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

Public [article]  inGéomètre > n° 2190 (avril 2021) . - pp 15 - 15 Titre : Des pixels et des peuples Type de document : Article/Communication Auteurs : Laurent Polidori, Auteur Année de publication : 2021 Article en page(s) : pp 15 - 15 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] croissance urbaine [Termes IGN] détection de changement [Termes IGN] frontière [Termes IGN] image thermique [Termes IGN] indicateur démographique [Termes IGN] mode d'occupation du sol [Termes IGN] population rurale [Termes IGN] population urbaine Résumé : (Auteur) Instruments de mesure physique, les satellites sont parfois utilisés pour l'étude des sociétés. Numéro de notice : A2021-324 Affiliation des auteurs : non IGN Thématique : IMAGERIE/URBANISME Nature : Article nature-HAL : ArtSansCL DOI : sans Date de publication en ligne : 07/04/2021 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97482 [article]

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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)  

Public [article]  inPlos one > vol 16 n° 3 (March 2021) . - n° 0249044 Titre : Gridded population mapping for Germany based on building density, height and type from Earth Observation data using census disaggregation and bottom-up estimates Type de document : Article/Communication Auteurs : Franz Schug, Auteur ; David Frantz, Auteur ; Sebastian van der Linden, Auteur ; Patrick Hostert, Auteur Année de publication : 2021 Article en page(s) : n° 0249044 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Allemagne [Termes IGN] bati [Termes IGN] densité du bâti [Termes IGN] estimation statistique [Termes IGN] figuration de la densité [Termes IGN] image Sentinel-MSI [Termes IGN] image Sentinel-SAR [Termes IGN] population Résumé : (auteur) Gridded population data is widely used to map fine scale population patterns and dynamics to understand associated human-environmental processes for global change research, disaster risk assessment and other domains. This study mapped gridded population across Germany using weighting layers from building density, building height (both from previous studies) and building type datasets, all created from freely available, temporally and globally consistent Copernicus Sentinel-1 and Sentinel-2 data. We first produced and validated a nation-wide dataset of predominant residential and non-residential building types. We then examined the impact of different weighting layers from density, type and height on top-down dasymetric mapping quality across scales. We finally performed a nation-wide bottom-up population estimate based on the three datasets. We found that integrating building types into dasymetric mapping is helpful at fine scale, as population is not redistributed to non-residential areas. Building density improved the overall quality of population estimates at all scales compared to using a binary building layer. Most importantly, we found that the combined use of density and height, i.e. volume, considerably increased mapping quality in general and with regard to regional discrepancy by largely eliminating systematic underestimation in dense agglomerations and overestimation in rural areas. We also found that building density, type and volume, together with living floor area per capita, are suitable to produce accurate large-area bottom-up population estimates. Numéro de notice : A2021-305 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1371/journal.pone.0249044 Date de publication en ligne : 26/03/2021 En ligne : https://doi.org/10.1371/journal.pone.0249044 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97654 [article]

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])  

Public [article]  inGeocarto international > vol 36 n° 2 [01/02/2021] . - pp 121 -1 36 Titre : Geographical random forests: a spatial extension of the random forest algorithm to address spatial heterogeneity in remote sensing and population modelling Type de document : Article/Communication Auteurs : Stefanos Georganos, Auteur ; Tais Grippa, Auteur ; Assane Niang Gadiaga, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 121 -1 36 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] apprentissage automatique [Termes IGN] autocorrélation spatiale [Termes IGN] classification par forêts aléatoires [Termes IGN] Dakar [Termes IGN] densité de population [Termes IGN] distribution spatiale [Termes IGN] hétérogénéité spatiale [Termes IGN] modèle dynamique [Termes IGN] population [Termes IGN] utilisation du sol Résumé : (auteur) Machine learning algorithms such as Random Forest (RF) are being increasingly applied on traditionally geographical topics such as population estimation. Even though RF is a well performing and generalizable algorithm, the vast majority of its implementations is still ‘aspatial’ and may not address spatial heterogenous processes. At the same time, remote sensing (RS) data which are commonly used to model population can be highly spatially heterogeneous. From this scope, we present a novel geographical implementation of RF, named Geographical Random Forest (GRF) as both a predictive and exploratory tool to model population as a function of RS covariates. GRF is a disaggregation of RF into geographical space in the form of local sub-models. From the first empirical results, we conclude that GRF can be more predictive when an appropriate spatial scale is selected to model the data, with reduced residual autocorrelation and lower Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE) values. Finally, and of equal importance, GRF can be used as an effective exploratory tool to visualize the relationship between dependent and independent variables, highlighting interesting local variations and allowing for a better understanding of the processes that may be causing the observed spatial heterogeneity. Numéro de notice : A2021-080 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1595177 Date de publication en ligne : 10/06/2019 En ligne : https://doi.org/10.1080/10106049.2019.1595177 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96822 [article]

