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GIS-based logic scoring of preference method for urban densification suitability analysis / Shuoge Shen in Computers, Environment and Urban Systems, vol 89 (September 2021)  

Public [article]  inComputers, Environment and Urban Systems > vol 89 (September 2021) . - n° 101654 Titre : GIS-based logic scoring of preference method for urban densification suitability analysis Type de document : Article/Communication Auteurs : Shuoge Shen, Auteur ; Suzana Dragićević, Auteur ; Jozo Dujmović, Auteur Année de publication : 2021 Article en page(s) : n° 101654 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] aide à la décision [Termes IGN] analyse multicritère [Termes IGN] croissance urbaine [Termes IGN] démographie [Termes IGN] densité de population [Termes IGN] planification urbaine [Termes IGN] système d'information géographique [Termes IGN] Vancouver (Colombie britannique) [Termes IGN] zone urbaine Résumé : (auteur) Urban Densification Suitability Analysis (UDSA) approach has been proposed using the GIS-based Logic Scoring of Preference (LSP) decision method. Our goal is to provide the methodology for the evaluation of suitability of locations for high density urban development to facilitate the spatial decision-making process and help justifiable urban planning. The main objectives of this research study are (1) to implement the GIS-based LSP method for high density urban growth suitability analysis, and (2) to perform an overall integrated suitability analysis for two key stakeholders, urban developer and urban planner. The LSP method is based on soft computing and used in the decision-making process to integrate large number of attribute criteria in a way that is consistent with human logic reasoning. The GIS-based LSP method is implemented using geospatial data for Metro Vancouver Region, Canada. Main criteria used to characterize the urban densification include recreation, transportation, existing development, economy, terrain, restrictions, and demography. The obtained results provide the distributions of suitability values and indicate that the opinions of two stakeholders differ. They select different locations as the most suitable for urban densifications and rather agree on the most unsuitable locations. The overall integrated suitability analysis has been performed with scenarios of possible decision-making outcomes between the two stakeholders. We introduce the concept of suitability agreement maps along with urban densification decision criteria. The analysis indicates that the GIS-based LSP method is a useful tool for measuring the similarities and differences in stakeholders' views and facilitating decision-making process for urban densification. Numéro de notice : A2021-534 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2021.101654 date de publication en ligne : 07/06/2021 En ligne : https://doi.org/10.1016/j.compenvurbsys.2021.101654 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97996 [article]

Identifying home locations in human mobility data: an open-source R package for comparison and reproducibility / Qingqing Chen in International journal of geographical information science IJGIS, vol 35 n° 7 (July 2021)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 7 (July 2021) . - pp 1425 - 1448 Titre : Identifying home locations in human mobility data: an open-source R package for comparison and reproducibility Type de document : Article/Communication Auteurs : Qingqing Chen, Auteur ; Ate Poorthuis, Auteur Année de publication : 2021 Article en page(s) : pp 1425 - 1448 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] contenu généré par les utilisateurs [Termes IGN] données issues des réseaux sociaux [Termes IGN] géopositionnement [Termes IGN] logement [Termes IGN] mobilité urbaine [Termes IGN] R (langage) [Termes IGN] service fondé sur la position [Termes IGN] Singapour Résumé : (auteur) Identifying meaningful locations, such as home or work, from human mobility data has become an increasingly common prerequisite for geographic research. Although location-based services (LBS) and other mobile technology have rapidly grown in recent years, it can be challenging to infer meaningful places from such data, which – compared to conventional datasets – can be devoid of context. Existing approaches are often developed ad-hoc and can lack transparency and reproducibility. To address this, we introduce an R package for inferring home locations from LBS data. The package implements pre-existing algorithms and provides building blocks to make writing algorithmic ‘recipes’ more convenient. We evaluate this approach by analyzing a de-identified LBS dataset from Singapore that aims to balance ethics and privacy with the research goal of identifying meaningful locations. We show that ensemble approaches, combining multiple algorithms, can be especially valuable in this regard as the resulting patterns of inferred home locations closely correlate with the distribution of residential population. We hope this package, and others like it, will contribute to an increase in use and sharing of comparable algorithms, research code and data. This will increase transparency and reproducibility in mobility analyses and further the ongoing discourse around ethical big data research. Numéro de notice : A2021-449 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2021.1887489 date de publication en ligne : 10/03/2021 En ligne : https://doi.org/10.1080/13658816.2021.1887489 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97861 [article]

