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Development of a GIS-based alert system to mitigate flash flood impacts in Asyut governorate, Egypt / Soha A. Mohamed in Natural Hazards, vol 108 n° 3 (September 2021)  

Public [article]  inNatural Hazards > vol 108 n° 3 (September 2021) . - pp 2739 - 2763 Titre : Development of a GIS-based alert system to mitigate flash flood impacts in Asyut governorate, Egypt Type de document : Article/Communication Auteurs : Soha A. Mohamed, Auteur Année de publication : 2021 Article en page(s) : pp 2739 - 2763 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] analyse multicritère [Termes IGN] crue [Termes IGN] densité de population [Termes IGN] Egypte [Termes IGN] image Landsat-OLI [Termes IGN] message d'alerte [Termes IGN] modèle numérique de surface [Termes IGN] précipitation [Termes IGN] processus d'analyse hiérarchique [Termes IGN] surveillance hydrologique [Termes IGN] système d'information géographique Résumé : (auteur) Egypt is one Arab country that is vulnerable to flash floods caused by heavy and intensive rainfall. Different locations in Egypt are vulnerable to the hazards of flash floods, especially in Upper Egypt. Throughout history, Egypt witnessed a series of events of flash floods that lead to mortality, damages, and economic losses. The intensity and frequency of flash floods in Egypt vary from year to year according to a number of hydrological and climatological variables. Although several previous flash floods studies have been conducted in Egypt, studies on the governorate of Asyut are still limited. This study integrates the physical and social parameters in order to assess the vulnerability to flash floods. The objectives of this study are to shed light on flash floods in the study area, develop a vulnerability model to determine the regions vulnerable to the impacts of flash floods, and propose a flash flood alert system in the governorate of Asyut in Egypt to mitigate the impacts of flash floods and to avoid the loss of life and property. The AHP (analytical hierarchy process) is used for assigning the optimal criterion weight of the considered vulnerability parameters based on the responses of eight expert respondents to an online Google forms questionnaire. The highest weighted flash floods causative parameters are population density (27.4%), precipitation (22.1%), total population (16.4%), and elevation (10.2%), respectively. The results reveal that Asyut is one of the Egyptian governorates pro ne to flash floods’ impacts, especially in Dayrut, Al-Qusiyah, and Abnub, urban districts. The findings of this study are expected to be useful to policymakers and responsible authorities for better disaster risk management and for dealing with the flash floods events in the future. Numéro de notice : A2021-598 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article DOI : 10.1007/s11069-021-04799-2 date de publication en ligne : 28/05/2021 En ligne : https://doi.org/10.1007/s11069-021-04799-2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98229 [article]

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]

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]

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)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 1 (January 2021) . - pp 152 - 174 Titre : Local fuzzy geographically weighted clustering: a new method for geodemographic segmentation Type de document : Article/Communication Auteurs : George Grekousis, Auteur Année de publication : 2021 Article en page(s) : pp 152 - 174 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse de groupement [Termes IGN] classification floue [Termes IGN] données démographiques [Termes IGN] New York (Etats-Unis ; ville) [Termes IGN] optimisation par essaim de particules [Termes IGN] pondération [Termes IGN] régression géographiquement pondérée [Termes IGN] santé [Termes IGN] segmentation [Termes IGN] voisinage (topologie) Résumé : (auteur) Fuzzy geographically weighted clustering has been proposed as an approach for improving fuzzy c-means algorithm when applied to geodemographic analysis. This clustering method allows a spatial entity to belong to more than one cluster with varying degrees, namely, membership values. Although fuzzy geographically weighted clustering attempts to create geographically aware clusters, it partially fails to trace spatial dependence and heterogeneity because, as a global metric, the membership values are calculated across the entire set of spatial entities. Here we introduce the first local version of fuzzy geographically weighted clustering, ‘local fuzzy geographically weighted clustering.’ In local fuzzy geographically weighted clustering, the membership values of a spatial entity are updated only according to the membership values of the spatial entities within its neighborhood and not across the entire set of entities, as originally proposed by the global metric. Additionally, we apply particle swarm optimization meta-heuristic to overcome the random initialization problem regarding the fuzzy c-means algorithm. To evaluate our method we compare local fuzzy geographically weighted clustering to global fuzzy geographically weighted clustering using a cancer incident benchmark dataset for Manhattan, New York. The results show that local fuzzy geographically weighted clustering outperforms the global version in all experimental settings. Numéro de notice : A2021-022 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1808221 date de publication en ligne : 21/08/2020 En ligne : https://doi.org/10.1080/13658816.2020.1808221 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96525 [article]

