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Establishing a GIS-based evaluation method considering spatial heterogeneity for debris flow susceptibility mapping at the regional scale / Shengwu Qin in Natural Hazards, vol 114 n° 3 (December 2022)  

Public [article]  inNatural Hazards > vol 114 n° 3 (December 2022) . - pp 2709 - 2738 Titre : Establishing a GIS-based evaluation method considering spatial heterogeneity for debris flow susceptibility mapping at the regional scale Type de document : Article/Communication Auteurs : Shengwu Qin, Auteur ; Shuangshuang Qiao, Auteur ; Jingyu Yao, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 2709 - 2738 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] cartographie des risques [Termes IGN] Chine [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] éboulement [Termes IGN] hétérogénéité spatiale [Termes IGN] prévention des risques [Termes IGN] séparateur à vaste marge [Termes IGN] système d'information géographique Résumé : (auteur) Susceptibility mapping is an effective means of preventing debris flow disasters. However, previous studies have failed to solve spatial heterogeneity well, especially at the regional scale. The main objective of this study is to solve the spatial heterogeneity of regional-scale debris flow susceptibility (DFS) mapping by establishing a geographic information system (GIS)-based processing framework. The framework was realized by integrating the determination factor (DFactor) model with machine learning models. The DFactor model established different combinations of evaluation factors in each local region and clarified the differing contributions of influencing factors to DFS. To test the feasibility of the framework, the support vector machine (SVM) and two-dimensional convolutional neural network (CNN) were integrated with the DFactor model (DFactor-SVM and DFactor-CNN) to evaluate DFS in Jilin Province, China. The individual models (SVM and CNN) were also used to map the DFS for comparison with the integrated models. For debris flow modeling, 868 debris flow samples were collected and randomly divided into two datasets: 70% of the samples were used for training and the result was used for verification. The results of the receiver operating characteristic curve showed that the integrated models performed better. The DFactor-CNN model had the highest predictive accuracy, followed by the DFactor-SVM, CNN and SVM models. In general, the GIS-based processing framework maximizes the contribution of the influencing factors to debris flows and enhances the prediction ability of models. Furthermore, it provides a reliable means to predict debris flows at the regional scale. Numéro de notice : A2022-854 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s11069-022-05487-5 Date de publication en ligne : 06/08/2022 En ligne : https://doi.org/10.1007/s11069-022-05487-5 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102101 [article]

A GIS and hybrid simulation aided environmental impact assessment of city-scale demolition waste management / Zhikun Ding in Sustainable Cities and Society, vol 86 (November 2022)  

Public [article]  inSustainable Cities and Society > vol 86 (November 2022) . - n° 104108 Titre : A GIS and hybrid simulation aided environmental impact assessment of city-scale demolition waste management Type de document : Article/Communication Auteurs : Zhikun Ding, Auteur ; Xinping Wen, Auteur ; Xiaoyan Cao, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 104108 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] aide à la décision [Termes IGN] déchet [Termes IGN] impact sur l'environnement [Termes IGN] modèle empirique [Termes IGN] modèle orienté agent [Termes IGN] planification urbaine [Termes IGN] Shenzhen [Termes IGN] simulation dynamique [Termes IGN] système d'information géographique [Termes IGN] ville intelligente Résumé : (auteur) A considerable amount of demolition waste (DW) generated by urbanization and urban renewal has brought significant threats to the environment. However, there is a serious lack of environmental impact assessment towards city-scale demolition waste management (DWM), particularly from the systematical and dynamical perspective. Traditionally the assessment has been conducted from a static perspective. The purpose of this paper is to comprehensively evaluate the environmental impact of city-scale DWM from a complex system perspective. A novel evaluation model was developed by innovatively integrating the geographic information system (GIS) and system hybrid simulation consisting of system dynamics (SD), agent-based modeling (ABM) and discrete event simulation (DES). The proposed model was verified. Based on an empirical analysis of Shenzhen, China, it is found that the environmental impact of city-scale DWM is mainly concentrated in the central and northeastern regions of Shenzhen, demonstrating spatial heterogeneity and regional aggregation. Furthermore, the results reveal that the model is robust and effective to assess environmental impact from four aspects, i.e., land occupation, water pollution, air pollution and energy consumption. The findings contribute to a better understanding of the status quo of city-scale DWM and accompanying environmental impacts, and coordinating various district governments to formulate effective DWM policies. Numéro de notice : A2022-817 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.scs.2022.104108 Date de publication en ligne : 06/08/2022 En ligne : https://doi.org/10.1016/j.scs.2022.104108 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101983 [article]

