiple SLEUTH models with open-source geospatial inputs / Alvin Christopher G. Varquez in Sustainable Cities and Society, vol 91 (April 2023)  

Public [article]  inSustainable Cities and Society > vol 91 (April 2023) . - n° 104442 Titre : Evaluating future railway-induced urban growth of twelve cities using multiple SLEUTH models with open-source geospatial inputs Type de document : Article/Communication Auteurs : Alvin Christopher G. Varquez, Auteur ; Sifan Dong, Auteur ; Shinya Hanaoka, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 104442 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] automate cellulaire [Termes IGN] changement d'utilisation du sol [Termes IGN] croissance urbaine [Termes IGN] gare [Termes IGN] modèle de simulation [Termes IGN] modélisation spatiale [Termes IGN] réseau ferroviaire [Termes IGN] système d'information géographique [Termes IGN] urbanisation Résumé : (auteur) Plausible urban growth projections aid in the understanding and treatment of multidisciplinary issues faced in society. In this work, we investigated the possible effects of train stations on urban growth by comparing urban projections from a cellular-automata-based land use change model, named SLEUTH, with versions (i.e. SLEUTsH and SLEUTsHGA introduced in this study) that can consider railway-induced urban growth and those (i.e. SLEUTH and SLEUTHGA) that do not. It was found that the influence of the railway stations on urban growth varied with time and according to each city. In general, railway stations induced urbanization in their immediate surroundings. However, edge growth, which is growth at the urban boundaries was slow in the first five years of the future prediction. As demonstrated by the higher urban growth rates simulated for the first few years in the SLEUTsH cases than the SLEUTH cases, the presence of railway stations will lead to more rapid urbanization in the 2040s. Mainly relying on publicly available GIS datasets, this work demonstrates the potential for modeling railway-induced urban growth on a global scale. The findings can be further confirmed with other cellular-automata models using a similar methodology. Numéro de notice : A2023-151 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.scs.2023.104442 Date de publication en ligne : 08/02/2023 En ligne : https://doi.org/10.1016/j.scs.2023.104442 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102824 [article]

Geospatial modelling of overlapping habitats for identification of tiger corridor networks in the Terai Arc landscape of India / Nupur Rautela in Geocarto international, vol 37 n° 27 ([20/12/2022])  

Public [article]  inGeocarto international > vol 37 n° 27 [20/12/2022] . - pp 15114 - 15142 Titre : Geospatial modelling of overlapping habitats for identification of tiger corridor networks in the Terai Arc landscape of India Type de document : Article/Communication Auteurs : Nupur Rautela, Auteur ; Saurabh Shanu, Auteur ; Alok Agarwal, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 15114 - 15142 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] chevauchement [Termes IGN] corridor biologique [Termes IGN] faune locale [Termes IGN] graphe [Termes IGN] habitat animal [Termes IGN] Inde [Termes IGN] modélisation spatiale [Termes IGN] système complexe Résumé : (auteur) Wildlife corridors in a landscape include local vegetation, topography, prey base, water and are associated with isolated wildlife habitat patches. They facilitate maintenance of ecological structure and function as well as provide connectivity to faunal populations supporting genetic transfers, and are elements critical to wildlife management. In this work, habitat patches for tiger, both inside as well as outside of Protected Areas have been identified by developing a Habitat Suitability Index model utilizing Remote Sensing and Geographical Information System datasets for the Terai Arc landscape, India. By using a computational approach based on the framework of theory of complex networks, for exclusively pairwise interactions between the habitat patches, a potential tiger corridor network has been structurally identified and studied in this landscape. The interactions between these habitat patches on a spatial scale has been analyzed as a clique of the corridor network. Further, the Clique Percolation Method has been applied to detect overlapping communities of habitat patches in the landscape. The Cliques required for maintaining contiguity between the habitat patches in order to support tiger movement are validated using field observations of tiger communities within the landscape matrix. The model developed for identification of tiger corridors in this study could potentially be of a vital importance for wildlife stakeholders to better understand and manage tiger populations both within and outside of protected areas. The study also highlights Critical Habitat Patches and their importance in maintaining landscape connectivity for tiger dispersal in the landscape. Using a report published by the Government of India as a benchmark, the model presented in the work is found to have an accuracy of 90.73% in predicting tiger carrying patches and the corridor network in the focal landscape. Numéro de notice : A2022-933 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2022.2095444 Date de publication en ligne : 14/07/2022 En ligne : https://doi.org/10.1080/10106049.2022.2095444 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102670 [article]

Hybrid XGboost model with various Bayesian hyperparameter optimization algorithms for flood hazard susceptibility modeling / Saeid Janizadeh in Geocarto international, vol 37 n° 25 ([01/12/2022])  