Using information entropy and a multi-layer neural network with trajectory data to identify transportation modes / Qingying Yu in International journal of geographical information science IJGIS, vol 35 n° 7 (July 2021)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 7 (July 2021) . - pp 1346 - 1373 Titre : Using information entropy and a multi-layer neural network with trajectory data to identify transportation modes Type de document : Article/Communication Auteurs : Qingying Yu, Auteur ; Yonglong Luo, Auteur ; Dongxia Wang, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 1346 - 1373 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] classification par Perceptron multicouche [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] direction [Termes IGN] données spatiotemporelles [Termes IGN] entropie [Termes IGN] extraction de traits caractéristiques [Termes IGN] mobilité urbaine [Termes IGN] Pékin (Chine) [Termes IGN] plan de déplacement urbain [Termes IGN] segmentation [Termes IGN] trajectoire [Termes IGN] vitesse de déplacement Résumé : (auteur) Residents’ trajectory data denote their instantaneous locations along their movements. Mobility research that applies trajectory mining techniques to identify the transportation modes of these movements can inform urban transportation planning. Herein, we propose a five-step approach with information entropy and a multi-layer neural network to identify transportation modes from trajectory data. First, this approach extracts the motion features at each time-stamped location based on foundation geospatial data and spatiotemporal trajectory data, including the speed, acceleration, change of direction, rate of change in direction, and distance from each basic transportation facility. The second step uses information entropy to identify the features that play key roles in identifying transportation modes. The third step weighs each attribute in the feature vector consisting of the selected features and normalizes it to prepare it as input data. The fourth step constructs, trains, and tests a multi-layer neural network with seven-fold cross-validation. The final step includes a post-processing method to optimize the identification result. We use F-measure metric to evaluate the performance. Experimental results on a real trajectory dataset show that the proposed approach can identify the transportation mode at each time-stamped location and outperforms existing transportation-mode identification methods in terms of accuracy and stability. Numéro de notice : A2021-448 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2021.1901904 date de publication en ligne : 15/04/2021 En ligne : https://doi.org/10.1080/13658816.2021.1901904 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97860 [article]

Evaluation of light pollution in global protected areas from 1992 to 2018 / Haowei Mu in Remote sensing, vol 13 n° 9 (May 2021)  

Public [article]  inRemote sensing > vol 13 n° 9 (May 2021) . - n° 1849 Titre : Evaluation of light pollution in global protected areas from 1992 to 2018 Type de document : Article/Communication Auteurs : Haowei Mu, Auteur ; Xuecao Li, Auteur ; Xiaoping Du, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 1849 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] aire protégée [Termes IGN] biodiversité [Termes IGN] carte thématique [Termes IGN] distribution spatiale [Termes IGN] image DMSP-OLS [Termes IGN] image NPP-VIIRS [Termes IGN] nuit [Termes IGN] politique de conservation (biodiversité) [Termes IGN] pollution lumineuse [Termes IGN] série temporelle [Termes IGN] urbanisation Résumé : (auteur) Light pollution, a phenomenon in which artificial nighttime light (NTL) changes the form of brightness and darkness in natural areas such as protected areas (PAs), has become a global concern due to its threat to global biodiversity. With ongoing global urbanization and climate change, the light pollution status in global PAs deserves attention for mitigation and adaptation. In this study, we developed a framework to evaluate the light pollution status in global PAs, using the global NTL time series data. First, we classified global PAs (30,624) into three pollution categories: non-polluted (5974), continuously polluted (8141), and discontinuously polluted (16,509), according to the time of occurrence of lit pixels in/around PAs from 1992 to 2018. Then, we explored the NTL intensity (e.g., digital numbers) and its trend in those polluted PAs and identified those hotspots of PAs at the global scale with consideration of global urbanization. Our study shows that global light pollution is mainly distributed within the range of 30°N and 60°N, including Europe, north America, and East Asia. Although the temporal trend of NTL intensity in global PAs is increasing, Japan and the United States of America (USA) have opposite trends due to the implementation of well-planned ecological conservation policies and declining population growth. For most polluted PAs, the lit pixels are close to their boundaries (i.e., less than 10 km), and the NTL in/around these lit areas has become stronger over the past decades. The identified hotspots of PAs (e.g., Europe, the USA, and East Asia) help support decisions on global biodiversity conservation, particularly with global urbanization and climate change. Numéro de notice : A2021-407 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.3390/rs13091849 date de publication en ligne : 09/05/2021 En ligne : https://doi.org/10.3390/rs13091849 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97723 [article]

