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Urban growth analysis and simulations using cellular automata and geo-informatics: comparison between Almaty and Astana in Kazakhstan / Aigerim Ilyassova in Geocarto international, vol 36 n° 5 ([15/03/2021])  

Public [article]  inGeocarto international > vol 36 n° 5 [15/03/2021] . - pp 520 - 539 Titre : Urban growth analysis and simulations using cellular automata and geo-informatics: comparison between Almaty and Astana in Kazakhstan Type de document : Article/Communication Auteurs : Aigerim Ilyassova, Auteur ; Lakshmi Kantakumar, Auteur ; Doreen S. Boyd, Auteur Année de publication : 2021 Article en page(s) : pp 520 - 539 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] automate cellulaire [Termes IGN] croissance urbaine [Termes IGN] dynamique spatiale [Termes IGN] étalement urbain [Termes IGN] image Landsat [Termes IGN] Kazakhstan [Termes IGN] modèle de simulation [Termes IGN] modélisation spatiale [Termes IGN] occupation du sol [Termes IGN] planification urbaine [Termes IGN] simulation spatiale [Termes IGN] système d'information géographique Résumé : (auteur) In this research, the SLEUTH urban growth model is calibrated and validated for the first time to post Soviet Union cities. The aim of the study is to monitor, assess, simulate and compare the spatiotemporal urban growth dynamics and spatial patterns of the two largest cities Almaty and Astana using free remote sensing data. The urban expansion metrics and SLEUTH model are used to assess the urban growth dynamics. Though the capital has been moved to Astana from Almaty in 1998, Almaty is still developing faster than Astana. The urban growth simulation results from SLEUTH show Astana will surpass the urban growth of Almaty to emerge as the largest city in Kazakhstan by 2030. Astana may experience more leapfrog and ribbon developments. In Almaty, the urban growth may likely to take place in north and north-west parts. Numéro de notice : A2021-251 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1618923 date de publication en ligne : 10/06/2019 En ligne : https://doi.org/10.1080/10106049.2019.1618923 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97273 [article]

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Geo-spatially modelling dengue epidemics in urban cities: a case study of Lahore, Pakistan / Muhammad Imran in Geocarto international, vol 36 n° 2 ([01/02/2021])  

Public [article]  inGeocarto international > vol 36 n° 2 [01/02/2021] . - pp 197 - 211 Titre : Geo-spatially modelling dengue epidemics in urban cities: a case study of Lahore, Pakistan Type de document : Article/Communication Auteurs : Muhammad Imran, Auteur ; Yasra Hamid, Auteur ; Abeer Mazher, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 197 - 211 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] cartographie des risques [Termes IGN] diptère [Termes IGN] image Landsat [Termes IGN] maladie tropicale [Termes IGN] modélisation spatiale [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] Pakistan [Termes IGN] régression géographiquement pondérée [Termes IGN] régression logistique [Termes IGN] risque sanitaire [Termes IGN] série temporelle [Termes IGN] zone intertropicale [Termes IGN] zone urbaine Résumé : (auteur) The study objective is to predict the epidemiological impact of dengue fever arbovirosis in urban tropical areas of Pakistan. To do so, we used the GPS-based data of the Aedes larvae collected during 2014–2015 in Lahore. We developed a Geographically Weighted Logistic Regression (GWLR) model for Geospatially predicting larvae presence or absence in Lahore. Data on rainfall, temperature are included along with time series of the normalized difference vegetation index (NDVI) derived from Landsat imagery. We observed a high spatial variability of the GWLR parameter estimates of these variables in the study area. The GWLR model significantly (R2a = 0.78) explained the presence or absence of Aedes larvae with temperature, rainfall and NDVI variables in South and Southeast of the study area. In the North and North-West, however, GWLR relationships were observed weak in highly populated areas. Interpolating GWLR coefficients generate more accurate maps of Aedes larvae presence or absence. Numéro de notice : A2021-474 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1614100 date de publication en ligne : 10/06/2020 En ligne : https://doi.org/10.1080/10106049.2019.1614100 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96932 [article]

Comparing the performance of turbulent kinetic energy and K-profile parameterization vertical parameterization schemes over the tropical indian ocean / Lokesh Kumar Pandey in Marine geodesy, vol 44 n° 1 (January 2021)  

Public [article]  inMarine geodesy > vol 44 n° 1 (January 2021) . - pp 42 - 69 Titre : Comparing the performance of turbulent kinetic energy and K-profile parameterization vertical parameterization schemes over the tropical indian ocean Type de document : Article/Communication Auteurs : Lokesh Kumar Pandey, Auteur ; Suneet Dwivedi, Auteur Année de publication : 2021 Article en page(s) : pp 42 - 69 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Océanographie [Termes IGN] Bengale, golfe du [Termes IGN] énergie cinétique [Termes IGN] Indien (océan) [Termes IGN] modélisation spatiale [Termes IGN] mousson [Termes IGN] salinité [Termes IGN] température de surface de la mer Résumé : (Auteur) The performance of vertical parameterization schemes, namely, turbulent kinetic energy (TKE) and K-profile parameterization (KPP), is evaluated over the domain [30E-120E; 20S-30N] in the Indian Ocean using the Nucleus for European Modeling of the Ocean (NEMO) regional model. The surface and sub-surface hydrography and mixed layer depth (MLD) of the simulations using TKE and KPP schemes have been compared. The KPP scheme produces higher bias (∼0.5 °C) of sea surface temperature (SST) in monsoon and post-monsoon seasons, which reduces on using the TKE scheme. The maximum surface salinity difference (0.45 psu) between TKE and KPP simulations is obtained over the head Bay of Bengal (BoB) in the post-monsoon months. The KPP scheme also overestimates MLD of the region. Barring highly convective regions as well as regions marked with very low and rapidly changing salinity, the TKE scheme performs better than KPP scheme in simulating the hydrography and MLD of the region. The differences between TKE and KPP simulations in the vertical stability and mixing are studied using buoyancy frequency, vertical shear of horizontal currents and energy required for mixing as quantifiers. The mixed layer heat budget analysis explains seasonal variability of SST and differences in vertical mixing parameterizations. Numéro de notice : A2021-059 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01490419.2020.1835758 date de publication en ligne : 29/10/2020 En ligne : https://doi.org/10.1080/01490419.2020.1835758 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96849 [article]

