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Flood depth mapping in street photos with image processing and deep neural networks / Bahareh Alizadeh Kharazi in Computers, Environment and Urban Systems, vol 88 (July 2021)
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Titre : Flood depth mapping in street photos with image processing and deep neural networks Type de document : Article/Communication Auteurs : Bahareh Alizadeh Kharazi, Auteur ; Amir H. Behzadan, Auteur Année de publication : 2021 Article en page(s) : n° 101628 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] apprentissage profond
[Termes IGN] Canada
[Termes IGN] centre urbain
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] crue
[Termes IGN] détection de contours
[Termes IGN] Etats-Unis
[Termes IGN] image Streetview
[Termes IGN] inondation
[Termes IGN] profondeur
[Termes IGN] signalisation routière
[Termes IGN] système d'aide à la décision
[Termes IGN] traitement d'image
[Termes IGN] transformation de Hough
[Termes IGN] zone urbaineRésumé : (auteur) Many parts of the world experience severe episodes of flooding every year. In addition to the high cost of mitigation and damage to property, floods make roads impassable and hamper community evacuation, movement of goods and services, and rescue missions. Knowing the depth of floodwater is critical to the success of response and recovery operations that follow. However, flood mapping especially in urban areas using traditional methods such as remote sensing and digital elevation models (DEMs) yields large errors due to reshaped surface topography and microtopographic variations combined with vegetation bias. This paper presents a deep neural network approach to detect submerged stop signs in photos taken from flooded roads and intersections, coupled with Canny edge detection and probabilistic Hough transform to calculate pole length and estimate floodwater depth. Additionally, a tilt correction technique is implemented to address the problem of sideways tilt in visual analysis of submerged stop signs. An in-house dataset, named BluPix 2020.1 consisting of paired web-mined photos of submerged stop signs across 10 FEMA regions (for U.S. locations) and Canada is used to evaluate the models. Overall, pole length is estimated with an RMSE of 17.43 and 8.61 in. in pre- and post-flood photos, respectively, leading to a mean absolute error of 12.63 in. in floodwater depth estimation. Findings of this research are sought to equip jurisdictions, local governments, and citizens in flood-prone regions with a simple, reliable, and scalable solution that can provide (near-) real time estimation of floodwater depth in their surroundings. Numéro de notice : A2021-358 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2021.101628 Date de publication en ligne : 01/04/2021 En ligne : https://doi.org/10.1016/j.compenvurbsys.2021.101628 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97620
in Computers, Environment and Urban Systems > vol 88 (July 2021) . - n° 101628[article]Prevention of erosion in mountain basins: A spatial-based tool to support payments for forest ecosystem services / Sandro Sacchelli in Journal of forest science, vol 67 n° 6 (July 2021)
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Titre : Prevention of erosion in mountain basins: A spatial-based tool to support payments for forest ecosystem services Type de document : Article/Communication Auteurs : Sandro Sacchelli, Auteur ; Costanza Borghi, Auteur ; Gianluca Grilli, Auteur Année de publication : 2021 Article en page(s) : pp 258 - 271 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] bassin hydrographique
[Termes IGN] érosion hydrique
[Termes IGN] géomorphologie locale
[Termes IGN] gestion forestière
[Termes IGN] réseau neuronal artificiel
[Termes IGN] ruissellement
[Termes IGN] service écosystémique
[Termes IGN] système d'aide à la décision
[Termes IGN] Toscane (Italie)Résumé : (auteur) This paper presents a spatial-based decision support system (DSS) to assist public and private forest managers in the analysis of potential feasibility in payments for forest ecosystem services (PES) for the prevention of soil erosion. The model quantifies the maximum willingness to pay (WTP) of managers of a reservoir to prevent soil loss. The minimum willingness to accept (WTA) of forest owners for the activation of a private market is also computed. The comparison of WTP and WTA identifies the forest area where PES are ideally feasible with additional potential for compensation to enable the schemes. The DSS highlights forest idiosyncrasies as well as local socio-economic and geomorphological characteristics influencing PES suitability at a geographic level. The potential applications and future improvements of the model are also discussed. Numéro de notice : A2021-450 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE Nature : Article DOI : 10.17221/5/2021-JFS Date de publication en ligne : 01/06/2021 En ligne : https://doi.org/10.17221/5/2021-JFS Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97867