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)  

Public [article]  inNatural Hazards > Vol 105 n° 2 (January 2021) . - pp 765 - 1796 Titre : Population dynamics and natural hazard risk management: conceptual and practical linkages for the case of Austrian policy making Type de document : Article/Communication Auteurs : Christoph Clar, Auteur ; Lukas Löschner, Auteur ; Ralf Nordbeck, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 765 - 1796 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] aide à la décision [Termes IGN] Autriche [Termes IGN] décroissance urbaine [Termes IGN] démographie [Termes IGN] enquête [Termes IGN] politique publique [Termes IGN] population Résumé : (auteur) This contribution explores the conceptual and empirical linkages between population dynamics and natural hazard risk management (NHRM). Following a review of the international scholarly literature, we conduct a mixed-methods approach in Austria, combining an online survey among policy makers and other stakeholders with a thematic analysis of policy documents. The aim is to investigate the practical relevance of socio-demographic change in Austria’s NHRM. The study shows that many hazard-prone regions in Austria face population change, in particular demographic ageing and population decline. In addition, our findings from the online survey demonstrate the relevance of population dynamics in NHRM, especially with regard to hazard response and recovery. Nonetheless, policy formulation in NHRM overwhelmingly disregards demographic change as a relevant factor. Accordingly, the study underscores the importance of future-oriented risk management strategies to better account for ongoing and expected socio-demographic changes. Numéro de notice : A2021-202 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s11069-020-04376-z Date de publication en ligne : 24/10/2020 En ligne : https://doi.org/10.1007/s11069-020-04376-z Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97162 [article]

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)  

