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The spatiotemporal implications of urbanization for urban heat islands in Beijing: A predictive approach based on CA–Markov modeling (2004–2050) / Muhammad Amir Siddique in Remote sensing, vol 13 n° 22 (November-2 2021)  

Public [article]  inRemote sensing > vol 13 n° 22 (November-2 2021) . - n° 4697 Titre : The spatiotemporal implications of urbanization for urban heat islands in Beijing: A predictive approach based on CA–Markov modeling (2004–2050) Type de document : Article/Communication Auteurs : Muhammad Amir Siddique, Auteur ; Yu Wang, Auteur ; Ninghan Xu, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 4697 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] automate cellulaire [Termes IGN] champ aléatoire de Markov [Termes IGN] changement d'occupation du sol [Termes IGN] changement d'utilisation du sol [Termes IGN] classification et arbre de régression [Termes IGN] coefficient de corrélation [Termes IGN] écosystème urbain [Termes IGN] flore urbaine [Termes IGN] ilot thermique urbain [Termes IGN] modèle de simulation [Termes IGN] Pékin (Chine) [Termes IGN] planification urbaine [Termes IGN] série temporelle [Termes IGN] température au sol [Termes IGN] urbanisation Résumé : (auteur) The rapid increase in infrastructural development in populated areas has had numerous adverse impacts. The rise in land surface temperature (LST) and its associated damage to urban ecological systems result from urban development. Understanding the current and future LST phenomenon and its relationship to landscape composition and land use/cover (LUC) changes is critical to developing policies to mitigate the disastrous impacts of urban heat islands (UHIs) on urban ecosystems. Using remote sensing and GIS data, this study assessed the multi-scale relationship of LUCC and LST of the cosmopolitan exponentially growing area of Beijing, China. We investigated the impacts of LUC on LST in urban agglomeration for a time series (2004–2019) of Landsat data using Classification and Regression Trees (CART) and a single channel algorithm (SCA), respectively. We built a CA–Markov model to forecast future (2025 and 2050) LUCC and LST spatial patterns. Our results indicate that the cumulative changes in an urban area (UA) increased by about 908.15 km2 (5%), and 11% of vegetation area (VA) decreased from 2004 to 2019. The correlation coefficient of LUCC including vegetation, water bodies, and built-up areas with LST had values of r = −0.155 (p > 0.419), −0.809 (p = 0.000), and 0.526 (p = 0.003), respectively. The results surrounding future forecasts revealed an estimated 2309.55 km2 (14%) decrease in vegetation (urban and forest), while an expansion of 1194.78 km2 (8%) was predicted for a built-up area from 2019 to 2050. This decrease in vegetation cover and expansion of settlements would likely cause a rise of about ~5.74 °C to ~9.66 °C in temperature. These findings strongly support the hypothesis that LST is directly related to the vegetation index. In conclusion, the estimated overall increase of 7.5 °C in LST was predicted from 2019–2050, which is alarming for the urban community’s environmental health. The present results provide insight into sustainable environmental development through effective urban planning of Beijing and other urban hotspots. Numéro de notice : A2021-860 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article DOI : 10.3390/rs13224697 Date de publication en ligne : 20/11/2021 En ligne : https://doi.org/10.3390/rs13224697 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99074 [article]

An extended patch-based cellular automaton to simulate horizontal and vertical urban growth under the shared socioeconomic pathways / Yimin Chen in Computers, Environment and Urban Systems, vol 91 (January 2022)  

Public [article]  inComputers, Environment and Urban Systems > vol 91 (January 2022) . - n° 101727 Titre : An extended patch-based cellular automaton to simulate horizontal and vertical urban growth under the shared socioeconomic pathways Type de document : Article/Communication Auteurs : Yimin Chen, Auteur Année de publication : 2021 Article en page(s) : n° 101727 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] automate cellulaire [Termes IGN] Canton (Kouangtoung) [Termes IGN] classification barycentrique [Termes IGN] classification par forêts aléatoires [Termes IGN] construction [Termes IGN] croissance urbaine [Termes IGN] données socio-économiques [Termes IGN] Kouangtoung (Chine) [Termes IGN] modèle de simulation [Termes IGN] urbanisation Résumé : (auteur) Most contemporary urban cellular automata (CA) models primarily focus on the simulation of urban land expansion, and cannot effectively simulate vertical urban growth. This study addresses this drawback by extending a patch-based urban CA model with a component that can predict the building volumes of an urban land expansion scenario. The proposed model is evaluated through a case study in the Guangzhou-Foshan metropolitan area, China. The horizontal urban growth simulations achieve a mean ‘Figure-of-merit’ value of 0.1406 at the cell level and an agreement of 97% at the pattern level. The building volume prediction made by the methods of random forest and k-nearest-neighbor has a testing R2 of 0.90 and a mean percentage absolute error of 22%. The proposed model is applied to the urban growth projections under the shared socioeconomic pathways (SSPs). The results successfully reflect the influences that different SSPs have on vertical urban developments. These results also complement related research of urbanization projections under the SSPs, because most existing studies consider the impacts of horizontal urban growth only. As building volumes and heights are fundamental parameters to urban climate modeling, the ability of the proposed model to project future change in vertical urban developments can support the mitigation of climate change effects on human settlements. Numéro de notice : A2022-008 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article DOI : 10.1016/j.compenvurbsys.2021.101727 Date de publication en ligne : 21/10/2021 En ligne : https://doi.org/10.1016/j.compenvurbsys.2021.101727 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99049 [article]

