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Identification of urban sectors prone to solid waste accumulation: A machine learning approach based on social indicators / Luis Izquierdo-Horna in Computers, Environment and Urban Systems, vol 96 (September 2022)  

Public [article]  inComputers, Environment and Urban Systems > vol 96 (September 2022) . - n° 101834 Titre : Identification of urban sectors prone to solid waste accumulation: A machine learning approach based on social indicators Type de document : Article/Communication Auteurs : Luis Izquierdo-Horna, Auteur ; Miker Damazo, Auteur ; Deyvis Yanayaco, Auteur Année de publication : 2022 Article en page(s) : n° 101834 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] apprentissage automatique [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] déchet [Termes IGN] densité de population [Termes IGN] données socio-économiques [Termes IGN] Pérou [Termes IGN] régression logistique [Termes IGN] zone urbaine Résumé : (auteur) In the last decades, the accumulation of municipal solid waste in urban areas has become a latent concern in our society due to its implications for the exposed population and the possible health and environmental issues it may cause. In this sense, this research study contributes to the timely identification of these sectors according to the anthropogenic characteristics of their residents as dictated by 10 social indicators (i.e., age, education, income, among others) sorted into three assessment categories (sociodemographic, sociocultural, and socioeconomic). Then, the data collected was processed and analyzed using two machine learning algorithms (random forest (RF) and logistic regression (LR)). The primary information that fed the machine learning model was collected through field visits and local/national reports. For this research, the Puente Piedra and Chaclacayo districts, both located in the province of Lima, Peru, were selected as case studies. Results suggest that the most relevant social indicators that help identifying these sectors are monthly income, consumption patterns, age, and household population density. The experiments showed that the RF algorithm has the best performance, since it efficiently identified 63% of the possible solid waste accumulation zones. In addition, both models were capable of determining different classes (AUC – RF = 0.65, AUC – LR = 0.71). Finally, the proposed approach is applicable and reproducible in different sectors of the national Peruvian territory. Numéro de notice : A2022-512 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2022.101834 Date de publication en ligne : 10/06/2022 En ligne : https://doi.org/10.1016/j.compenvurbsys.2022.101834 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101052 [article]

Mapping annual urban evolution process (2001–2018) at 250 m: A normalized multi-objective deep learning regression / Haoyu Wang in Remote sensing of environment, vol 278 (September 2022)  

Public [article]  inRemote sensing of environment > vol 278 (September 2022) . - n° 113088 Titre : Mapping annual urban evolution process (2001–2018) at 250 m: A normalized multi-objective deep learning regression Type de document : Article/Communication Auteurs : Haoyu Wang, Auteur ; Xiuyuan Zhang, Auteur ; Shihong Du, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 113088 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse des mélanges spectraux [Termes IGN] apprentissage profond [Termes IGN] carte d'occupation du sol [Termes IGN] cartographie thématique [Termes IGN] Chine [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] croissance urbaine [Termes IGN] image Terra-MODIS [Termes IGN] modèle de régression [Termes IGN] série temporelle [Termes IGN] surface cultivée Résumé : (auteur) Global urbanization changes land cover patterns and affects the living environment of humans. However, urbanization and its evolution process, i.e., conversions among diverse land covers, are hard to measure, as existing land cover maps usually have low temporal resolutions; conversely, long-term and temporally dense land cover maps, such as vegetation-impervious-soil decomposition maps base on MODIS, ignore the important land cover of cropland in urban evolution process (UEP). To resolve the issue, this study suggests a novel model named time-extended non-crop vegetation-impervious-cropland (Time V-I-C) to represent and quantify different stages of UEP; then, a normalized multi-objective T-ConvLSTM (NMT) method is proposed to unmix cropland, non-crop vegetation, and impervious based on the intra-annual remotely-sensed time series, and obtain their fractions in each pixel for generating UEP maps. Consequently, UEP maps from 2001 to 2018 are generated for two Chinese urban agglomerations, i.e., Beijing-Tianjin-Hebei and Yangtze River Delta urban agglomerations. The mapping results have high accuracies with a small standard error of regression (SER) of 13.1%, small root mean square error (RMSE) of 12.6%, and small mean absolute error (MAE) of 8.4%, and the maps reveal the different UEP in the two urban agglomerations. Therefore, this study provides a new idea for expressing UEP and contributes to a wide range of urbanization studies and sustainable city development. Numéro de notice : A2022-511 Affiliation des auteurs : non IGN Thématique : IMAGERIE/URBANISME Nature : Article DOI : 10.1016/j.rse.2022.113088 Date de publication en ligne : 25/05/2022 En ligne : https://doi.org/10.1016/j.rse.2022.113088 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101049 [article]

Experiencing virtual geographic environment in urban 3D participatory e-planning: A user perspective / Thibaud Chassin in Landscape and Urban Planning, vol 224 (August 2022)  