Public Titre : Development and analysis of land-use/land-cover spatio-temporal metrics in urban environments: Exploring urban growth patterns and linkages to socio-economic factors Type de document : Thèse/HDR Auteurs : Marta Sapena Moll, Auteur ; Luis Angel Ruiz Fernandez, Directeur de thèse Editeur : Valencia : Universidad politécnica de Valencia Année de publication : 2021 Importance : 268 p. Format : 21 x 30 cm Note générale : bibliographie PhD in Geomatics Engineering, Universidad politécnica de Valencia Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse discriminante [Termes IGN] analyse spatio-temporelle [Termes IGN] carte d'occupation du sol [Termes IGN] classification par forêts aléatoires [Termes IGN] croissance urbaine [Termes IGN] données socio-économiques [Termes IGN] implémentation (informatique) [Termes IGN] milieu urbain [Termes IGN] modélisation spatiale [Termes IGN] occupation du sol [Termes IGN] population urbaine [Termes IGN] régression linéaire [Termes IGN] Rhénanie du Nord-Wesphalie (Allemagne) [Termes IGN] utilisation du sol [Termes IGN] ville durable Résumé : (auteur) This thesis addresses the development and analysis of new tools and methods for monitoring and characterizing urban growth using geo-data and land-use/land-cover (LULC) databases, as well as exploring their relationships with socio-economic factors, providing new evidences regarding the use of LULC data for urban characterization at different levels by means of spatial and statistical methods. First, the most common spatio-temporal metrics were compiled and implemented within a software tool, IndiFrag. Then, we present a methodology based on spatio-temporal metrics and propose a new index that quantifies the inequality of growth between population and built-up areas to analyze and compare urban growth patterns at different levels. This allowed for a differentiation of growing patterns, besides, the analysis at various levels contributed to a better understanding of such patterns. Second, we quantified the two-way relationship between the urban structure in cities and their socio-economic status by means of spatial metrics issued from a local climate zone map for 31 cities in North Rhine-Westphalia, Germany. Based on these data, we quantified their relationship with socio-economic indicators by means of multiple linear regression models, explaining a significant part of their variability. The proposed method is transferable to other datasets, levels, and regions. Third, we assessed the use of spatio-temporal metrics derived from LULC maps to identify urban growth spatial patterns. We applied LULC change models to simulate different long-term scenarios of urban growth following various spatial patterns on diverse baseline urban forms. Then, we computed spatio-temporal metrics for the simulated scenarios, selected the most explanatory by applying a discriminant analysis and classified the growth patterns using clustering methods. Finally, we identified empirical relationships between socio-economic indicators and their change over time with the spatial structure of the built and natural elements in up to 600 urban areas from 32 countries. We employed random forest regression models and the spatio-temporal metrics were able to explain substantially the variability of socio-economic variables. This confirms that spatial patterns and their change are linked to socio-economic indicators. This work contributes to a better understanding of urban growth patterns and improves knowledge about the relationships between urban spatial structure and socio-economic factors, providing new methods for monitoring and assessing urban sustainability by means of LULC databases, which could be used by researchers, urban planners and decision-makers to ensure the sustainable future of urban environments. Note de contenu : 1- Introduction 2- Hypotheses and objectives 3- Spatio-temporal analysis of LULC and population in urban areas 4- Relationships between spatial patterns of urban structure and quality of life 5- Spatio-temporal metrics for urban growth spatial pattern categorization 6- Linking spatio-temporal metrics of built-up areas to socio-economic indicators on a semi-global scale 7- Conclusions Numéro de notice : 28308 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Thèse étrangère Note de thèse : PhD Thesis : Geomatics Engineering : Valencia, Spain : 2021 Organisme de stage : German Aerospace Center DOI : 10.4995/Thesis/10251/158626 En ligne : https://doi.org/10.4995/Thesis/10251/158626 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98112

Exploring the heterogeneity of human urban movements using geo-tagged tweets / Ding Ma in International journal of geographical information science IJGIS, vol 34 n° 12 (December 2020)  

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Impact of extreme weather events on urban human flow: A perspective from location-based service data / Zhenhua Chen in Computers, Environment and Urban Systems, vol 83 (September 2020)  

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Estimating and interpreting fine-scale gridded population using random forest regression and multisource data / Yun Zhou in ISPRS International journal of geo-information, vol 9 n° 6 (June 2020)  

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Extracting activity patterns from taxi trajectory data: a two-layer framework using spatio-temporal clustering, Bayesian probability and Monte Carlo simulation / Shuhui Gong in International journal of geographical information science IJGIS, vol 34 n° 6 (June 2020)  

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Mapping urban grey and green structures for liveable cities using a 3D enhanced OBIA approach and vital statistics / E. Banzhaf in Geocarto international, vol 35 n° 6 ([01/05/2020])  

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A review of assessment methods for cellular automata models of land-use change and urban growth / Xiaohua Tong in International journal of geographical information science IJGIS, vol 34 n° 5 (May 2020)  

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Measuring differential access to facilities between population groups using spatial Lorenz curves and related indices / Gordon A. Cromley in Transactions in GIS, Vol 23 n° 6 (November 2019)  

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High‐resolution national land use scenarios under a shrinking population in Japan / Haruka Ohashi in Transactions in GIS, vol 23 n° 4 (August 2019)  

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A methodology with a distributed algorithm for large-scale trajectory distribution prediction / QiuLei Guo in International journal of geographical information science IJGIS, Vol 33 n° 3-4 (March - April 2019)  

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Contemporary co-housing in Europe / Pernilla Hagbert (2019)  

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