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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)
[article]
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 : 2022 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 d'arbres décisionnels
[Termes IGN] construction
[Termes IGN] croissance urbaine
[Termes IGN] données socio-économiques
[Termes IGN] Kouangtoung (Chine)
[Termes IGN] modèle de simulation
[Termes IGN] urbanisationRésumé : (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
in Computers, Environment and Urban Systems > vol 91 (January 2022) . - n° 101727[article]Attributing pedestrian networks with semantic information based on multi-source spatial data / Xue Yang in International journal of geographical information science IJGIS, vol 36 n° 1 (January 2022)
[article]
Titre : Attributing pedestrian networks with semantic information based on multi-source spatial data Type de document : Article/Communication Auteurs : Xue Yang, Auteur ; Kathleen Stewart, Auteur ; Mengyuan Fang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 31 - 54 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] données localisées des bénévoles
[Termes IGN] données multisources
[Termes IGN] extraction de données
[Termes IGN] itinéraire piétionnier
[Termes IGN] navigation pédestre
[Termes IGN] ondelette
[Termes IGN] réseau routier
[Termes IGN] segmentation sémantique
[Termes IGN] utilisation du sol
[Termes IGN] Wuhan (Chine)Résumé : (auteur) The lack of associating pedestrian networks, i.e. the paths and roads used for non-vehicular travel, with information about semantic attribution is a major weakness for many applications, especially those supporting accurate pedestrian routing. Researchers have developed various algorithms to generate pedestrian walkways based on datasets, including high-resolution images, existing map databases, and GPS data; however, the semantic attribution of pedestrian walkways is often ignored. The objective of our study is to automatically extract semantic information including incline values and the different categories of pedestrian paths from multi-source spatial data, such as crowdsourced GPS tracking data, land use data, and motor vehicle road (MVR) networks. Incline values for each pedestrian path were derived from tracking data through elevation filtering using wavelet theory and a similarity-based map-matching method. To automatically categorize pedestrian paths into five classes including sidewalk, crosswalk, entrance walkway, indoor path, and greenway, we developed a hierarchical strategy of spatial analysis using land use data and MVR networks. The effectiveness of our proposed method is demonstrated using real datasets including GPS tracking data collected by volunteers, land use data acquired from OpenStreetMap, and MVR network data downloaded from Gaode Map. Numéro de notice : A2022-083 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2021.1902530 En ligne : https://doi.org/10.1080/13658816.2021.1902530 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99480
in International journal of geographical information science IJGIS > vol 36 n° 1 (January 2022) . - pp 31 - 54[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2022011 SL Revue Centre de documentation Revues en salle Disponible Combining a class-weighted algorithm and machine learning models in landslide susceptibility mapping: A case study of Wanzhou section of the Three Gorges Reservoir, China / Huijuan Zhang in Computers & geosciences, vol 158 (January 2022)
[article]
Titre : Combining a class-weighted algorithm and machine learning models in landslide susceptibility mapping: A case study of Wanzhou section of the Three Gorges Reservoir, China Type de document : Article/Communication Auteurs : Huijuan Zhang, Auteur ; Yingxu Song, Auteur ; Shiluo Xu, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 104966 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] aléa
[Termes IGN] apprentissage automatique
[Termes IGN] base de données localisées
[Termes IGN] cartographie des risques
[Termes IGN] Chine
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] effondrement de terrain
[Termes IGN] modèle de simulation
[Termes IGN] régression géographiquement pondérée
[Termes IGN] régression logistique
[Termes IGN] risque naturel
