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Simulation of land use/land cover changes and urban expansion in Estonia by a hybrid ANN-CA-MCA model and utilizing spectral-textural indices / Najmeh Mozaffaree Pour in Environmental Monitoring and Assessment, vol 194 n° 9 (September 2022)  

Public [article]  inEnvironmental Monitoring and Assessment > vol 194 n° 9 (September 2022) . - n° 584 Titre : Simulation of land use/land cover changes and urban expansion in Estonia by a hybrid ANN-CA-MCA model and utilizing spectral-textural indices Type de document : Article/Communication Auteurs : Najmeh Mozaffaree Pour, Auteur ; Oleksandr Karasov, Auteur ; Iuliia Burdun, Auteur ; Tõnu Oja, Auteur Année de publication : 2022 Article en page(s) : n° 584 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] automate cellulaire [Termes IGN] chaîne de Markov [Termes IGN] croissance urbaine [Termes IGN] Estonie [Termes IGN] Google Earth Engine [Termes IGN] image Landsat-8 [Termes IGN] modèle de simulation [Termes IGN] occupation du sol [Termes IGN] réseau neuronal artificiel Résumé : (auteur) Over the recent two decades, land use/land cover (LULC) drastically changed in Estonia. Even though the population decreased by 11%, noticeable agricultural and forest land areas were turned into urban land. In this work, we analyzed those LULC changes by mapping the spatial characteristics of LULC and urban expansion in the years 2000–2019 in Estonia. Moreover, using the revealed spatiotemporal transitions of LULC, we simulated LULC and urban expansion for 2030. Landsat 5 and 8 data were used to estimate 147 spectral-textural indices in the Google Earth Engine cloud computing platform. After that, 19 selected indices were used to model LULC changes by applying the hybrid artificial neural network, cellular automata, and Markov chain analysis (ANN-CA-MCA). While determining spectral-textural indices is quite common for LULC classifications, utilization of these continues indices in LULC change detection and examining these indices at the landscape scale is still in infancy. This country-wide modeling approach provided the first comprehensive projection of future LULC utilizing spectral-textural indices. In this work, we utilized the hybrid ANN-CA-MCA model for predicting LULC in Estonia for 2030; we revealed that the predicted changes in LULC from 2019 to 2030 were similar to the observed changes from 2011 to 2019. The predicted change in the area of artificial surfaces was an increased rate of 1.33% to reach 787.04 km2 in total by 2030. Between 2019 and 2030, the other significant changes were the decrease of 34.57 km2 of forest lands and the increase of agricultural lands by 14.90 km2 and wetlands by 9.31 km2. These findings can develop a proper course of action for long-term spatial planning in Estonia. Therefore, a key policy priority should be to plan for the stable care of forest lands to maintain biodiversity. Numéro de notice : A2022-458 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE/URBANISME Nature : Article DOI : 10.1007/s10661-022-10266-7 Date de publication en ligne : 13/07/2022 En ligne : http://dx.doi.org/10.1007/s10661-022-10266-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101258 [article]

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)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 36 n° 5 (May 2022) . - pp 1037 - 1058 Titre : Impacts of spatiotemporal resolution and tiling on SLEUTH model calibration and forecasting for urban areas with unregulated growth patterns Type de document : Article/Communication Auteurs : Damilola Eyelade, Auteur ; Keith C. Clarke, Auteur ; Ighodalo Ijagbone, Auteur Année de publication : 2022 Article en page(s) : pp 1037 - 1058 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] dalle [Termes IGN] données spatiotemporelles [Termes IGN] méthode de Monte-Carlo [Termes IGN] modèle de simulation [Termes IGN] modélisation spatiale [Termes IGN] Nigéria [Termes IGN] OpenStreetMap Résumé : (auteur) The SLEUTH model provides a framework for understanding land use evolution around urban areas. Calibration of SLEUTH’s behavioral coefficients can be impacted by scale and nonlinear transitions due to the SLEUTH land use deltatron module’s assumption of linear Markov change probabilities. This study attempted to establish what spatial resolution and temporal scale produces the most accurate forecasts given the linear change assumption. The impact of tiling the input data was also examined. To determine these, SLEUTH was calibrated at four spatial and three temporal scales for Ibadan, Nigeria using both untiled and tiled data. Calibration results were evaluated using accuracy metrics including Figure of Merit (FOM) and mean uncertainty. The best mix of calibration metrics (FOM 0.26) and mean uncertainty (11.64) was achieved at 30 m resolution and an intermediate temporal interval. Tiling input data led to overfitting, allowing good model fit within individual tiles but a reduction in trend recognition across land use types. Subsequently, a 2040 projection that is as accurate as possible, and scientifically justifiable given the available data, was produced. The findings provide a framework for understanding the effect of spatiotemporal scale on SLEUTH inputs that require tiling particularly for urban areas in the global south. Numéro de notice : A2022-347 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2021.2011292 Date de publication en ligne : 16/12/2021 En ligne : https://doi.org/10.1080/13658816.2021.2011292 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100531 [article]