GIS and MCDMA prioritization based modeling for sub-watershed in Bastora river basin / Raid Mahmood Faisal in Geocarto international, vol 37 n° 23 ([15/10/2022])  

Public [article]  inGeocarto international > vol 37 n° 23 [15/10/2022] . - pp 6826 - 6847 Titre : GIS and MCDMA prioritization based modeling for sub-watershed in Bastora river basin Type de document : Article/Communication Auteurs : Raid Mahmood Faisal, Auteur Année de publication : 2022 Article en page(s) : pp 6826 - 6847 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] analyse multicritère [Termes IGN] ArcGIS [Termes IGN] érosion [Termes IGN] géomorphométrie [Termes IGN] Iraq [Termes IGN] modèle RUSLE [Termes IGN] processus de hiérarchisation analytique Résumé : (auteur) This study examines the watersheds in the Bastora river basin and builds a geographic model within ARC GIS software. The work was divided into three phases. The first phase was to obtain the results of 14 morphometric parameters to determine priorities, by using AHP model to extract the relative weights of the parameters. Then, these weights are adopted in building (SDI, TOPSIS and SAW) models to determine levels of priorities. The outputs were classified into five categories according to the degree of their susceptibility to erosion. The second phase includes creating another model to provide necessary data and tools for building the RUSLE model. The final phase validates of pairs of models (TOPSIS-RUSLE), (SDI-RUSLE), and (SAW-RUSLE) using least squares tool for comparison between the results. The results indicate a highly statistically significant relationship among all the previous pairs of models with clear preference recorded for (TOPSIS-RUSLE) models relationship. Numéro de notice : A2022-751 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2021.1950848 Date de publication en ligne : 26/07/2021 En ligne : https://doi.org/10.1080/10106049.2021.1950848 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101743 [article]

Assessing logging residues availability for energy production by using forest management plans data and geographic information system (GIS) / Luca Nonini in European Journal of Forest Research, vol 141 n° 5 (October 2022)  

Public [article]  inEuropean Journal of Forest Research > vol 141 n° 5 (October 2022) . - pp 959 - 977 Titre : Assessing logging residues availability for energy production by using forest management plans data and geographic information system (GIS) Type de document : Article/Communication Auteurs : Luca Nonini, Auteur ; Calogero Schillaci, Auteur ; Marco Fiala, Auteur Année de publication : 2022 Article en page(s) : pp 959 - 977 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] données localisées [Termes IGN] estimation statistique [Termes IGN] exploitation forestière [Termes IGN] gestion forestière [Termes IGN] Italie [Termes IGN] planification [Termes IGN] système d'information géographique Résumé : (auteur) The aim of the work was to quantify the mass of logging residues (branches and tops; t yr−1 dry matter, DM) for energy generation starting from Forest Management Plans (FMP) data. The methodology was applied to public stands of an Italian district (area: 3.60 × 104 ha; period: 2009–2018). Compared to the previous preliminary analysis, the potentially available residues were computed considering forest accessibility and road traversability, by combining FMPs data with a geographic information system (GIS). New issues that were assessed here were: (i) representation of stands consisting of multiple disconnected parts; (ii) calculation of producible residues by using different values of biomass expansion factors (Scenario 1, S1; Scenario 2, S2). The potentially available residues computed for the analyzed period were used to quantify the current sustainable supply. Then, the potentially generated heat (thermal energy, TE; GJ yr−1) and electricity (EE; GJ yr−1), and the potentially avoided CO2 emissions into the atmosphere (EM; t yr−1 CO2) related to the final combustion process were computed by assuming that the current supply of residues was used as woodchips in a local centralized heating plant currently operating. For both S1 and S2, the large difference between the potentially producible and the potentially available residues demonstrated that geodata are essential for reliable estimations. Moreover, as the required information for the GIS analysis can be easily found in databases made available by forestry authorities, the proposed approach can be applied also to other areas; this could be helpful to support local decision-makers in defining sustainable practices for residues recovery. Numéro de notice : A2022-760 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE Nature : Article DOI : 10.1007/s10342-022-01484-2 Date de publication en ligne : 22/08/2022 En ligne : https://doi.org/10.1007/s10342-022-01484-2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101772 [article]

Developing a GIS-based rough fuzzy set granulation model to handle spatial uncertainty for hydrocarbon structure classification, case study: Fars domain, Iran / Sahand Seraj in Geo-spatial Information Science, vol 25 n° 3 (October 2022)  