[Termes IGN] Trois Gorges, barrage desRésumé : (auteur) This study aims to investigate the application of a class-weighted algorithm combined with conventional machine learning model (logistic regression (LR)) and ensemble machine learning models (LightGBM and random forest (RF)) to the landslide susceptibility evaluation. Wanzhou section of the Three Gorges Reservoir area, China, frequently suffering numerous landslides, is chosen as an example. The class-weighted algorithm focuses on the class-imbalanced issue of landslide and non-landslide samples, and it can turn the class-imbalanced issue into a cost-sensitive machine learning by setting unequal weights for different classes, which contribute to improving the accuracy of landslide susceptibility evaluation. The landslide inventory database was produced by field investigation and remote sensing images derived from Google Earth. Of the 233 landslides in the inventory, 40% were used for validation, and the remaining 60% were used for training purposes. Twelve environmental parameters (elevation, slope, aspect, curvature, distance to river, NDVI, NDWI, rainfall, seismic intensity, land use, TRI, lithology) were treated as inputs of the models to produce a landslide susceptibility map (LSM). The AUC value, Balanced accuracy, and Geometric mean score were utilized to estimate the quality of models. The result shows that the weighted models (weighted logistic regression (WLR), weighted LightGBM (WLightGBM), weighted random forest (WRF) have higher AUC values, Balanced accuracy, and Geometric mean scores than those of unweighted methods, which demonstrates that the weighted models exhibit better than unweighted models, with the WRF model having the best performance. The landslide susceptibility map of the Wanzhou section displays that the high and very high landslide susceptibility zones are mainly distributed on both sides of the river. The insights from this research will be useful for ameliorating the landslide susceptibility mapping and the prevention and mitigation for the Wanzhou section. Numéro de notice : A2022-029 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.cageo.2021.104966Get rights and content Date de publication en ligne : 27/10/2021 En ligne : https://doi.org/10.1016/j.cageo.2021.104966Get rights and content Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99268
in Computers & geosciences > vol 158 (January 2022) . - n° 104966[article]A constraint-based approach for identifying the urban–rural fringe of polycentric cities using multi-sourced data / Jing Yang in International journal of geographical information science IJGIS, vol 36 n° 1 (January 2022)
[article]
Titre : A constraint-based approach for identifying the urban–rural fringe of polycentric cities using multi-sourced data Type de document : Article/Communication Auteurs : Jing Yang, Auteur ; Jingwen Dong, Auteur ; Yizhong Sun, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 114 - 136 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] délimitation de frontière
[Termes IGN] données multisources
[Termes IGN] entropie de Shannon
[Termes IGN] espace rural
[Termes IGN] estimation par noyau
[Termes IGN] Kiangsou (Chine)
[Termes IGN] programmation par contraintes
[Termes IGN] transformation en ondelettes
[Termes IGN] urbanisation
[Termes IGN] zonage (urbanisme)
[Termes IGN] zone rurale
[Termes IGN] zone urbaineRésumé : (auteur) Studies on urban–rural fringes, which represent regions facing various urbanization problems caused by rapid expansion, have steadily increased in recent years. However, problems persist in the quantitative delimitation of such regions. Based on the characteristics of abrupt urbanization-level changes in urban–rural fringe areas, we propose a constraint-based method in this study to detect the urban–rural fringes of cities with a spatial polycentric structure of ‘Main center–Subcenter’ based on data from multiple sources. We used the proposed approach to delimitate the fringe areas of Jiangyin and Zhangjiagang and identify their urban main center and subcenter pre-defined by their city master plans, towns, and rural hinterlands. Comparison of the identified results of different single urbanization indices, a single detection center, kernel density estimation, and a single constraint revealed that the patch density and Shannon’s diversity index of the proposed method were higher in urban–rural fringes and smaller in city centers and rural hinterlands. This suggests that the landscape of urban–rural fringes delimitated by the proposed method is more fragmented, diverse, and complicated, thereby performing better. This study is significant for future urban spatial analysis, planning, and management. Numéro de notice : A2022-045 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article DOI : 10.1080/13658816.2021.1876236 Date de publication en ligne : 05/02/2021 En ligne : https://doi.org/10.1080/13658816.2021.1876236 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99404