Public [article]  inGeocarto international > vol 37 n° 25 [01/12/2022] . - pp 8273 - 8292 Titre : Hybrid XGboost model with various Bayesian hyperparameter optimization algorithms for flood hazard susceptibility modeling Type de document : Article/Communication Auteurs : Saeid Janizadeh, Auteur Année de publication : 2022 Article en page(s) : pp 8273 - 8292 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] apprentissage automatique [Termes IGN] ArcGIS [Termes IGN] bassin hydrographique [Termes IGN] cartographie des risques [Termes IGN] classification par arbre de décision [Termes IGN] colinéarité [Termes IGN] estimation bayesienne [Termes IGN] Extreme Gradient Machine [Termes IGN] inondation [Termes IGN] modèle numérique de surface [Termes IGN] modélisation spatiale [Termes IGN] optimisation (mathématiques) [Termes IGN] Téhéran Résumé : (auteur) The purpose of this investigation is to develop an optimal model to flood susceptibility mapping in the Kan watershed, Tehran, Iran. Therefore, in this study, three Bayesian optimization hyper-parameter algorithms including Upper confidence bound (UCB), Probability of improvement (PI) and Expected improvement (EI) in order to Extreme Gradient Boosting (XGB) machine learning model optimization and Extreme randomize tree (ERT) model for modeling flood hazard were used. In order to perform flood susceptibility mapping, 118 historic flood locations were identified and analyzed using 17 geo-environmental explanatory variables to predict flooding susceptibility. Flood locations data were divided into 70% for training and 30% for testing of models developed. The receiver operating characteristic (ROC) curve parameters were used to evaluate the performance of the models. The evaluation results based on the criterion area under curve (AUC) in the testing stage showed that the ERT and XGB models have efficiencies of 91.37% and 91.95%, respectively. The evaluation of the efficiency of Bayesian hyperparameters optimization methods on the XGB model also showed that these methods increase the efficiency of the XGB model, so that the model efficiency using these methods EI-XGB, POI-XGB and UCB-XGB based on the AUC in the testing stage were 95.89%, 96.87% and 96.38%, respectively. The results of the relative importance of the five models shows that the variables of elevation and distance from the river are the significant compared to other variables in predicting flood hazard in the Kan watershed. Numéro de notice : A2022-931 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/10106049.2021.1996641 Date de publication en ligne : 29/10/2021 En ligne : https://doi.org/10.1080/10106049.2021.1996641 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102666 [article]

Updating and backdating analyses for mitigating uncertainties in land change modeling: a case study of the Ci Kapundung upper water catchment area, Java Island, Indonesia / Medria Shekar Rani in International journal of geographical information science IJGIS, vol 36 n° 12 (December 2022)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 36 n° 12 (December 2022) . - pp 2549 - 2562 Titre : Updating and backdating analyses for mitigating uncertainties in land change modeling: a case study of the Ci Kapundung upper water catchment area, Java Island, Indonesia Type de document : Article/Communication Auteurs : Medria Shekar Rani, Auteur ; Ross Cameron, Auteur ; Olaf Schrott, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 2549 - 2562 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] automate cellulaire [Termes IGN] bassin hydrographique [Termes IGN] carte thématique [Termes IGN] changement d'occupation du sol [Termes IGN] Java (île de) [Termes IGN] mise à jour [Termes IGN] modèle de Markov [Termes IGN] modélisation spatiale [Termes IGN] Perceptron multicouche Résumé : (auteur) In developing countries, data gaps are common and lead to uncertainties in land cover change analysis. This study demonstrates how to mitigate uncertainties in modeling land change in the Ci Kapundung upper water catchment area by comparing the outcomes of two simulation phases. A conventional cellular automata (CA)–Markov model was complemented with a multilayer perceptron (MLP) to project future land cover maps in the study area. The CA–Markov–MLP model results in high uncertainties in forested sites where a data gap is apparent in the input data (land cover maps and driver variables) and parameters. The results show that the model accuracy is improved from 47.90% in the first phase to 81.36% in the second phase. Both first and second phases integrate six demographic–economic and environmental drivers in the modeling, but the second phase also incorporates an updating and backdating analysis to revise the base-maps. This study suggests that uncertainties can be mitigated by linking such base-map revision process with the updating and backdating analyses using remote sensing datasets retrieved at different times. Numéro de notice : A2022-845 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2022.2103820 Date de publication en ligne : 28/07/2022 En ligne : https://doi.org/10.1080/13658816.2022.2103820 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102076 [article]

Driving factors of urban sprawl in the Romanian plain. Regional and temporal modelling using logistic regression / Ines Grigorescu in Geocarto international, vol 37 n° 24 ([20/10/2022])  