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Monitoring population dynamics in the Pearl River Delta from 2000 to 2010 / Sisi Yu in Geocarto international, vol 35 n° 14 ([15/10/2020])  

Public [article]  inGeocarto international > vol 35 n° 14 [15/10/2020] . - pp 1511 - 1526 Titre : Monitoring population dynamics in the Pearl River Delta from 2000 to 2010 Type de document : Article/Communication Auteurs : Sisi Yu, Auteur ; ZengXiang Zhang, Auteur ; Fang Liu, Auteur Année de publication : 2020 Article en page(s) : pp 1511 - 1526 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] agglomération [Termes IGN] croissance urbaine [Termes IGN] delta de la rivière des perles [Termes IGN] données démographiques [Termes IGN] image DMSP-OLS [Termes IGN] Kouangtoung (Chine) [Termes IGN] prise de vue nocturne [Termes IGN] recensement démographique [Termes IGN] répartition géographique [Termes IGN] série temporelle [Termes IGN] surveillance de l'urbanisation Résumé : (auteur) Although numerous literatures have documented the monitoring of population distributions and dynamics for socio-economic development, environmental protection, and urban planning on different scales, little attention has been paid to long-term and multi-frequency population evolution on urban agglomeration scale, especially in non-census years. Furthermore, although multi models have been applied to population spatialization based on night-time light imagery (NLT) and census data, their accuracy needs to be further improved. Selected the Pearl River Delta (PRD), China as the study area, this work aimed to solve the aforementioned problems by constructing the residential extent extraction index (REEI) and employing the population growth theory and ‘DN density–population density’ model. Results indicated that the proposed approaches were feasible to optimize NTL products and simulate populations in both census (2000, 2010) and non-census (2005) years. Population evolution in the PRD presented distinct differences from space and over time, and mainly driven by socioeconomic development. Numéro de notice : A2020-617 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1576778 date de publication en ligne : 28/05/2019 En ligne : https://doi.org/10.1080/10106049.2019.1576778 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95993 [article]

Landuse and land cover identification and disaggregating socio-economic data with convolutional neural network / Jingtao Yao in Geocarto international, vol 35 n° 10 ([01/08/2020])  

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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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Fine-scale dasymetric population mapping with mobile phone and building use data based on grid Voronoi method / Zhenzhong Peng in ISPRS International journal of geo-information, vol 9 n° 6 (June 2020)  

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A method for urban population density prediction at 30m resolution / Krishnachandran Balakrishnan in Cartography and Geographic Information Science, vol 47 n° 3 (May 2020)  

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Road network structure and ride-sharing accessibility: A network science perspective / Mingshu Wang in Computers, Environment and Urban Systems, vol 80 (March 2020)  

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Interactive display of surnames distributions in historic and contemporary Great Britain / Justin Van Dijk in Journal of maps, vol 16 n° 1 ([02/01/2020])  

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Revealing the Correlation between Population Density and the Spatial Distribution of Urban Public Service Facilities with Mobile Phone Data / Yi Shi in ISPRS International journal of geo-information, Vol 9 n° 1 (January 2020)  

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A spatio-temporal web-application for the understanding of the formation of the Parisian metropolis / Emile Blettery (2020)  

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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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Understanding demographic and socioeconomic biases of geotagged Twitter users at the county level / Jiang Juqin in Cartography and Geographic Information Science, vol 46 n° 3 (May 2019)  

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