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scientifique

Prioritizing urban water scarcity mitigation strategies based on hybrid multi-criteria decision approach under fuzzy environment / Ömer Ekmekcioğlu in Sustainable Cities and Society, vol 87 (December 2022)  

Public [article]  inSustainable Cities and Society > vol 87 (December 2022) . - n° 104195 Titre : Prioritizing urban water scarcity mitigation strategies based on hybrid multi-criteria decision approach under fuzzy environment Type de document : Article/Communication Auteurs : Ömer Ekmekcioğlu, Auteur ; Kerim Koc, Auteur ; Ismail Dabanli, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 104195 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] analyse multicritère [Termes IGN] changement climatique [Termes IGN] eau [Termes IGN] milieu urbain [Termes IGN] planification urbaine [Termes IGN] pondération [Termes IGN] processus de hiérarchisation analytique floue [Termes IGN] résilience écologique [Termes IGN] ressources en eau [Termes IGN] utilisation du sol [Termes IGN] ville durable Résumé : (auteur) This study was undertaken to be a remedy to urban water scarcity phenomena having escalated consequences with the contemporaneous effects of climate change and over-urbanization. Hence, a broad list of mitigation strategies comprising 44 action plans under seven dimensions was assessed depending upon five constraints (i.e., cost-effectiveness, time/effort required, feasibility, primary benefit, and secondary benefits). To realize the overarching aim of this research, the analytical hierarchy process (AHP) and technique for order of preference by similarity to ideal solution (TOPSIS) each subjected to the fuzzy set theory were employed. In this regard, the fuzzy AHP was utilized for determining the weights of constraining criteria, while the prioritization of the strategies was performed via the fuzzy TOPSIS. The results revealed that the primary benefit is the most prevailing criterion compared to its counterparts. In addition, procuring organized land use planning and limiting new growth in urban areas was found as the most promising strategy to combat urban water scarcity phenomena. The findings further highlighted the effectiveness of conducting integrated water resource planning against climate change and fostering the use of sustainable materials domestically in not only mitigating urban water scarcity but also increasing the resiliency and sustainability of the urbanized cities. Numéro de notice : A2022-818 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.scs.2022.104195 Date de publication en ligne : 21/09/2022 En ligne : https://doi.org/10.1016/j.scs.2022.104195 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101985 [article]

Change detection in street environments based on mobile laser scanning: A fuzzy spatial reasoning approach / Joachim Gehrung in ISPRS Open Journal of Photogrammetry and Remote Sensing, vol 5 (August 2022)  

Public [article]  inISPRS Open Journal of Photogrammetry and Remote Sensing > vol 5 (August 2022) . - n° 100019 Titre : Change detection in street environments based on mobile laser scanning: A fuzzy spatial reasoning approach Type de document : Article/Communication Auteurs : Joachim Gehrung, Auteur ; Marcus Hebel, Auteur ; Michael Arens, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 100019 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] détection automatique [Termes IGN] détection de changement [Termes IGN] données lidar [Termes IGN] Inférence floue [Termes IGN] information sémantique [Termes IGN] logique floue [Termes IGN] milieu urbain [Termes IGN] représentation spatiale [Termes IGN] semis de points [Termes IGN] voxel Résumé : (auteur) Automated change detection based on urban mobile laser scanning data is the foundation for a whole range of applications such as building model updates, map generation for autonomous driving and natural disaster assessment. The challenge with mobile LiDAR data is that various sources of error, such as localization errors, lead to uncertainties and contradictions in the derived information. This paper presents an approach to automatic change detection using a new category of generic evidence grids that addresses the above problems. Said technique, referred to as fuzzy spatial reasoning, solves common problems of state-of-the-art evidence grids and also provides a method of inference utilizing fuzzy Boolean reasoning. Based on this, logical operations are used to determine changes and combine them with semantic information. A quantitative evaluation based on a hand-annotated version of the TUM-MLS data set shows that the proposed method is able to identify confirmed and changed elements of the environment with F1-scores of 0.93 and 0.89. Numéro de notice : A2022-663 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.ophoto.2022.100019 En ligne : https://doi.org/10.1016/j.ophoto.2022.100019 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101524 [article]

Large-scale automatic identification of urban vacant land using semantic segmentation of high-resolution remote sensing images / Lingdong Mao in Landscape and Urban Planning, vol 222 (June 2022)  