Public [article]  inGeocarto international > vol 37 n° 24 [20/10/2022] . - pp 7220 - 7246 Titre : Driving factors of urban sprawl in the Romanian plain. Regional and temporal modelling using logistic regression Type de document : Article/Communication Auteurs : Ines Grigorescu, Auteur ; Gheorghe Kucsicsa, Auteur ; Bianca Mitrică, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 7220 - 7246 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse de données [Termes IGN] analyse spatio-temporelle [Termes IGN] croissance urbaine [Termes IGN] étalement urbain [Termes IGN] image Landsat-ETM+ [Termes IGN] image Landsat-OLI [Termes IGN] image Landsat-TM [Termes IGN] modélisation spatiale [Termes IGN] régression logistique [Termes IGN] Roumanie [Termes IGN] zone urbaine Résumé : (auteur) The paper investigates built-up areas expansion after the 1990 in one of the highly urbanized regions of Romania - Romanian Plain, in order to explore the urban sprawl phenomena and its temporal and regional disparities in relation to some of the main distance driving factors. The research uses Landsat 4/5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper (ETM), and Landsat 8 Operational Land Imager (OLI) imagery to derive built-up areas and quantify their expansion over time in relation to fourteen distance explanatory factors: i.e. previous built-up areas, main road infrastructure, Bucharest city’s boundary, location of the urban centres classified according to demographic size and main economic function, forest land and water bodies. To estimate the influence of the predictors, the binary logistic regression was applied. Furthermore, to estimate the effectiveness of the predictor set in the variation of built-up areas expansion, the pseudo R2 was calculated and discussed. Moreover, to understand the future potential trend of urban sprawl and its spatial pattern, the probability maps were generated by integrating the regression coefficients of the statistically significant predictors into the spatial modeling. For the results performance assessment, the statistic Receiver Operating Characteristic and the pixel-based comparison between the real and predicted data were used. To assess possible differences at spatial and temporal scale, the analysis was carried out at regional level, for two periods: 1990–2002 and 2002–2018. In general, our findings show inverse relationship between the distance driving factors and built-up areas expansion, but the estimated predictive power suggests important disparities within the study area over the analysed periods. Overall, the statistical analysis indicate that the distance to previous build-up areas, distance to road infrastructure, distance to Bucharest and other large urban centres, and distance to urban centres with dominant industrial and service functions were more influential to urban sprawl after 1990. Furthermore, the predicted spatial data shows the highest potential of urban sprawl in the future around Bucharest, in the proximity of existing built-up areas and road infrastructure. Because of its predictive character, the present study is to be a useful tool for land managers and policy makers. Numéro de notice : A2022-777 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2021.1967465 Date de publication en ligne : 23/08/2021 En ligne : https://doi.org/10.1080/10106049.2021.1967465 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101832 [article]

Simulation of the potential impact of urban expansion on regional ecological corridors: A case study of Taiyuan, China / Wei Hou in Sustainable Cities and Society, vol 83 (August 2022)  

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Fusion of GNSS and InSAR time series using the improved STRE model: applications to the San Francisco bay area and Southern California / Huineng Yan in Journal of geodesy, vol 96 n° 7 (July 2022)  

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A cost-effective algorithm for calibrating multiscale geographically weighted regression models / Bo Wu in International journal of geographical information science IJGIS, vol 36 n° 5 (May 2022)  

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Impacts of spatiotemporal resolution and tiling on SLEUTH model calibration and forecasting for urban areas with unregulated growth patterns / Damilola Eyelade in International journal of geographical information science IJGIS, vol 36 n° 5 (May 2022)  

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Spatial modeling of migration using GIS-based multi-criteria decision analysis: A case study of Iran / Naeim Mijani in Transactions in GIS, vol 26 n° 2 (April 2022)  

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Assessment of the performance of GIS-based analytical hierarchical process (AHP) approach for flood modelling in Uttar Dinajpur district of West Bengal, India / Rajib Mitra in Geomatics, Natural Hazards and Risk, vol 13 (2022)  

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Explorer les processus de mobilité passée : raisonnement ontologique fondé sur la connaissance des pratiques socioculturelles et des vestiges archéologiques / Laure Nuninger in Revue internationale de géomatique, vol 31 n° 1-2 (janvier - juin 2022)  

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Modelling spatial processes in quantitative human geography / A. Stewart Fotheringham in Annals of GIS, vol 28 n° 1 (January 2022)  

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Télédétection et modélisation spatiale / Annelise Tran (2022)  

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A topology-based graph data model for indoor spatial-social networking / Mahdi Rahimi in International journal of geographical information science IJGIS, vol 35 n° 12 (December 2021)  

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