Simulating future LUCC by coupling climate change and human effects based on multi-phase remote sensing data / Zihao Huang in Remote sensing, vol 14 n° 7 (April-1 2022)  

Public [article]  inRemote sensing > vol 14 n° 7 (April-1 2022) . - n° 1698 Titre : Simulating future LUCC by coupling climate change and human effects based on multi-phase remote sensing data Type de document : Article/Communication Auteurs : Zihao Huang, Auteur ; Xuejian Li, Auteur ; Qiang Du, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 1698 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] apprentissage automatique [Termes IGN] automate cellulaire [Termes IGN] changement climatique [Termes IGN] changement d'utilisation du sol [Termes IGN] Chine [Termes IGN] écosystème forestier [Termes IGN] forêt tropicale [Termes IGN] image Landsat-OLI [Termes IGN] image Landsat-TM [Termes IGN] interaction homme-milieu [Termes IGN] modèle de simulation [Termes IGN] modèle dynamique [Termes IGN] modèle numérique de surface [Termes IGN] puits de carbone [Termes IGN] simulation spatiale Résumé : (auteur) Future land use and cover change (LUCC) simulations play an important role in providing fundamental data to reveal the carbon cycle response of forest ecosystems to LUCC. Subtropical forests have great potential for carbon sequestration, yet their future dynamics under natural and human influences are unclear. Zhejiang Province in China is an important distribution area for subtropical forests. For forest management, it is of great significance to explore the future dynamic changes of subtropical forests in Zhejiang. As a popular LUCC spatial simulation model, the cellular automata (CA) model coupled with machine learning and LUCC quantitative demand models such as system dynamics (SD) can achieve effective LUCC simulation. Therefore, we first integrated a back propagation neural network (BPNN), a CA, and a SD model as a BPNN_CA_SD (BCS) coupled model for future LUCC simulation and then designed a slow development scenario (SD_Scenario), a harmonious development scenario (HD_Scenario), a baseline development scenario (BD_Scenario), and a fast development scenario (FD_Scenario), combining climate change and human disturbance. Thirdly, we obtained future land-use patterns in Zhejiang Province from 2014 to 2084 under multiple scenarios, and finally, we analyzed the temporal and spatial changes of land use and discussed the subtropical forest dynamics of the future. The results showed the following: (1) The overall accuracy was approximately 0.8, the kappa coefficient was 0.75, and the figure of merit (FOM) value was over 28% when using the BCS model to predict LUCC, indicating that the model could predict the consistent change of LUCC accurately. (2) The future evolution of the LUCC under different scenarios varied, with the growth of bamboo forests and the decline of coniferous forests in the FD_Scenario being prominent among the forest dynamics changes. Compared with 2014, the bamboo forest in 2084 will increase by 37%, while the coniferous forest will decrease by 25%. (3) Comparing the area and spatial change of the subtropical forests, the SD_Scenario was found to be beneficial for the forest ecology. These results can provide an important decision-making reference for land-use planning and sustainable forest development in Zhejiang Province. Numéro de notice : A2022-281 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/rs14071698 Date de publication en ligne : 31/03/2022 En ligne : https://doi.org/10.3390/rs14071698 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100297 [article]

Unravelling the dynamics behind the urban morphology of port-cities using a LUTI model based on cellular automata / Aditya Tafta Nugraha in Computers, Environment and Urban Systems, vol 92 (March 2022)  

