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Mapping monthly population distribution and variation at 1-km resolution across China / Zhifeng Cheng in International journal of geographical information science IJGIS, vol 36 n° 6 (June 2022)
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Titre : Mapping monthly population distribution and variation at 1-km resolution across China Type de document : Article/Communication Auteurs : Zhifeng Cheng, Auteur ; Jianghao Wang, Auteur ; Yong Ge, Auteur Année de publication : 2022 Article en page(s) : pp 1166 - 1184 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie thématique
[Termes IGN] analyse spatiale
[Termes IGN] autocorrélation spatiale
[Termes IGN] Chine
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] densité de population
[Termes IGN] distribution spatiale
[Termes IGN] figuration de la densité
[Termes IGN] krigeage
[Termes IGN] population
[Termes IGN] série temporelle
[Termes IGN] téléphonie mobileRésumé : (auteur) Fine-grained inner-annual population data are instrumental in climate change response, resource allocation, and epidemic control. However, such data are currently scarce due to the lack of human-related indicators with both high temporal resolution and long-term coverage that can be used in the process of population spatialization. Here, we estimate monthly 1-km gridded population distribution across China in 2015 using time-series mobile phone positioning data. We construct a hybrid downscaling model to map the gridded population by incorporating random forest and area-to-point kriging. The estimated monthly population products appear to capture inner-annual population variations, especially during special periods, such as the festival, holiday, and short-term labor flow period, which are characterized by large-scale population movements. Additionally, compared with census data, the hybrid model-based results obtained exhibit higher consistency than popular global population products across all spatial extents. Our monthly 1-km data products for the population distribution across China in 2015 provide a credible dataset that can be employed in studies aimed at accurate population-dependent decisions. Numéro de notice : A2022-407 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1854767 Date de publication en ligne : 07/12/2020 En ligne : https://doi.org/10.1080/13658816.2020.1854767 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100724
in International journal of geographical information science IJGIS > vol 36 n° 6 (June 2022) . - pp 1166 - 1184[article]
Titre : Atlas of global change risk of population and economic systems Type de document : Monographie Auteurs : Peijun Shi, Éditeur scientifique Editeur : Berlin, Heidelberg, Vienne, New York, ... : Springer Année de publication : 2022 Collection : IHDP/Future Earth-Integrated Risk Governance Project Series, ISSN 2363-4979 Importance : 278 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-981-1666933-- Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie thématique
[Termes IGN] cartographie des risques
[Termes IGN] changement climatique
[Termes IGN] économie internationale
[Termes IGN] population
[Termes IGN] risque naturelRésumé : (Editeur) This book is open access and illustrates the spatial distribution of the global change risk of population and economic systems with the maps of environment, global climate change, global population and economic systems, and global change risk. The risks of global change are mapped at 0.25 degree grid unit. The risk results and their contribution rates of the world at national level are unprecedentedly derived and ranked. The book can be a good reference for researchers and students in the field of global climate change and natural disaster risk management, as well as risk managers and enterpriser to understand the global change risk of population and economic systems. Note de contenu : Environments
- Mapping Environments of the World / Peijun Shi, Jing’ai Wang, Ying Wang, Tian Liu
Climate Changes
- Mapping Temperature Changes / Xin Qi, Miaoni Gao, Tao Zhu, Siyu Li, Sicheng He, Jing Yang
- Mapping Precipitation Changes / Xianghui Kong, Xiaoxin Wang, Huopo Chen, Aihui Wang, Dan Wan, Lianlian Xu et al.
- Mapping Wind Speed Changes / Rui Mao, Cuicui Shi, Qi Zong, Xingya Feng, Yijie Sun, Yufei Wang et al.
Population and Economic System Changes
- Mapping Global Population Changes / Yujie Liu, Jie Chen
- Mapping Global Population Exposure to Heatwaves / Qinmei Han, Wei Xu, Peijun Shi
- Mapping Global Population Exposure to Rainstorms / Xinli Liao, Junlin Zhang, Wei Xu, Peijun Shi
- Mapping Global GDP Distribution / Fubao Sun, Tingting Wang, Hong Wang
- Mapping Global GDP Exposure to Drought / Fubao Sun, Tingting Wang, Hong Wang
- Mapping Global Crop Distribution / Yaojie Yue, Peng Su, Yuan Gao, Puying Zhang, Ran Wang, Anyu Zhang et al.
- Mapping Global Crop Exposure to Extremely High Temperature / Yaojie Yue, Peng Su, Yuan Gao, Puying Zhang, Ran Wang, Anyu Zhang et al.
- Mapping Global Industrial Value Added / Wei Song, Huiyi Zhu, Han Li, Qian Xue, Yuanzhe Liu
- Mapping Global Road Networks / Wenxiang Wu, Lingyun Hou
Global Change Risks
- Mapping Global Risk of Heatwave Mortality Under Climate Change / Qinmei Han, Weihang Liu, Wei Xu, Peijun Shi
- Mapping Global Risk of River Flood Mortality / Junlin Zhang, Xinli Liao, Wei Xu
- Mapping Global Risk of GDP Loss to River Floods / Junlin Zhang, Xinli Liao, Wei Xu
- Mapping Global Risk of Crop Yield Under Climate Change / Weihang Liu, Shuo Chen, Qingyang Mu, Tao Ye, Peijun ShiNuméro de notice : 26789 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Monographie DOI : 10.1007/978-981-16-6691-9 En ligne : https://doi.org/10.1007/978-981-16-6691-9 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99926
[article]
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 urbaineRésumé : (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
in Géomètre > n° 2190 (avril 2021) . - pp 15 - 15[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 063-2021041 SL Revue Centre de documentation Revues en salle Disponible 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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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] populationRésumé : (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
in Plos one > vol 16 n° 3 (March 2021) . - n° 0249044[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])
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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 d'arbres décisionnels
[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 solRésumé : (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
in Geocarto international > vol 36 n° 2 [01/02/2021] . - pp 121 -1 36[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)
PermalinkDevelopment 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)
PermalinkExploring 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)
PermalinkImpact 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)
PermalinkEstimating 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)
PermalinkExtracting 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)
PermalinkMapping 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])
PermalinkA 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)
PermalinkAnalyse de la distribution spatiale des implantations humaines : apports et limites d’indicateurs multi-échelles et trans-échelles / François Sémécurbe (2020)
PermalinkMeasuring 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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