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Flood vulnerability assessment of urban buildings based on integrating high-resolution remote sensing and street view images / Ziyao Xing in Sustainable Cities and Society, vol 92 (May 2023)  

Public [article]  inSustainable Cities and Society > vol 92 (May 2023) . - n° 104467 Titre : Flood vulnerability assessment of urban buildings based on integrating high-resolution remote sensing and street view images Type de document : Article/Communication Auteurs : Ziyao Xing, Auteur ; Shuai Yang, Auteur ; Xuli Zan, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 104467 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] attention (apprentissage automatique) [Termes IGN] bâtiment [Termes IGN] Chine [Termes IGN] gestion des risques [Termes IGN] image Streetview [Termes IGN] inondation [Termes IGN] milieu urbain [Termes IGN] planification urbaine [Termes IGN] Quickbird [Termes IGN] segmentation sémantique [Termes IGN] vulnérabilité Résumé : (auteur) Urban flood risk management requires an extensive investigation of the vulnerability characteristics of buildings. Large-scale field surveys usually cost a lot of time and money, while satellite remote sensing and street view images can provide information on the tops and facades of buildings respectively. Thereupon, this paper develops a building vulnerability assessment framework using remote sensing and street view features. Specifically, a UNet-based semantic segmentation model, FSA-UNet (Fusion-Self-Attention-UNet) is proposed to integrate remote sensing and street view features and the vulnerability information contained in the images is fully exploited. And the building vulnerability index is generated to provide the spatial distribution characteristics of urban building vulnerability. The experiment shows that the mIoU of the proposed model can reach 82% for building vulnerability classification in Hefei, China, which is more accurate than the traditional semantic segmentation models. The results indicate that the integration of street view and remote sensing image features can improve the ability of building vulnerability assessment, and the model proposed in this study can better capture the correlation features of multi-angle images through the self-attention mechanism and combines hierarchy features and edge information to improve the classification effect. This study can support for disaster management and urban planning. Numéro de notice : A2023-152 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.scs.2023.104467 Date de publication en ligne : 23/02/2023 En ligne : https://doi.org/10.1016/j.scs.2023.104467 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102826 [article]

A GIS-based flood risk mapping of Assam, India, using the MCDA-AHP approach at the regional and administrative level / Laxmi Gupta in Journal of maps, vol 18 n° 2 (February 2023)  

Public [article]  inJournal of maps > vol 18 n° 2 (February 2023) . - 33 p. Titre : A GIS-based flood risk mapping of Assam, India, using the MCDA-AHP approach at the regional and administrative level Type de document : Article/Communication Auteurs : Laxmi Gupta, Auteur ; Jagabandhu Dixit, Auteur Année de publication : 2023 Article en page(s) : 33 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] analyse multicritère [Termes IGN] cartographie des risques [Termes IGN] eau de surface [Termes IGN] Inde [Termes IGN] inondation [Termes IGN] planification [Termes IGN] processus de hiérarchisation analytique [Termes IGN] ruissellement [Termes IGN] système d'information géographique [Termes IGN] vulnérabilité Résumé : (auteur) Floods are frequently occurring events in the Assam region due to the presence of the Brahmaputra River and the heavy monsoon period. An efficient and reliable methodology is utilized to prepare a GIS-based flood risk map for the Assam region, India. At the regional and administrative level, the flood hazard index (FHI), flood vulnerability index (FVI), and flood risk index (FRI) are developed using multi-criteria decision analysis (MCDA) – analytical hierarchy process (AHP). The selected indicators define the topographical, geological, meteorological, drainage characteristics, land use land cover, and demographical features of Assam. The results show that more than 70%, 57.37%, and 50% of the total area lie in moderate to very high FHI, FVI, and FRI classes, respectively. The proposed methodology can be applied to identify high flood risk zones and to carry out effective flood risk management and mitigation strategies in vulnerable areas. Numéro de notice : A2023-054 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/10106049.2022.2060329 Date de publication en ligne : 19/04/2022 En ligne : https://doi.org/10.1080/10106049.2022.2060329 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102387 [article]

GIS-based planning of buffer zones for protection of boreal streams and their riparian forests / Heikki Mykrä in Forest ecology and management, vol 528 (January-15 2023)  

