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Simulating fire-safe cities using a machine learning-based algorithm for the complex urban forms of developing nations: a case of Mumbai India / Vaibhav Kumar in Geocarto international, vol 37 n° 4 ([15/02/2022])  

Public [article]  inGeocarto international > vol 37 n° 4 [15/02/2022] . - pp 1084 - 1099 Titre : Simulating fire-safe cities using a machine learning-based algorithm for the complex urban forms of developing nations: a case of Mumbai India Type de document : Article/Communication Auteurs : Vaibhav Kumar, Auteur ; Arnab Jana, Auteur ; Krithi Ramamritham, Auteur Année de publication : 2022 Article en page(s) : pp 1084 - 1099 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] apprentissage automatique [Termes IGN] bâtiment [Termes IGN] Bombay [Termes IGN] incendie [Termes IGN] modèle de régression [Termes IGN] planification urbaine [Termes IGN] prévention des risques [Termes IGN] régression linéaire [Termes IGN] zone urbaine Résumé : (auteur) The article addresses the void in developing analytical methods concerning to design urban configurations that could reduce fire risks, and, thus, could help in achieving sustainable goals. A novel algorithm is developed to generate alternative Urban Built Form (UBF) models that could be less susceptible to fire compared to the existing built-form. Fire susceptibility of a generated UBF is predicted using a developed linear regression model. The algorithm considers existing regulations to derive rules and develop scenarios that might be effective in building fire-resilient cities. The outcomes of the simulations showed a significant decrease in the fire susceptibility of the southern region of Mumbai city. Moreover, for a certain simulated scenario the predicted UBF could accommodate twice the current population while being less susceptible than the existing UBF. The proposed techniques and methods can act as a decision-making tool in taking pre-emptive planning measures to develop fire resilient cities. Numéro de notice : A2022-395 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2020.1756463 Date de publication en ligne : 28/04/2020 En ligne : https://doi.org/10.1080/10106049.2020.1756463 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100689 [article]

Urban expansion in the megacity since 1970s: a case study in Mumbai / Sisi Yu in Geocarto international, vol 36 n° 6 ([01/04/2021])  

Public [article]  inGeocarto international > vol 36 n° 6 [01/04/2021] . - pp 603 - 621 Titre : Urban expansion in the megacity since 1970s: a case study in Mumbai Type de document : Article/Communication Auteurs : Sisi Yu, Auteur ; ZengXiang Zhang, Auteur ; Fang Liu, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 603 - 621 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse spatio-temporelle [Termes IGN] Bombay [Termes IGN] cartographie urbaine [Termes IGN] croissance urbaine [Termes IGN] données spatiotemporelles [Termes IGN] dynamique spatiale [Termes IGN] image Landsat [Termes IGN] mégalopole [Termes IGN] paysage urbain Résumé : (Auteur) Understanding the process of urban expansion in megacities is considerably important. In this study, megacity Mumbai was selected as the study area. Based on the urban maps retrieved from Landsat images in 1973–2018, we mapped and quantified the detailed urban expansion process of Mumbai by adopting the expansion area and speed indices, centroid shift model, urban expansion type method, hot-zone identification method and landscape metrics. The results indicated that: (1) urban land remarkably expanded, and its centroid moved from the southwest to the northeast direction, mainly adopting the edge-expansion form. (2) Distinctly spatiotemporal heterogeneities existed in eight directions, faster in the north, northeast and east directions, whereas slower in the five other directions. (3) The number of hot-zones increased from two to three and moved outward in space from urban centroid. (4) The urban landscape of Mumbai showed the ‘diffusion, aggregation, re-diffusion’ pattern and presented differences in eight directions. Numéro de notice : A2021-290 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1622600 Date de publication en ligne : 01/07/2019 En ligne : https://doi.org/10.1080/10106049.2019.1622600 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97336 [article]

Urban slum detection using texture and spatial metrics derived from satellite imagery / Divyani Kohli in Journal of spatial science, vol 61 n° 2 (December 2016)  

Public [article]  inJournal of spatial science > vol 61 n° 2 (December 2016) . - pp 405 - 426 Titre : Urban slum detection using texture and spatial metrics derived from satellite imagery Type de document : Article/Communication Auteurs : Divyani Kohli, Auteur ; Robert Sliuzas, Auteur ; Alfred Stein, Auteur Année de publication : 2016 Article en page(s) : pp 405 - 426 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse d'image orientée objet [Termes IGN] détection du bâti [Termes IGN] image Quickbird [Termes IGN] Maharashtra (Inde ; état) [Termes IGN] ontologie [Termes IGN] spatial metrics [Termes IGN] texture d'image [Termes IGN] ville Résumé : (auteur) Slum detection from satellite imagery is challenging due to the variability in slum types and definitions. This research aimed at developing a method for slum detection based on the morphology of the built environment. The method consists of segmentation followed by hierarchical classification using object-oriented image analysis and integrating expert knowledge in the form of a local slum ontology. Results show that textural feature contrast derived from a grey-level co-occurrence matrix was useful for delineating segments of slum areas or parts thereof. Spatial metrics such as the size of segments and proportions of vegetation and built-up were used for slum detection. The percentage of agreement between the reference layer and slum classification was 60 percent. This is lower than the accuracy achieved for land cover classification (80.8 percent), due to large variations. We conclude that the method produces useful results and has potential for successful application in contexts with similar morphology. Numéro de notice : A2016--147 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/14498596.2016.1138247 Date de publication en ligne : 05/05/2016 En ligne : http://dx.doi.org/10.1080/14498596.2016.1138247 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86334 [article]