in International journal of geographical information science IJGIS > vol 36 n° 1 (January 2022) . - pp 114 - 136[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2022011 SL Revue Centre de documentation Revues en salle Disponible Cultivating historical heritage area vitality using urban morphology approach based on big data and machine learning / Jiayu Wu in Computers, Environment and Urban Systems, vol 91 (January 2022)
[article]
Titre : Cultivating historical heritage area vitality using urban morphology approach based on big data and machine learning Type de document : Article/Communication Auteurs : Jiayu Wu, Auteur ; Yutian Lu, Auteur ; Hei Gao, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 101716 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] apprentissage automatique
[Termes IGN] Chine
[Termes IGN] conservation du patrimoine
[Termes IGN] distribution spatiale
[Termes IGN] données massives
[Termes IGN] échantillonnage de données
[Termes IGN] Extreme Gradient Machine
[Termes IGN] morphologie urbaine
[Termes IGN] patrimoine culturel
[Termes IGN] planification urbaine
[Termes IGN] point d'intérêt
[Termes IGN] régularisation de Tychonoff
[Termes IGN] variation diurneRésumé : (auteur) The conservation of historical heritage can bring social benefits to cities by promoting community economic development and societal creativity. In the early stages of historical heritage conservation, the focus was on the museum-style concept for individual structures. At present, heritage area vitality is often adopted as a general conservation method to increase the vibrancy of such areas. However, it remains unclear whether urban morphological elements suitable for urban areas can be applied to heritage areas. This study uses ridge regression and LightGBM with multi-source big geospatial data to explore whether urban morphological elements that affect the vitality of heritage and urban areas are consistent or have different spatial distributions and daily variations. From a sample of 12 Chinese cities, our analysis shows the following results. First, factors affecting urban vitality differ from those influencing heritage areas. Second, factors influencing urban and heritage areas' vitality have diurnal variations and differ across cities. The overarching contribution of this study is to propose a quantitative and replicable framework for heritage adaptation, combining urban morphology and vitality measures derived from big geospatial data. This study also extends the understanding of forms of heritage areas and provides theoretical support for heritage conservation, urban construction, and economic development. Numéro de notice : A2022-007 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2021.101716 Date de publication en ligne : 30/09/2021 En ligne : https://doi.org/10.1016/j.compenvurbsys.2021.101716 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99048
in Computers, Environment and Urban Systems > vol 91 (January 2022) . - n° 101716[article]Detection and biomass estimation of phaeocystis globosa blooms off Southern China from UAV-based hyperspectral measurements / Xue Li in IEEE Transactions on geoscience and remote sensing, vol 60 n° 1 (January 2022)PermalinkHourly rainfall forecast model using supervised learning algorithm / Qingzhi Zhao in IEEE Transactions on geoscience and remote sensing, vol 60 n° 1 (January 2022)PermalinkImproving LSMA for impervious surface estimation in an urban area / Jin Wang in European journal of remote sensing, vol 55 n° 1 (2022)PermalinkImproving urban land cover mapping with the fusion of optical and SAR data based on feature selection strategy / Qing Ding in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 1 (January 2022)PermalinkIncorporation 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)PermalinkA prediction model for surface deformation caused by underground mining based on spatio-temporal associations / Min Ren in Geomatics, Natural Hazards and Risk, vol 13 (2022)PermalinkA rapid assessment method for earthquake-induced landslide casualties based on GIS and logistic regression model / Yuqian Dai in Geomatics, Natural Hazards and Risk, vol 13 (2022)PermalinkApplication of a hand-held LiDAR scanner for the urban cadastral detail survey in digitized cadastral area of Taiwan urban city / Shih-Hong Chio in Remote sensing, vol 13 n° 24 (December-2 2021)PermalinkMulti-model estimation of forest canopy closure by using red edge bands based on Sentinel-2 images / Yiying Hua in Forests, vol 12 n° 12 (December 2021)PermalinkOBIA-based extraction of artificial terrace damages in the Loess plateau of China from UAV photogrammetry / Xuan Fang in ISPRS International journal of geo-information, vol 10 n° 12 (December 2021)Permalink