Public [article]  inLandscape and Urban Planning > vol 222 (June 2022) . - n° 104384 Titre : Large-scale automatic identification of urban vacant land using semantic segmentation of high-resolution remote sensing images Type de document : Article/Communication Auteurs : Lingdong Mao, Auteur ; Zhe Zheng, Auteur ; Xiangfeng Meng, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 104384 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] apprentissage profond [Termes IGN] Chine [Termes IGN] détection d'objet [Termes IGN] grande échelle [Termes IGN] identification automatique [Termes IGN] image à haute résolution [Termes IGN] milieu urbain [Termes IGN] occupation du sol [Termes IGN] segmentation d'image [Termes IGN] segmentation sémantique Résumé : (auteur) Urban vacant land is a growing issue worldwide. However, most of the existing research on urban vacant land has focused on small-scale city areas, while few studies have focused on large-scale national areas. Large-scale identification of urban vacant land is hindered by the disadvantage of high cost and high variability when using the conventional manual identification method. Criteria inconsistency in cross-domain identification is also a major challenge. To address these problems, we propose a large-scale automatic identification framework of urban vacant land based on semantic segmentation of high-resolution remote sensing images and select 36 major cities in China as study areas. The framework utilizes deep learning techniques to realize automatic identification and introduces the city stratification method to address the challenge of identification criteria inconsistency. The results of the case study on 36 major Chinese cities indicate two major conclusions. First, the proposed framework of vacant land identification can achieve over 90 percent accuracy of the level of professional auditors with much higher result stability and approximately 15 times higher efficiency compared to the manual identification method. Second, the framework has strong robustness and can maintain high performance in various cities. With the above advantages, the proposed framework provides a practical approach to large-scale vacant land identification in various countries and regions worldwide, which is of great significance for the academic development of urban vacant land and future urban development. Numéro de notice : A2022-267 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.landurbplan.2022.104384 Date de publication en ligne : 03/03/2022 En ligne : https://doi.org/10.1016/j.landurbplan.2022.104384 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100275 [article]

Multi-objective optimization of urban environmental system design using machine learning / Peiyuan Li in Computers, Environment and Urban Systems, vol 94 (June 2022)  

Public [article]  inComputers, Environment and Urban Systems > vol 94 (June 2022) . - n° 101796 Titre : Multi-objective optimization of urban environmental system design using machine learning Type de document : Article/Communication Auteurs : Peiyuan Li, Auteur ; Tianfang Xu, Auteur ; Shiqi Wei, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 101796 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] algorithme génétique [Termes IGN] apprentissage automatique [Termes IGN] dioxyde de carbone [Termes IGN] ilot thermique urbain [Termes IGN] indicateur environnemental [Termes IGN] milieu urbain [Termes IGN] optimisation (mathématiques) [Termes IGN] planification urbaine [Termes IGN] processus gaussien [Termes IGN] régression [Termes IGN] végétation Résumé : (auteur) The efficacy of urban mitigation strategies for heat and carbon emissions relies heavily on local urban characteristics. The continuous development and improvement of urban land surface models enable rather accurate assessment of the environmental impact on urban development strategies, whereas physically-based simulations remain computationally costly and time consuming, as a consequence of the increasing complexity of urban system dynamics. Hence it is imperative to develop fast, efficient, and economic operational toolkits for urban planners to foster the design, implementation, and evaluation of urban mitigation strategies, while retaining the accuracy and robustness of physical models. In this study, we adopt a machine learning (ML) algorithm, viz. Gaussian Process Regression, to emulate the physics of heat and biogenic carbon exchange in the built environment. The ML surrogate is trained and validated on the simulation results generated by a state-of-the-art single-layer urban canopy model over a wide range of urban characteristics, showing high accuracy in capturing heat and carbon dynamics. Using the validated surrogate model, we then conduct multi-objective optimization using the genetic algorithm to optimize urban design scenarios for desirable urban mitigation effects. While the use of urban greenery is found effective in mitigating both urban heat and carbon emissions, there is manifest trade-offs among ameliorating diverse urban environmental indicators. Numéro de notice : A2022-244 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE/URBANISME Nature : Article DOI : 10.1016/j.compenvurbsys.2022.101796 Date de publication en ligne : 18/03/2022 En ligne : https://doi.org/10.1016/j.compenvurbsys.2022.101796 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100184 [article]