Assessment and prediction of urban growth for a mega-city using CA-Markov model / Veerendra Yadav in Geocarto international, Vol 36 n° 17 ([21/09/2021])  

Public [article]  inGeocarto international > Vol 36 n° 17 [21/09/2021] . - pp 1960 - 1992 Titre : Assessment and prediction of urban growth for a mega-city using CA-Markov model Type de document : Article/Communication Auteurs : Veerendra Yadav, Auteur ; Sanjay Kumar Ghosh, Auteur Année de publication : 2021 Article en page(s) : pp 1960 - 1992 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] automate cellulaire [Termes IGN] changement d'occupation du sol [Termes IGN] classification par maximum de vraisemblance [Termes IGN] coefficient de corrélation [Termes IGN] croissance urbaine [Termes IGN] mégalopole [Termes IGN] modèle de Markov [Termes IGN] modèle de simulation [Termes IGN] OpenStreetMap [Termes IGN] Tamil Nadu (Inde ; état) [Termes IGN] urbanisation Résumé : (auteur) Most of World’s mega-cities are facing high population growth. To accommodate the increased population, new built-up areas are emerging at the periphery or fringe area of cities. New urbanisation has an adverse impact on the existing Land Use Land Cover (LULC). To monitor and analyse the impact of urbanisation, LULC change analysis has become the primary concern for LULC monitoring agencies. In this study, LULC change of Chennai has been assessed during 1981–2011 using temporal Landsat data. All the dataset has been classified using Maximum Likelihood Classifier (MLC). Quantitative change in LULC has been carried out using Pearson’s Correlation Coefficient, Transition Potential Matrix, Land Use Dynamic Degree and MLC. Further, spatio-temporal change analysis has been performed using Post-classification comparison technique. Cellular Automata-Markov (CA-Markov) Model used for LULC prediction for 2021–2051. The urban area of Chennai has increased from 40.74 to 103.52 km2 during 1981–2011. Further, LULC prediction using the CA-Markov model shows that the urban area of Chennai district may increase from 103.52 to 140.79 km2 during 2011–2051. During the period 1981–2051, the prediction model indicates that mostly vegetation and barren land will be converted into urban land class. Numéro de notice : A2021-692 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/10106049.2019.1690054 Date de publication en ligne : 14/11/2019 En ligne : https://doi.org/10.1080/10106049.2019.1690054 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98507 [article]

Calibration of cellular automata urban growth models from urban genesis onwards - a novel application of Markov chain Monte Carlo approximate Bayesian computation / Jingyan Yu in Computers, Environment and Urban Systems, vol 90 (November 2021)  

Public [article]  inComputers, Environment and Urban Systems > vol 90 (November 2021) . - n° 101689 Titre : Calibration of cellular automata urban growth models from urban genesis onwards - a novel application of Markov chain Monte Carlo approximate Bayesian computation Type de document : Article/Communication Auteurs : Jingyan Yu, Auteur ; Alex Hagen-Zanker, Auteur ; Naratip Santitissadeekorn, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 101689 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse diachronique [Termes IGN] automate cellulaire [Termes IGN] changement d'utilisation du sol [Termes IGN] Corine Land Cover [Termes IGN] croissance urbaine [Termes IGN] estimation bayesienne [Termes IGN] Grande-Bretagne [Termes IGN] méthode de Monte-Carlo par chaînes de Markov [Termes IGN] modèle dynamique Résumé : (auteur) Cellular Automata (CA) models are widely used to study spatial dynamics of urban growth and evolving patterns of land use. One complication across CA approaches is the relatively short period of data available for calibration, providing sparse information on patterns of change and presenting problematic signal-to-noise ratios. To overcome the problem of short-term calibration, this study investigates a novel approach in which the model is calibrated based on the urban morphological patterns that emerge from a simulation starting from urban genesis, i.e., a land cover map completely void of urban land. The application of the model uses the calibrated parameters to simulate urban growth forward in time from a known urban configuration. This approach to calibration is embedded in a new framework for the calibration and validation of a Constrained Cellular Automata (CCA) model of urban growth. The investigated model uses just four parameters to reflect processes of spatial agglomeration and preservation of scarce non-urban land at multiple spatial scales and makes no use of ancillary layers such as zoning, accessibility, and physical suitability. As there are no anchor points that guide urban growth to specific locations, the parameter estimation uses a goodness-of-fit (GOF) measure that compares the built density distribution inspired by the literature on fractal urban form. The model calibration is a novel application of Markov Chain Monte Carlo Approximate Bayesian Computation (MCMC-ABC). This method provides an empirical distribution of parameter values that reflects model uncertainty. The validation uses multiple samples from the estimated parameters to quantify the propagation of model uncertainty to the validation measures. The framework is applied to two UK towns (Oxford and Swindon). The results, including cross-application of parameters, show that the models effectively capture the different urban growth patterns of both towns. For Oxford, the CCA correctly produces the pattern of scattered growth in the periphery, and for Swindon, the pattern of compact, concentric growth. The ability to identify different modes of growth has both a theoretical and practical significance. Existing land use patterns can be an important indicator of future trajectories. Planners can be provided with insight in alternative future trajectories, available decision space, and the cumulative effect of parcel-by-parcel planning decisions. Numéro de notice : A2021-616 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article DOI : 10.1016/j.compenvurbsys.2021.101689 Date de publication en ligne : 12/08/2021 En ligne : https://doi.org/10.1016/j.compenvurbsys.2021.101689 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98367 [article]