Understanding collective human movement dynamics during large-scale events using big geosocial data analytics / Junchuan Fan in Computers, Environment and Urban Systems, vol 87 (May 2021)  

Public [article]  inComputers, Environment and Urban Systems > vol 87 (May 2021) . - n° 101605 Titre : Understanding collective human movement dynamics during large-scale events using big geosocial data analytics Type de document : Article/Communication Auteurs : Junchuan Fan, Auteur ; Kathleen Stewart, Auteur Année de publication : 2021 Article en page(s) : n° 101605 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] collecte de données [Termes IGN] données GPS [Termes IGN] données issues des réseaux sociaux [Termes IGN] données localisées des bénévoles [Termes IGN] données massives [Termes IGN] dynamique spatiale [Termes IGN] échantillonnage de données [Termes IGN] éclipse solaire [Termes IGN] estimation par noyau [Termes IGN] Etats-Unis [Termes IGN] événement [Termes IGN] géolocalisation [Termes IGN] migration humaine [Termes IGN] mobilité territoriale [Termes IGN] téléphonie mobile Résumé : (auteur) Conventional approaches for modeling human mobility pattern often focus on human activity and movement dynamics in their regular daily lives and cannot capture changes in human movement dynamics in response to large-scale events. With the rapid advancement of information and communication technologies, many researchers have adopted alternative data sources (e.g., cell phone records, GPS trajectory data) from private data vendors to study human movement dynamics in response to large-scale natural or societal events. Big geosocial data such as georeferenced tweets are publicly available and dynamically evolving as real-world events are happening, making it more likely to capture the real-time sentiments and responses of populations. However, precisely-geolocated geosocial data is scarce and biased toward urban population centers. In this research, we developed a big geosocial data analytical framework for extracting human movement dynamics in response to large-scale events from publicly available georeferenced tweets. The framework includes a two-stage data collection module that collects data in a more targeted fashion in order to mitigate the data scarcity issue of georeferenced tweets; in addition, a variable bandwidth kernel density estimation(VB-KDE) approach was adopted to fuse georeference information at different spatial scales, further augmenting the signals of human movement dynamics contained in georeferenced tweets. To correct for the sampling bias of georeferenced tweets, we adjusted the number of tweets for different spatial units (e.g., county, state) by population. To demonstrate the performance of the proposed analytic framework, we chose an astronomical event that occurred nationwide across the United States, i.e., the 2017 Great American Eclipse, as an example event and studied the human movement dynamics in response to this event. However, this analytic framework can easily be applied to other types of large-scale events such as hurricanes or earthquakes. Numéro de notice : A2021-275 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/SOCIETE NUMERIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2021.101605 date de publication en ligne : 05/02/2021 En ligne : https://doi.org/10.1016/j.compenvurbsys.2021.101605 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97358 [article]

Des pixels et des peuples / Laurent Polidori in Géomètre, n° 2190 (avril 2021)

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Gridded population mapping for Germany based on building density, height and type from Earth Observation data using census disaggregation and bottom-up estimates / Franz Schug in Plos one, vol 16 n° 3 (March 2021)  

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Geographical random forests: a spatial extension of the random forest algorithm to address spatial heterogeneity in remote sensing and population modelling / Stefanos Georganos in Geocarto international, vol 36 n° 2 ([01/02/2021])  

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Population dynamics and natural hazard risk management: conceptual and practical linkages for the case of Austrian policy making / Christoph Clar in Natural Hazards, Vol 105 n° 2 (January 2021)  

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Development and analysis of land-use/land-cover spatio-temporal metrics in urban environments: Exploring urban growth patterns and linkages to socio-economic factors / Marta Sapena Moll (2021)  

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Incorporating memory-based preferences and point-of-interest stickiness into recommendations in location-based social networks / Hang Zhang in ISPRS International journal of geo-information, vol 10 n° 1 (January 2021)  

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Local fuzzy geographically weighted clustering: a new method for geodemographic segmentation / George Grekousis in International journal of geographical information science IJGIS, vol 35 n° 1 (January 2021)  

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Near-real-time identification of the drivers of deforestation in French Guiana / Marie Ballère (2021)  

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Urban construction waste with VHR remote sensing using multi-feature analysis and a hierarchical segmentation method / Qiang Chen in Remote sensing, vol 13 n° 1 (January 2021)  

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Urban Informatics / Wenzhong Shi (2021)  

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