Public [article]  inGeo-spatial Information Science > vol 25 n° 3 (October 2022) . - pp 399 - 41 Titre : Developing a GIS-based rough fuzzy set granulation model to handle spatial uncertainty for hydrocarbon structure classification, case study: Fars domain, Iran Type de document : Article/Communication Auteurs : Sahand Seraj, Auteur ; Mahmoud Reza Delavar, Auteur Année de publication : 2022 Article en page(s) : pp 399 - 41 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] cartographie géologique [Termes IGN] classification floue [Termes IGN] entropie de Shannon [Termes IGN] forage [Termes IGN] granulométrie (pétrologie) [Termes IGN] hydrocarbure [Termes IGN] incertitude géométrique [Termes IGN] Iran [Termes IGN] prospection minérale [Termes IGN] sous ensemble flou [Termes IGN] système d'information géographique Résumé : (auteur) It is well agreed that geologic risk occurs during hydrocarbon exploration because diverse uncertainties accompany the entire hydrocarbon system parameters such as the source rock, reservoir rock, trap and seal rock. In order to overcome such attributes with uncertainties, a number of soft computing methods are used. Information granules could be provided by the Rough Fuzzy Set Granulation (RFSG) with a thorough quality evaluation. This is capable of attribute reduction that has been claimed to be essential in investigating the hydrocarbon systems. This paper is an endeavor to recommend a Geospatial Information System (GIS)-based model with the aim of categorizing the hydrocarbon structures map consistent with the uncertainty range concepts of geologic risk in the rough fuzzy sets and granular computing. The model used the RFSG for the attribute reduction by a Decision Logic language (DL-language). The RFSG was employed in order to classify hydrocarbon structures according to geological risk and extract the fuzzy rules with a predefined range of uncertainty. In order to assess the precisions of the fuzzy decisions on the hydrocarbon structure classification, the fuzzy entropy and fuzzy cross-entropy are applied. The proposed RFSG model applied for 62 structures as the training data, average fuzzy entropy has been calculated as 0.85, whereas the average fuzzy cross-entropy has been calculated 0.18. As it can be discerned, just seven structures had cross-entropies greater than 0.1, while three structures were larger than 0.3. It is implied that the precision of the proposed model is about 89%. The results yielded two reductions for the condition attributes and 11 fuzzy rules being filtered by the granular computing values. Numéro de notice : A2022-724 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/10095020.2021.2020600 Date de publication en ligne : 03/02/2022 En ligne : https://doi.org/10.1080/10095020.2021.2020600 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101667 [article]

A comparative assessment of modeling groundwater vulnerability using DRASTIC method from GIS and a novel classification method using machine learning classifiers / Qasim Khan in Geocarto international, vol 37 n° 20 ([20/09/2022])  

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Flood vulnerability and buildings’ flood exposure assessment in a densely urbanised city: comparative analysis of three scenarios using a neural network approach / Quoc Bao Pham in Natural Hazards, vol 113 n° 2 (September 2022)  

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Study on city digital twin technologies for sustainable smart city design: A review and bibliometric analysis of geographic information system and building information modeling integration / Haishan Xia in Sustainable Cities and Society, vol 84 (September 2022)  

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Use of GIS and dasymetric mapping for estimating tsunami-affected population to facilitate humanitarian relief logistics: a case study from Phuket, Thailand / Kiatkulchai Jitt-Aer in Natural Hazards, vol 113 n° 1 (August 2022)  

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A model development on GIS-driven data to predict temporal daily collision through integrating Discrete Wavelet Transform (DWT) and Artificial Neural Network (ANN) algorithms; case study: Tehran-Qazvin freeway / Reza Sanayeia in Geocarto international, vol 37 n° 14 ([20/07/2022])  

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Modelling areas for sustainable forest management in a mining and human dominated landscape: A Geographical Information System (GIS)- Multi-Criteria Decision Analysis (MCDA) approach / Xavier Takam Tiamgne in Annals of GIS, vol 28 n° 3 (July 2022)  

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Risk assessment and prediction of forest health for effective geo-environmental planning and monitoring of mining affected forest area in hilltop region / Narayan Kayet in Geocarto international, vol 37 n° 11 ([15/06/2022])  

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Analysis of the land suitability for paddy fields in Tanzania using a GIS-based analytical hierarchy process / Ahmad Al-Hanbali in Geo-spatial Information Science, vol 25 n° 2 ([01/06/2022])  

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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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GIS and machine learning for analysing influencing factors of bushfires using 40-year spatio-temporal bushfire data / Wanqin He in ISPRS International journal of geo-information, vol 11 n° 6 (June 2022)  

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