A cellular-automata model for assessing the sensitivity of the street network to natural terrain / Jeeno Soa George in Annals of GIS, vol 27 n° 3 (July 2021)  

Public [article]  inAnnals of GIS > vol 27 n° 3 (July 2021) . - pp 261 - 272 Titre : A cellular-automata model for assessing the sensitivity of the street network to natural terrain Type de document : Article/Communication Auteurs : Jeeno Soa George, Auteur ; Saikat Kumar Paul, Auteur ; Richa Dhawale, Auteur Année de publication : 2021 Article en page(s) : pp 261 - 272 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse de sensibilité [Termes IGN] automate cellulaire [Termes IGN] Caracas [Termes IGN] croissance urbaine [Termes IGN] données spatiotemporelles [Termes IGN] Inde [Termes IGN] Japon [Termes IGN] modélisation spatiale [Termes IGN] morphologie urbaine [Termes IGN] planification urbaine [Termes IGN] réalité de terrain [Termes IGN] réseau routier [Termes IGN] Singapour Résumé : (auteur) Natural and human-made features are not exclusive in settlements but interact across time and space, placing the context in constant evolution. The purpose of this paper is to search for the influence of terrain, a natural feature, on the configuration of the street network, a human-made feature, by analysing the results of two transition states of cellular automata used to model street networks. This work uses data from open-source projects and open-source applications. The first transition state models the street network considering the neighbourhood rules and randomness, assuming the natural terrain and street are exclusive. The second transition state models the street network as the product of characteristics of the terrain, neighbourhood rules, and randomness, thus assuming the natural terrain and street network interacting with one another. The model is run thirteen times for four different cities by varying the terrain characteristics and calibrated by comparing the simulated street maps with recent street maps. The results are compared and found that the CA model with the second transition state yields better simulation results than the first transition state. In one of the four cities studied, the first transition state results are similar to a specific state of the second transition state, indicating a weak inter-connectedness between the terrain and the street network in the mega-city. Further research can reveal whether the amount of inter-connectedness is specific to the city’s terrain or size. The recognition of the inter-connectedness of the road to terrain can help plan for resilient human settlements. Numéro de notice : A2021-628 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article DOI : 10.1080/19475683.2021.1936173 Date de publication en ligne : 03/06/2021 En ligne : https://doi.org/10.1080/19475683.2021.1936173 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98269 [article]

Cellular automata based land-use change simulation considering spatio-temporal influence heterogeneity of light rail transit construction: A case in Nanjing, China / Jiaming Na in ISPRS International journal of geo-information, vol 10 n° 5 (May 2021)  

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Integrating a forward feature selection algorithm, random forest, and cellular automata to extrapolate urban growth in the Tehran-Karaj region of Iran / Hossein Shafizadeh-Moghadam in Computers, Environment and Urban Systems, vol 87 (May 2021)  

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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])  

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Coupling fuzzy clustering and cellular automata based on local maxima of development potential to model urban emergence and expansion in economic development zones / Xun Liang in International journal of geographical information science IJGIS, vol 34 n° 10 (October 2020)  

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Applying multi-temporal Landsat satellite data and Markov-cellular automata to predict forest cover change and forest degradation of sundarban reserve forest, Bangladesh / Mohammad Emran Hasan in Forests, vol 11 n° 9 (September 2020)  

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Tourism land use simulation for regional tourism planning using POIs and cellular automata / Hong Shi in Transactions in GIS, Vol 24 n° 4 (August 2020)  

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Simulating urban land use change by integrating a convolutional neural network with vector-based cellular automata / Yaqian Zhai in International journal of geographical information science IJGIS, vol 34 n° 7 (July 2020)  

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A review of assessment methods for cellular automata models of land-use change and urban growth / Xiaohua Tong in International journal of geographical information science IJGIS, vol 34 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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