Public [article]  inLandscape and Urban Planning > vol 224 (August 2022) . - n° 104432 Titre : Experiencing virtual geographic environment in urban 3D participatory e-planning: A user perspective Type de document : Article/Communication Auteurs : Thibaud Chassin, Auteur ; Jens Ingensand, Auteur ; Sidonie Christophe , Auteur ; Guillaume Touya , Auteur Année de publication : 2022 Projets : 3-projet - voir note / Article en page(s) : n° 104432 Note générale : bibliographie This study was partly funded by the Computers & Geosciences Research Scholarships co-sponsored by Elsevier and the International Association for Mathematical Geosciences (IAMG). Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] approche participative [Termes IGN] cognition [Termes IGN] environnement géographique virtuel [Termes IGN] projet urbain [Termes IGN] urbanisme [Termes IGN] utilisateur [Termes IGN] visualisation 3D Résumé : (auteur) The adoption of technology in urban participatory planning with tools such as Virtual Geographic Environments (VGE) promises a broader engagement of urban dwellers, which should ultimately lead to the creation of better cities. However, the authorities and urban experts show hesitancy in endorsing these tools in their practices. Indeed, several parameters must be wisely considered in the design of VGE; if misjudged, their impact could be damaging for the participatory approach and the related urban project. The objective of this study is to engage participants (N = 107) with common tasks conducted in participatory sessions, in order to evaluate the users’ performance when manipulating a VGE. We aimed at assessing three crucial parameters: (1) the VGE representation, (2) the participants’ idiosyncrasies, and (3) the nature of the VGE format. The results demonstrate that the parameters did not affect the same aspect of users’ performance in terms of time, inputs, and correctness. The VGE representation impacts only the time needed to fulfill a task. The participants’ idiosyncrasies, namely age, gender and frequency of 3D use also induce an alteration in time, but spatial abilities seem to impact all characteristics of users’ performance, including correctness. Lastly, the nature of the VGE format significantly alters the time and correctness of users interactions. The results of this study highlight concerns about the inadequacies of the current VGE practices in participatory sessions. Moreover, we suggest guidelines to improve the design of VGE, which could enhance urban participatory planning processes, in order to create better cities. Numéro de notice : A2022-439 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : GEOMATIQUE/INFORMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.landurbplan.2022.104432 Date de publication en ligne : 18/04/2022 En ligne : https://doi.org/10.1016/j.landurbplan.2022.104432 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100758 [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]

Smart city data science: Towards data-driven smart cities with open research issues / Iqbal H. Sarker in Internet of Things, vol 19 (August 2022)  

Public [article]  inInternet of Things > vol 19 (August 2022) . - n° 100528 Titre : Smart city data science: Towards data-driven smart cities with open research issues Type de document : Article/Communication Auteurs : Iqbal H. Sarker, Auteur Année de publication : 2022 Article en page(s) : n° 100528 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Intelligence artificielle [Termes IGN] apprentissage profond [Termes IGN] gestion urbaine [Termes IGN] internet des objets [Termes IGN] planification urbaine [Termes IGN] science des données [Termes IGN] sécurité [Termes IGN] télédétection [Termes IGN] ville intelligente Résumé : (auteur) Cities are undergoing huge shifts in technology and operations in recent days, and ‘data science’ is driving the change in the current age of the Fourth Industrial Revolution (Industry 4.0 or 4IR). Extracting useful knowledge or actionable insights from city data and building a corresponding data-driven model is the key to making a city system automated and intelligent. Data science is typically the scientific study and analysis of actual happenings with historical data using a variety of scientific methodologies, machine learning techniques, processes, and systems. In this paper, we concentrate on and explore “Smart City Data Science”, where city data collected from various sources such as sensors, Internet-connected devices, or other external sources, is being mined for insights and hidden correlations to enhance decision-making processes and deliver better and more intelligent services to citizens. To achieve this goal, artificial intelligence, particularly, machine learning analytical modeling can be employed to provide deeper knowledge about city data, which makes the computing process more actionable and intelligent in various real-world city services. Finally, we identify and highlight ten open research issues for future development and research in the context of data-driven smart cities. Overall, we aim to provide an insight into smart city data science conceptualization on a broad scale, which can be used as a reference guide for the researchers, industry professionals, as well as policy-makers of a country, particularly, from the technological point of view. Numéro de notice : A2022-383 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE/SOCIETE NUMERIQUE Nature : Article DOI : 10.1016/j.iot.2022.100528 Date de publication en ligne : 20/04/2022 En ligne : https://doi.org/10.1016/j.iot.2022.100528 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100660 [article]

Estimating generalized measures of local neighbourhood context from multispectral satellite images using a convolutional neural network / Alex David Singleton in Computers, Environment and Urban Systems, vol 95 (July 2022)  

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A framework for urban land use classification by integrating the spatial context of points of interest and graph convolutional neural network method / Yongyang Xu in Computers, Environment and Urban Systems, vol 95 (July 2022)  

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GANmapper: geographical data translation / Abraham Noah Wu in International journal of geographical information science IJGIS, vol 36 n° 7 (juillet 2022)  

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Detecting spatiotemporal traffic events using geosocial media data / Shishuo Xu in Computers, Environment and Urban Systems, vol 94 (June 2022)  

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A geospatial workflow for the assessment of public transit system performance using near real-time data / Anastassios Dardas in Transactions in GIS, vol 26 n° 4 (June 2022)  

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Graph-based block-level urban change detection using Sentinel-2 time series / Nan Wang in Remote sensing of environment, vol 274 (June 2022)  

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Large-scale automatic identification of urban vacant land using semantic segmentation of high-resolution remote sensing images / Lingdong Mao in Landscape and Urban Planning, vol 222 (June 2022)  

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Multi-objective optimization of urban environmental system design using machine learning / Peiyuan Li in Computers, Environment and Urban Systems, vol 94 (June 2022)  

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Summarizing large scale 3D mesh for urban navigation / Imeen Ben Salah in Robotics and autonomous systems, vol 152 (June 2022)  

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The promising combination of a remote sensing approach and landscape connectivity modelling at a fine scale in urban planning / Elie Morin in Ecological indicators, vol 139 (June 2022)  

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