Public [article]  inComputers, Environment and Urban Systems > vol 92 (March 2022) Titre : Unravelling the dynamics behind the urban morphology of port-cities using a LUTI model based on cellular automata Type de document : Article/Communication Auteurs : Aditya Tafta Nugraha, Auteur ; Ben J. Waterson, Auteur ; Simon P. Blainey, Auteur ; et al., Auteur Année de publication : 2022 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] automate cellulaire [Termes IGN] dynamique spatiale [Termes IGN] Grande-Bretagne [Termes IGN] interaction spatiale [Termes IGN] modèle orienté agent [Termes IGN] morphologie urbaine [Termes IGN] planification urbaine [Termes IGN] port [Termes IGN] transport urbain [Termes IGN] utilisation du sol Résumé : (auteur) The urban morphology is characterised by self-organisation where interactions of multiple agents produce emerging patterns on the urban form. Port-urban relationship added to the complexity of port cities' urban form. Most urban cellular automata (CA) models simulate land-use evolution through transition rules representing multi-factored local interactions. However, calibration of CA-based urban land use and transport interaction (LUTI) models often utilise manual methods due to complexity of the process. This limits insights on urban interactions to a few explored settlements and prevents applications for planning and assessment of transport policies in other contexts. This paper, therefore, addresses three main points. The paper (i) demonstrates an improved method for the calibration of CA-based LUTI models, (ii) contributes to a better understanding of the urban dynamics in port city systems by quantifying generalizable interactions from a wide range of port-urban settlements, and (iii) illustrates how the use of these interactions in a simulation model can allow long-term impact predictions of planning interventions. These were done by formulating a model in a similar structure as a neural network model to enable automatic calibration using an application of the gradient-descent algorithm. The model was then used to quantify the dynamics between land-use, geographic, and transport factors in 46 port-based and 10 non-port settlements across Great Britain, thus enabling cross-sectional analysis. Cluster analysis of the calibrated interactions in the study areas was conducted to examine the variations of these interactions. This produced two main groups. In the first group, consisting larger settlements, connections between ports and other urban activities were weaker than in the second group which consisted of smaller port-settlements. Overall, the findings of the research are consistent with existing evidence in the port-cities literature but go further in quantifying the interaction between urban agents within port-urban systems of various sizes and types. These quantified interactions will enable planners to better predict the longer-term consequences of their interventions. Numéro de notice : A2022-084 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article DOI : 10.1016/j.compenvurbsys.2021.101733 Date de publication en ligne : 25/11/2021 En ligne : https://doi.org/10.1016/j.compenvurbsys.2021.101733 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99489 [article]

Simulation of future forest and land use/cover changes (2019–2039) using the cellular automata-Markov model / Hasan Aksoy in Geocarto international, vol 37 n° 4 ([15/02/2022])  

Public [article]  inGeocarto international > vol 37 n° 4 [15/02/2022] . - pp 1183 - 1202 Titre : Simulation of future forest and land use/cover changes (2019–2039) using the cellular automata-Markov model Type de document : Article/Communication Auteurs : Hasan Aksoy, Auteur ; Sinan Kaptan, Auteur Année de publication : 2022 Article en page(s) : pp 1183 - 1202 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse diachronique [Termes IGN] automate cellulaire [Termes IGN] classification dirigée [Termes IGN] détection de changement [Termes IGN] gestion forestière [Termes IGN] image Landsat-8 [Termes IGN] image Landsat-TM [Termes IGN] modèle de Markov [Termes IGN] occupation du sol [Termes IGN] surface cultivée [Termes IGN] surface forestière [Termes IGN] Turquie [Termes IGN] utilisation du sol Résumé : (auteur) This study aimed to simulate and assess forest cover and land use/land cover (LULC) changes between 2019 and 2039 using the cellular automata-Markov model. The performance of the model was evaluated by comparing the 2019 simulation map with the 2019 supervised classified map, and it was found to be reliable, with a similarity rate of 85.43%. The LULC analysis and estimates were carried out for a total of six classes: coniferous, broad-leaf, mixed forest, settlement, water and agriculture. Between 1999 and 2019, the areas of total forest increased by 17.4%, settlement by 84.6% and water by 20.1%, whereas the agriculture area decreased by 33.2%. According to 2019‒2039 land use/cover simulation results, there were decreases of 2.4% in total forest area and 3.7% in residential and water surface areas, but a 6.9% decrease in the agriculture class. Tracking these changes will contribute to decision making and strategy development efforts of forest planners and managers. Numéro de notice : A2022-397 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2020.1778102 Date de publication en ligne : 22/06/2020 En ligne : https://doi.org/10.1080/10106049.2020.1778102 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100691 [article]

Exploring the advantages of the maximum entropy model in calibrating cellular automata for urban growth simulation: a comparative study of four methods / Bin Zhang in GIScience and remote sensing, vol 59 n° 1 (2022)  

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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)  

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Incorporation of spatial anisotropy in urban expansion modelling with cellular automata / Jinqu Zhang in International journal of geographical information science IJGIS, vol 36 n° 1 (January 2022)  

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Simulating multiple urban land use changes by integrating transportation accessibility and a vector-based cellular automata: a case study on city of Toronto / Xiaocong Xu in Geo-spatial Information Science, vol 25 n° inconnu ([01/01/2022])  

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There’s no best model! Addressing limitations of land-use scenario modelling through multi-model ensembles / Richard J. Hewitt in International journal of geographical information science IJGIS, vol 36 n° inconnu (2022)  

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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)  

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Assessment and prediction of urban growth for a mega-city using CA-Markov model / Veerendra Yadav in Geocarto international, vol 36 n° 17 ([15/09/2021])  

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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)  

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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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