The promising combination of a remote sensing approach and landscape connectivity modelling at a fine scale in urban planning / Elie Morin in Ecological indicators, vol 139 (June 2022)  

Public [article]  inEcological indicators > vol 139 (June 2022) . - n° 108930 Titre : The promising combination of a remote sensing approach and landscape connectivity modelling at a fine scale in urban planning Type de document : Article/Communication Auteurs : Elie Morin, Auteur ; Pierre-Alexis Herrault, Auteur ; Yvonnick Guinard, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 108930 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse d'image orientée objet [Termes IGN] analyse du paysage [Termes IGN] BD Topo [Termes IGN] carte d'occupation du sol [Termes IGN] carte de la végétation [Termes IGN] classification orientée objet [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] connexité (topologie) [Termes IGN] corridor biologique [Termes IGN] extraction de la végétation [Termes IGN] extraction de traits caractéristiques [Termes IGN] indicateur environnemental [Termes IGN] milieu urbain [Termes IGN] Niort [Termes IGN] planification urbaine [Termes IGN] Poitiers [Termes IGN] segmentation d'image [Termes IGN] Vienne (86) Résumé : (auteur) Urban landscapes are rapid changing ecosystems with diverse urban forms that impede the movement of organisms. Therefore, designing and modelling ecological networks to identify biodiversity reservoirs and their corridors are crucial aspects of land management in terms of population persistence and survival. However, the land cover/use maps used for landscape connectivity modelling can lack information in such a highly complex environment. In this context, remote sensing approaches are gaining interest for the development of accurate land cover/use maps. We tested the efficiency of an object-based classification using open-source projects and free images to identify vegetation strata at a very fine scale and evaluated its contribution to landscape connectivity modelling. We compared different spatial and thematic resolutions from existing databases and object-based image analyses in three French cities. Our results suggested that this remote sensing approach produced reliable land cover maps to differentiate artificial areas, tree vegetation and herbaceous vegetation. Land cover maps enhanced with the remote sensing products substantially changed the structural connectivity indices, showing an improvement up to four times the proportion of herbaceous and tree vegetation. In addition, functional connectivity indices evaluated for several forest species were mainly impacted for medium dispersers in quantitative (metrics) and qualitative (corridors) estimations. Thus, the combination of this reproductible remote sensing approach and landscape connectivity modelling at a very fine scale provides new insights into the characterisation of ecological networks for conservation planning. Numéro de notice : A2022-368 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE/URBANISME Nature : Article DOI : 10.1016/j.ecolind.2022.108930 Date de publication en ligne : 04/05/2022 En ligne : https://doi.org/10.1016/j.ecolind.2022.108930 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100592 [article]

Urban land cover/use mapping and change detection analysis using multi-temporal Landsat OLI with Lidar-DEM and derived TPI / Clement E. Akumu in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 4 (April 2022)  

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Exploring the relationship between the 2D/3D architectural morphology and urban land surface temperature based on a boosted regression tree: A case study of Beijing, China / Zhen Li in Sustainable Cities and Society, vol 78 (March 2022)  

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A new method for evaluation of the positional error of low-cost devices based on GNSS integrity for transportation applications / Luciano Aparecido Barbosa in Boletim de Ciências Geodésicas, vol 28 n° 1 ([01/03/2022])  

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Using street view images to identify road noise barriers with ensemble classification model and geospatial analysis / Kai Zhang in Sustainable Cities and Society, vol 78 (March 2022)  

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A method of vision aided GNSS positioning using semantic information in complex urban environment / Rui Zhai in Remote sensing, vol 14 n° 4 (February-2 2022)  

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Mapping abundance distributions of allergenic tree species in urbanized landscapes: A nation-wide study for Belgium using forest inventory and citizen science data / Sébastien Dujardin in Landscape and Urban Planning, vol 218 (February 2022)  

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Representing vector geographic information as a tensor for deep learning based map generalisation / Azelle Courtial (2022)  

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Vegetation index and dynamics / Eusebio Cano Carmona (2022)  

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Application of a hand-held LiDAR scanner for the urban cadastral detail survey in digitized cadastral area of Taiwan urban city / Shih-Hong Chio in Remote sensing, vol 13 n° 24 (December-2 2021)  

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Review of spectral indices for urban remote sensing / Akib Javed in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 7 (July 2021)  

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