in Journal of forest science > vol 67 n° 6 (July 2021) . - pp 258 - 271[article]Mitigating urban visual pollution through a multistakeholder spatial decision support system to optimize locational potential of billboards / Khydija Wakil in ISPRS International journal of geo-information, vol 10 n° 2 (February 2021)
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Titre : Mitigating urban visual pollution through a multistakeholder spatial decision support system to optimize locational potential of billboards Type de document : Article/Communication Auteurs : Khydija Wakil, Auteur ; Ali Tahir, Auteur ; Muhammad Hussnain, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 60 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] analyse spatiale
[Termes IGN] Pakistan
[Termes IGN] pollution
[Termes IGN] processus de hiérarchisation analytique floue
[Termes IGN] publicité
[Termes IGN] système d'aide à la décision
[Termes IGN] urbanismeRésumé : (auteur) Urban visual pollution is increasingly affecting the built-up areas of the rapidly urbanizing planet. Outdoor advertisements are the key visual pollution objects affecting the visual pollution index and revenue generation potential of a place. Current practices of uninformed and uncontrolled outdoor advertising (especially billboards) impairs effective control of visual pollution in developing countries. Improving this can result in over 20% reduction of visual pollution. This article presents a spatial decision support system (SDSS) to facilitate all the stakeholders (development control authorities, advertisers, billboard owners, and the public) in balancing the optimal positioning of billboards under the governing regulations. In terms of its technical implementation, SDSS is based on well-known geospatial open source technologies and uses an analytical hierarchy process AHP-inspired approach in spatial decision-making. It can help users through its category-specific user interface to identify potential sites to position new billboards and the selection of boards from existing sites based on a wide variety of characteristics. The observations of all stakeholders have been recorded through panel feedback to assess the system’s initial effectiveness. The proposed system has been found functional in identifying hot spots for the focused management and exploration of the best suitable sites for new billboards. So, it helps the advertising agencies, urban authorities, and city councils in better planning and management of existing billboard locations to optimize revenue and improve urban aesthetics. The system can be replicated in other countries irrespective of spatial boundaries by incorporating jurisdictional rules and regulations. Numéro de notice : A2021-156 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10020060 Date de publication en ligne : 01/02/2021 En ligne : https://doi.org/10.3390/ijgi10020060 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97062
in ISPRS International journal of geo-information > vol 10 n° 2 (February 2021) . - n° 60[article]
Titre : Artificial intelligence : Latest advances, new paradigms and novel applications Type de document : Monographie Auteurs : Eneko Osaba, Auteur ; Esther Villar-Rodriguez, Auteur ; Jesus L. Lobo, Auteur ; et al., Auteur Editeur : London [UK] : IntechOpen Année de publication : 2021 Importance : 158 p. Format : 16 x 23 cm ISBN/ISSN/EAN : 978-1-83962-389-9 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Intelligence artificielle
[Termes IGN] apprentissage profond
[Termes IGN] exploration de données
[Termes IGN] innovation
[Termes IGN] modèle orienté agent
[Termes IGN] organisme international
[Termes IGN] reconnaissance de formes
[Termes IGN] règlement
[Termes IGN] réseau neuronal artificiel
[Termes IGN] Spark
[Termes IGN] système d'informationRésumé : (éditeur) Artificial Intelligence (AI) is widely known as a knowledge field that aims to make computers, robots, or products that mimic the way humans think. In the current scientific community, AI is an intensively studied area composed of multiple branches. Historically, machine learning and optimization are two of the most studied fronts thanks to the development of novel and challenging research topics such as transfer optimization, swarm robotics, and drift detection and adaptation to evolving conditions in real-time. This book collects radically new theoretical insights, reporting recent developments and evincing innovative applications regarding AI methods in all fields of knowledge. It also presents works focused on new paradigms and novel branches of AI science. Note de contenu : 1- Introductory chapter: Artificial intelligence - Latest advances, new paradigms and novel applications
2- Big data framework using Spark architecture for dose optimization based on deep learning in medical imaging
3- Novelty detection methodology based on self-organizing maps for power quality monitoring
4- AI-powered workforce management and its future in India
5- Agent based load balancing in grid computing
6- A food recommender based on frequent sets of food mining using image recognition
7- The prospects for creating instruments for the coordination of activities of international organizations in the regulation of artificial intelligence
8- Artificial intelligence assisted innovation
