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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)  

Public [article]  inSustainable Cities and Society > vol 83 (August 2022) . - n° 103933 Titre : Simulation of the potential impact of urban expansion on regional ecological corridors: A case study of Taiyuan, China Type de document : Article/Communication Auteurs : Wei Hou, Auteur ; Wen Zhou, Auteur ; Jingyang Li, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 103933 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] carte d'occupation du sol [Termes IGN] Chansi (Chine) [Termes IGN] corridor biologique [Termes IGN] croissance urbaine [Termes IGN] étalement urbain [Termes IGN] modèle de simulation [Termes IGN] modélisation spatiale [Termes IGN] trame verte et bleue Résumé : (auteur) Urbanization caused by intensive land-use change is the main driving force of environment degradation. The development and protection of ecological corridors to connect green natural features has been recognized as an effective means for improving the resilience of cities. It is especially important for the cities which are in the rapid urbanizing process. In this paper, we used high-resolution spatial data to extract the distribution of ecological corridors by using the Least Cost Path model for the city of Taiyuan, China. Then, a prediction of the urban area for the year 2035 was achieved by using the SLEUTH model. Finally, we analyzed the negative impact of urban expansion on the corridors under current urbanization trends. Our results show that the regional corridors are mostly distributed in the western mountainous area, connecting large natural areas. There are also three ecological corridors crossing the city from the east to west. According to our prediction, Taiyuan will mainly grow southward along the urban edge and road network. As a result, two ecological corridors in the central and southern parts of Taiyuan will be largely occupied, especially the corridors in Xiaodian district which account for 72.51% of the total occupied corridor area. To avoid further conflict, the urbanization intensity along the sides of the corridors should be restricted to maintain corridors of a certain width. Our research findings can provide urban planners insightful suggestions for conservation and restoration of ecological networks and assist in spatial planning. Numéro de notice : A2022-487 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article DOI : 10.1016/j.scs.2022.103933 Date de publication en ligne : 07/05/2022 En ligne : https://doi.org/10.1016/j.scs.2022.103933 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100952 [article]

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)  

Public [article]  inJournal of geodesy > vol 96 n° 7 (July 2022) . - n° 47 Titre : Fusion of GNSS and InSAR time series using the improved STRE model: applications to the San Francisco bay area and Southern California Type de document : Article/Communication Auteurs : Huineng Yan, Auteur ; Wujiao Dai, Auteur ; Lei Xie, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 47 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] Californie (Etats-Unis) [Termes IGN] déformation de la croute terrestre [Termes IGN] données GNSS [Termes IGN] faille géologique [Termes IGN] filtrage spatiotemporel [Termes IGN] fusion de données [Termes IGN] image radar moirée [Termes IGN] interféromètrie par radar à antenne synthétique [Termes IGN] modélisation spatiale [Termes IGN] rééchantillonnage [Termes IGN] série temporelle Résumé : (auteur) The spatio-temporal random effects (STRE) model is a classic dynamic filtering model, which can be used to fuse GNSS and InSAR deformation data. The STRE model uses a certain time span of high spatial resolution Interferometric Synthetic Aperture Radar (InSAR) time series data to establish a spatial model and then obtain a deformation result with high spatio-temporal resolution through the state transition equation recursively in time domain. Combined with the Kalman filter, the STRE model is continuously updated and modified in time domain to obtain higher accuracy result. However, it relies heavily on the prior information and personal experience to establish an accurate spatial model. To the authors' knowledge, there are no publications which use the STRE model with multiple sets of different deformation monitoring data to verify its applicability and reliability. Here, we propose an improved STRE model to automatically establish accurate spatial model to improve the STRE model, then apply it to the fusion of GNSS and InSAR deformation data in the San Francisco Bay Area covering approximately 6000 km2 and in Southern California covering approximately 100,000 km2. Our experimental results show that the improved STRE model can achieve good fusion effects in both study areas. For internal inspection, the average error RMS values in the two regions are 0.13 mm and 0.06 mm for InSAR and 2.4 and 2.8 mm for GNSS, respectively; for Jackknife cross-validation, the average error RMS values are 6.0 and 1.3 mm for InSAR and 4.3 and 4.8 mm for GNSS in the two regions, respectively. We find that the deformation rate calculated from the fusion results is highly consistent with the existing studies, the significant difference in the deformation rate on both sides of the major faults in the two regions can be clearly seen, and the area with abnormal deformation rate corresponds well to the actual situation. These results indicate that the improved STRE model can reduce the reliance on prior information and personal experience, realize the effective fusion of GNSS and InSAR deformation data in different regions, and also has the advantages of high accuracy and strong applicability. Numéro de notice : A2022-553 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT Nature : Article nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1007/s00190-022-01636-7 Date de publication en ligne : 05/07/2022 En ligne : https://doi.org/10.1007/s00190-022-01636-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101165 [article]

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)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 36 n° 5 (May 2022) . - pp 898 - 917 Titre : A cost-effective algorithm for calibrating multiscale geographically weighted regression models Type de document : Article/Communication Auteurs : Bo Wu, Auteur ; Jinbiao Yan, Auteur ; Hui Lin, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 898 - 917 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse multiéchelle [Termes IGN] grande échelle [Termes IGN] hétérogénéité spatiale [Termes IGN] jeu de données [Termes IGN] modélisation spatiale [Termes IGN] régression géographiquement pondérée Résumé : (auteur) The multiscale geographically weighted regression (MGWR) model is a useful extension of the geographically weighted regression (GWR) model. MGWR, however, is a kind of Nadaraya–Watson kernel smoother, which usually leads to inaccurate estimates for the regression function and suffers from the boundary effect. Moreover, the widely used calibration technique for the MGWR with a back-fitting estimator (MGWR-BF) is computationally demanding, preventing it from being applied to large-scale data. To overcome these problems, we proposed a local linear-fitting-based MGWR (MGWR-LL) by introducing a local spatially varying coefficient model in which coefficients of different variables could be characterised as linear functions of spatial coordinates with different degrees of smoothness. Then the model was calibrated with a two-step least-squared estimated algorithm. Both simulated and actual data were implemented to validate the performance of the proposed method. The results consistently showed that the MGWR-LL automatically corrected for the boundary effect and improved the accuracy in most cases, not only in the goodness-of-fit measure but also in reducing the bias of the coefficient estimates. Moreover, the MGWR-LL significantly outperformed the MGWR-BF in computational cost, especially for larger-scale data. These results demonstrated that the proposed method can be a useful tool for the MGWR calibration. Numéro de notice : A2022-342 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2021.1999457 Date de publication en ligne : 29/11/2021 En ligne : https://doi.org/10.1080/13658816.2021.1999457 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100516 [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)  

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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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Modelling spatial processes in quantitative human geography / A. Stewart Fotheringham in Annals of GIS, vol 28 n° 1 (January 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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A spatial model of cognitive distance in cities / Ed Manley in International journal of geographical information science IJGIS, vol 35 n° 11 (November 2021)  

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Geomorphological mapping and anthropogenic landform change in an urbanizing watershed using structure-from-motion photogrammetry and geospatial modeling techniques / Peter G. Chirico in Journal of maps, vol 17 n° 4 (October 2021)  

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Spatial structure system of land use along urban rail transit based on GIS spatial clustering / Yu Gao in European journal of remote sensing, vol 54 sup 2 (2021)  

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Pattern-based identification and mapping of landscape types using multi-thematic data / Jakub Nowosad in International journal of geographical information science IJGIS, vol 35 n° 8 (August 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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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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