Modeling the risk of robbery in the city of Tshwane, South Africa / Nicolas Kemp in Cartography and Geographic Information Science, vol 48 n° 1 (January 2021)  

Public [article]  inCartography and Geographic Information Science > vol 48 n° 1 (January 2021) . - pp 29 - 42 Titre : Modeling the risk of robbery in the city of Tshwane, South Africa Type de document : Article/Communication Auteurs : Nicolas Kemp, Auteur ; Gregory D. Breetzke, Auteur ; Anthony Cooper, Auteur Année de publication : 2021 Article en page(s) : pp 29 - 42 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] Afrique du sud (état) [Termes IGN] criminalité [Termes IGN] modèle de simulation [Termes IGN] modélisation spatiale [Termes IGN] prévention des risques [Termes IGN] sécurité civile [Termes IGN] zone à risque Résumé : (auteur) In this study, we model the risk of robbery in the City of Tshwane in South Africa. We use the collective knowledge of two prominent spatial theories of crime (social disorganization theory, and crime pattern theory) to guide the selection of data and employ rudimentary geospatial techniques to create a crude model that identifies the risk of future robbery incidents in the city. The model is validated using actual robbery incidences recorded for the city. Overall the model performs reasonably well with approximately 70% of future robbery incidences accurately identified within a small subset of the overall model. Developing countries such as South Africa are in dire need of crime risk intensity models that are simple, and not data intensive to allocate scarce crime prevention resources in a more optimal fashion. It is anticipated that this model is a first step in this regard. Numéro de notice : A2021-017 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2020.1814872 date de publication en ligne : 10/09/2020 En ligne : https://doi.org/10.1080/15230406.2020.1814872 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96455 [article]

Semantic‐based urban growth prediction / Marvin Mc Cutchan in Transactions in GIS, Vol 24 n° 6 (December 2020)  

Public [article]  inTransactions in GIS > Vol 24 n° 6 (December 2020) . - 1482 - 1503 Titre : Semantic‐based urban growth prediction Type de document : Article/Communication Auteurs : Marvin Mc Cutchan, Auteur ; Simge Özdal‐Oktay, Auteur ; Ioannis Giannopoulos, Auteur Année de publication : 2020 Article en page(s) : 1482 - 1503 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] apprentissage profond [Termes IGN] croissance urbaine [Termes IGN] dynamique spatiale [Termes IGN] Europe (géographie politique) [Termes IGN] information sémantique [Termes IGN] modèle de simulation [Termes IGN] modélisation spatiale [Termes IGN] occupation du sol [Termes IGN] OpenStreetMap [Termes IGN] organisation spatiale [Termes IGN] OWL [Termes IGN] prévision [Termes IGN] réseau neuronal artificiel [Termes IGN] urbanisation [Termes IGN] ville durable Résumé : (Auteur) Urban growth is a spatial process which has a significant impact on the earth’s environment. Research on predicting this complex process makes it therefore especially fruitful for decision‐making on a global scale, as it enables the introduction of more sustainable urban development. This article presents a novel method of urban growth prediction. The method utilizes geospatial semantics in order to predict urban growth for a set of random areas in Europe. For this purpose, a feature space representing geospatial configurations was introduced which embeds semantic information. Data in this feature space was then used to perform deep learning, which ultimately enables the prediction of urban growth with high accuracy. The final results reveal that geospatial semantics hold great potential for spatial prediction tasks. Numéro de notice : A2020-766 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12655 date de publication en ligne : 14/07/2020 En ligne : https://doi.org/10.1111/tgis.12655 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96657 [article]

An agent-based model of public space use / Kostas Cheliotis in Computers, Environment and Urban Systems, Vol 81 (May 2020)  

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Incorporating landscape character in cork oak forest expansion in Sardinia: constraint or opportunity? / I.N. Vogiatzakis in Forests, vol 11 n° 5 (May 2020)  

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Region level SAR image classification using deep features and spatial constraints / Anjun Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 163 (May 2020)  

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Using GIS for disease mapping and clustering in Jeddah, Saudi Arabia / Abdulkader Murad in ISPRS International journal of geo-information, vol 9 n° 5 (May 2020)  

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Comparison of spatial modelling approaches to simulate urban growth: a case study on Udaipur city, India / Biswajit Mondal in Geocarto international, vol 35 n° 4 ([15/03/2020])  

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Analysing performance of SLEUTH model calibration using brute force and genetic algorithm–based methods / Ankita Saxena in Geocarto international, vol 35 n° 3 ([01/03/2020])  

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Object‐oriented tracking of thematic and spatial behaviors of urban heat islands / Rui Zhu in Transactions in GIS, Vol 24 n° 1 (February 2020)  

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Composition of place: towards a compositional view of functional space / Emmanuel Papadakis in Cartography and Geographic Information Science, Vol 47 n° 1 (January 2020)  

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La modélisation en géographie / Denise Pumain (2020)

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Optimizing arbovirus surveillance using risk mapping and coverage modelling / Joni A. Downs in Annals of GIS, Vol 26 n° 1 (January 2020)  

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