9- Quest for I (intelligence) in AI (artificial intelligence): A non-elusive attemptNuméro de notice : 28633 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE Nature : Recueil / ouvrage collectif DOI : 10.5772/intechopen.87770 En ligne : https://doi.org/10.5772/intechopen.87770 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99636
Titre : Resilient urban futures Type de document : Monographie Auteurs : Zoé A. Hamstead, Éditeur scientifique ; David M. Iwaniec, Éditeur scientifique ; Timon McPhearson, Éditeur scientifique ; Marta Berbés-Blázquez, Éditeur scientifique ; Elizabeth M. Cook, Éditeur scientifique ; Tischa A. Muñoz-Erickson, Éditeur scientifique Editeur : Springer Nature Année de publication : 2021 Importance : 190 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-3-030-63131-4 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Urbanisme
[Termes IGN] aménagement durable
[Termes IGN] cartographie des risques
[Termes IGN] chaleur
[Termes IGN] changement climatique
[Termes IGN] inondation
[Termes IGN] planification urbaine
[Termes IGN] prospective
[Termes IGN] résilience écologique
[Termes IGN] système de gestion de connaissances
[Termes IGN] urbanisation
[Termes IGN] ville durableRésumé : (éditeur) This open access book addresses the way in which urban and urbanizing regions profoundly impact and are impacted by climate change. The editors and authors show why cities must wage simultaneous battles to curb global climate change trends while adapting and transforming to address local climate impacts. This book addresses how cities develop anticipatory and long-range planning capacities for more resilient futures, earnest collaboration across disciplines, and radical reconfigurations of the power regimes that have institutionalized the disenfranchisement of minority groups. Although planning processes consider visions for the future, the editors highlight a more ambitious long-term positive visioning approach that accounts for unpredictability, system dynamics and equity in decision-making. This volume brings the science of urban transformation together with practices of professionals who govern and manage our social, ecological and technological systems to design processes by which cities may achieve resilient urban futures in the face of climate change. Note de contenu : 1- A framework for resilient urban futures
2- How we got here: Producing climate inequity and vulnerability to urban weather extremes
3- Social, ecological, and technological strategies for climate adaptation
4- Mapping vulnerability to weather extremes: Heat and flood assessment approaches
5- Producing and communicating flood risk: A knowledge system analysis of FEMA flood maps in New York City
6- Positive futures
7- Setting the stage for co-production
8- Assessing future resilience, equity, and sustainability in scenario planning
9- Modeling urban futures: Data-driven scenarios of climate change and vulnerability in cities
10- Visualizing urban social–ecological–technological systems
11- Anticipatory resilience bringing back the future into urban planning and knowledge systems
12- A vision for resilient urban futures
13- Correction to: Modeling urban futures: Data-driven scenarios of climate change and vulnerability in citiesNuméro de notice : 28659 Affiliation des auteurs : non IGN Thématique : URBANISME Nature : Recueil / ouvrage collectif DOI : 10.1007/978-3-030-63131-4 En ligne : https://doi.org/10.1007/978-3-030-63131-4 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99816 Interoperable information model for geovisualization and interaction in XR environments / Daeil Seo in International journal of geographical information science IJGIS, vol 34 n° 7 (July 2020)
PermalinkA web-based spatial decision support system for monitoring the risk of water contamination in private wells / Yu Lan in Annals of GIS, vol 26 n° 3 (July 2020)
PermalinkPermalinkPermalinkTowards improving knowledge capitalization system for sport events legacy / Malika Grim-Yefsah (2019)
PermalinkOPTEER, un dispositif de connaissance et d’analyse territoriale par et pour les acteurs de la transition énergétique / Marie-Hélène de Sède-Marceau in Revue internationale de géomatique, vol 28 n° 1 (janvier - mars 2018)
PermalinkMEMORAe : un système d'information support d'un éco-système apprenant / Marie-Hélène Abel in Ingénierie des systèmes d'information, ISI : Revue des sciences et technologies de l'information, RSTI, vol 22 n° 6 (novembre - décembre 2017)
PermalinkA cyber-enabled spatial decision support system to inventory mangroves in Mozambique: coupling scientific workflows and cloud computing / Wenwu Tang in International journal of geographical information science IJGIS, vol 31 n° 5-6 (May-June 2017)
PermalinkVers un modèle unifié de données entreposées et de données ouvertes liées. Concepts et expérimentations / Franck Ravat in Ingénierie des systèmes d'information, ISI : Revue des sciences et technologies de l'information, RSTI, vol 22 n° 2 (mars - avril 2017)
Permalinkvol 21 n° 5 - 6 - septembre - décembre 2016 - Le web de données : publication, liage et capitalisation (Bulletin de Ingénierie des systèmes d'information, ISI : Revue des sciences et technologies de l'information, RSTI) / Fayçal Hamdi
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