GIS based drainage morphometry and its influence on hydrology in parts of Western Ghats region, Maharashtra, India / Dipak R. Samal in Geocarto international, vol 30 n° 7 - 8 (August - September 2015)  

Public [article]  inGeocarto international > vol 30 n° 7 - 8 (August - September 2015) . - pp 755 - 778 Titre : GIS based drainage morphometry and its influence on hydrology in parts of Western Ghats region, Maharashtra, India Type de document : Article/Communication Auteurs : Dipak R. Samal, Auteur ; Shirish S. Gedam, Auteur ; R. Nagarajan, Auteur Année de publication : 2015 Article en page(s) : pp 755 - 778 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] analyse multicritère [Termes IGN] base de données thématiques [Termes IGN] bassin hydrographique [Termes IGN] carte topographique [Termes IGN] corrélation [Termes IGN] géomorphométrie [Termes IGN] Ghats occidentaux [Termes IGN] hydrographie de surface [Termes IGN] Inde [Termes IGN] intégration de données [Termes IGN] Maharashtra (Inde ; état) [Termes IGN] matrice [Termes IGN] MNS ASTER [Termes IGN] système d'information géographique Résumé : (Auteur) Various drainage morphometric parameters in the Upper Bhima river basin and its influence on hydrological processes (e.g. runoff, peak flow, time to peak, infiltration, overland flow, etc.) were discussed using geographical information system (GIS) and remote sensing techniques. Survey of India topographical maps and ASTER digital elevation model was incorporated for thematic database generation and morphometric parameter evaluation in GIS environment. The whole study basin was divided into 8 sub-basins so that the spatial variation of morphological parameters and its influence on hydrology could be analyzed. The interrelationship between morphometric variables were computed (p Numéro de notice : A2015-501 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2014.978903 Date de publication en ligne : 15/06/2015 En ligne : http://www.tandfonline.com/doi/full/10.1080/10106049.2014.978903 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77417 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
059-2015041	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Performance analysis of radial basis function networks and multi-layer perceptron networks in modeling urban change: a case study / Hossein Shafizadeh-Moghadam in International journal of geographical information science IJGIS, vol 29 n° 4 (April 2015)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 29 n° 4 (April 2015) . - pp 606 - 623 Titre : Performance analysis of radial basis function networks and multi-layer perceptron networks in modeling urban change: a case study Type de document : Article/Communication Auteurs : Hossein Shafizadeh-Moghadam, Auteur ; Julian Hagenauer, Auteur ; Manuchehr Farajzadeh, Auteur ; Marco Helbich, Auteur Année de publication : 2015 Article en page(s) : pp 606 - 623 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] apprentissage automatique [Termes IGN] Bombay [Termes IGN] croissance urbaine [Termes IGN] fonction de base radiale [Termes IGN] milieu urbain [Termes IGN] modèle de simulation [Termes IGN] Perceptron multicouche [Termes IGN] performance [Termes IGN] test de performance [Termes IGN] urbanisation Résumé : (Auteur) The majority of cities are rapidly growing. This makes the monitoring and modeling of urban change’s spatial patterns critical to urban planners, decision makers, and environment protection activists. Although a wide range of methods exists for modeling and simulating urban growth, machine learning (ML) techniques have received less attention despite their potential for producing highly accurate predictions of future urban extents. The aim of this study is to investigate two ML techniques, namely radial basis function network (RBFN) and multi-layer perceptron (MLP) networks, for modeling urban change. By predicting urban change for 2010, the models’ performance is evaluated by comparing results with a reference map and by using a set of pertinent statistical measures, such as average spatial distance deviation and figure of merit. The application of these techniques employs the case study area of Mumbai, India. The results show that both models, which were tested using the same explanatory variables, produced promising results in terms of predicting the size and extent of future urban areas. Although a close match between RBFN and MLP is observed, RBFN demonstrates higher spatial accuracy of prediction. Accordingly, RBFN was utilized to simulate urban change for 2020 and 2030. Overall, the study provides evidence that RBFN is a robust and efficient ML technique and can therefore be recommended for land use change modeling. Numéro de notice : A2015-589 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2014.993989 En ligne : http://www.tandfonline.com/doi/full/10.1080/13658816.2014.993989 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77875 [article]

Learning with transductive SVM for semisupervised pixel classification of remote sensing imagery / Ujjwal Maulik in ISPRS Journal of photogrammetry and remote sensing, vol 77 (March 2013)  

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Satellite image classification using genetically guided fuzzy clustering with spatial information / S. Bandyopadhyay in International Journal of Remote Sensing IJRS, vol 26 n° 3 (February 2005)  

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