Public [article]  inForest ecology and management > vol 528 (January-15 2023) . - n° 120639 Titre : GIS-based planning of buffer zones for protection of boreal streams and their riparian forests Type de document : Article/Communication Auteurs : Heikki Mykrä, Auteur ; M.J. Annala, Auteur ; Anu Hilli, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 120639 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] Alnus incana [Termes IGN] Betula pendula [Termes IGN] cours d'eau [Termes IGN] données lidar [Termes IGN] érosion hydrique [Termes IGN] forêt ripicole [Termes IGN] humidité du sol [Termes IGN] modèle numérique de surface [Termes IGN] modèle RUSLE [Termes IGN] Picea abies [Termes IGN] Pinus sylvestris [Termes IGN] protection de la biodiversité [Termes IGN] Salix (genre) [Termes IGN] zone boréale [Termes IGN] zone tampon Résumé : (auteur) Forested buffer zones with varying width have been suggested as the most promising approach for protecting boreal riparian biodiversity, reducing erosion, and minimizing nutrient leaching from managed forestry areas. Yet, less optimal fixed-width approach is still largely used, likely because of its simple design and implementation. We examined the efficiency of varying-width buffer zones based on depth-to-water (DTW) index in protecting stream riparian plant communities. We further compared the economic costs of DTW-based buffer to commonly used 5, 10 and 15 m fixed-width buffers. We also included an additional buffer based on a combination of DTW and erosion risk (Revised Universal Soil Loss Equation, RUSLE) into these comparisons to see the extent and cost of a buffer that should maximize the protection of the linked aquatic environment. Plant species richness increased with increasing soil moisture and species preferring moist conditions, nutrient-rich soils and high pH were clearly more abundant adjacent to stream in areas with high predicted soil moisture than in dry areas. Differences in species richness were paralleled by differences in community composition and higher beta diversity of plant communities in wet than in dry riparian areas. There were also several indicator species typical for moist and nutrient-rich soils for wet riparian areas. Riparian buffer zones based on DTW were on average larger than 15 m wide fixed-width buffers. However, the cost for DTW-based buffer was lower than for fixed-width buffer zones when the cost was normalized by area. Simulated selective cutting decreased the costs, but cutting possibilities were variable among streams and depended on the characteristics of forest stands. Our results thus suggest a high potential of DTW in predicting wet areas and variable-width buffer zones based on these areas in the protection of riparian biodiversity and stream ecosystems. Numéro de notice : A2023-029 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE Nature : Article DOI : 10.1016/j.foreco.2022.120639 Date de publication en ligne : 13/11/2022 En ligne : https://doi.org/10.1016/j.foreco.2022.120639 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102148 [article]

Sediment yield estimation in GIS environment using RUSLE and SDR model in Southern Ethiopia / Dawit Kanito in Geomatics, Natural Hazards and Risk, vol 14 n° 1 (2023)  

Public [article]  inGeomatics, Natural Hazards and Risk > vol 14 n° 1 (2023) . - n° 2167614 Titre : Sediment yield estimation in GIS environment using RUSLE and SDR model in Southern Ethiopia Type de document : Article/Communication Auteurs : Dawit Kanito, Auteur ; Dawit Bedadi, Auteur ; Samuel Feyissa, Auteur Année de publication : 2023 Article en page(s) : n° 2167614 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse de sensibilité [Termes IGN] bassin hydrographique [Termes IGN] Ethiopie [Termes IGN] image Landsat [Termes IGN] modèle RUSLE [Termes IGN] précipitation [Termes IGN] sédiment [Termes IGN] système d'information géographique Résumé : (auteur) Soil erosion and sediment yields are the current limitations and future threats to agriculture, water resources and hydropower projects particularly in developing countries. Estimating the extent and comprehending the spatial distribution of hotspot area is crucial to implement evidence-based soil and water conservation (SWC) measures with limited resources. The study used RUSLE and SDR models in ArcGIS 10.8 environment. The RUSLE model was found to be highly sensitive to C factor followed by LS factor. The result indicated that the annual soil loss varies from 0 to 359.99 t ha−1 yr−1 with 22.31 t ha−1 yr−1 as a mean annual. Besides, the estimated sediment yield ranged from 0 to 42.5 t ha−1 yr−1 with a mean value of 12.02 t ha−1 yr−1. The finding revealed that the central west (SW_5) and northeast (SW_4) parts of the watershed yield higher sediment. The result also signified that about 52.9% of the eroded materials including soil and nutrients are transferred to the outlet. The outcome of our finding undoubtedly aids in the identification of hotspot areas for the adoption of appropriate SWC measures. Hence, adopting RUSLE and SDR for Gununo watershed and another watershed having similar biophysical and environmental factors is suggested. Numéro de notice : A2023-155 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/19475705.2023.2167614 Date de publication en ligne : 26/01/2023 En ligne : https://doi.org/10.1080/19475705.2023.2167614 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102841 [article]

Simplified automatic prediction of the level of damage to similar buildings affected by river flood in a specific area / David Marín-García in Sustainable Cities and Society, vol 88 (January 2023)  

Public [article]  inSustainable Cities and Society > vol 88 (January 2023) . - n° 104251 Titre : Simplified automatic prediction of the level of damage to similar buildings affected by river flood in a specific area Type de document : Article/Communication Auteurs : David Marín-García, Auteur ; Juan Rubio-Gómez-Torga, Auteur ; Manuel Duarte-Pinheiro, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 104251 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] acquisition de données [Termes IGN] Andalousie [Termes IGN] apprentissage automatique [Termes IGN] bassin hydrographique [Termes IGN] bâtiment [Termes IGN] cartographie des risques [Termes IGN] coefficient de corrélation [Termes IGN] dommage matériel [Termes IGN] évaluation des paramètres [Termes IGN] image à haute résolution [Termes IGN] modèle de simulation [Termes IGN] zone inondable Résumé : (auteur) Flooding due to overflowing rivers affects the construction elements of many buildings. Although significant progress has been made in predicting this damage, there is still a need to continue studying this issue. For this reason, the main goal of this research focuses on finding out if, based on a small dataset of cases of a given area, it is possible to predict at least three degrees of affectation in buildings, considering only three environmental factors (minimum distance from the river, unevenness and possible water communication). To meet this goal, the methodological approach followed considers scientific literature review and collection and analysis of a small dataset from 101 buildings that have been affected by floods in the Guadalquivir River basin (Andalusia. Spain). After analyzing this data, algorithms based on machine learning (ML) are applied to predict the degree of affection. The results, analysis and conclusions indicate that, if the study focuses on a specific area and similar buildings, using a correlation matrix and ML algorithms such as the "Decision Tree" with cross-validation, around 90% can be achieved in the "Recall" and "Precision" of "High-Level-Affection" class, and an “Accuracy” around 80% in general. Numéro de notice : A2023-006 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.scs.2022.104251 Date de publication en ligne : 15/10/2022 En ligne : https://doi.org/10.1016/j.scs.2022.104251 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102093 [article]

Eco-environment and coupling coordination and quantification of urbanization in Yangtze River delta considering spatial non-stationarity / Yaqiu Zhang in Geocarto international, vol 37 n° 27 ([20/12/2022])  

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Assessment of groundwater potential using multi-criteria decision analysis and geoelectrical surveying / Marzieh Shabani in Geo-spatial Information Science, vol 25 n° 4 (December 2022)  

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Hybrid XGboost model with various Bayesian hyperparameter optimization algorithms for flood hazard susceptibility modeling / Saeid Janizadeh in Geocarto international, vol 37 n° 25 ([01/12/2022])  

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Modelling evacuation preparation time prior to floods: A machine learning approach / R. Sreejith in Sustainable Cities and Society, vol 87 (December 2022)  

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Progressive collapse of dual-line rivers based on river segmentation considering cartographic generalization rules / Fubing Zhang in ISPRS International journal of geo-information, vol 11 n° 12 (December 2022)  

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Updating and backdating analyses for mitigating uncertainties in land change modeling: a case study of the Ci Kapundung upper water catchment area, Java Island, Indonesia / Medria Shekar Rani in International journal of geographical information science IJGIS, vol 36 n° 12 (December 2022)  

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Automatic vectorization of fluvial corridor features on historical maps to assess riverscape changes / Samuel Dunesme in Cartography and Geographic Information Science, vol 49 n° 6 (November 2022)  

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Flash-flood hazard susceptibility mapping in Kangsabati River Basin, India / Rabin Chakrabortty in Geocarto international, vol 37 n° 23 ([15/10/2022])  

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Spatio-temporal graph convolutional networks for road network inundation status prediction during urban flooding / Faxi Yuan in Computers, Environment and Urban Systems, vol 97 (October 2022)  

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Development of a novel hybrid multi-boosting neural network model for spatial prediction of urban flood / Amid Darabi in Geocarto international, vol 37 n° 19 ([15/09/2022])  

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