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GIS models for vulnerability of coastal erosion assessment in a tropical protected area / Luís Russo Vieira in ISPRS International journal of geo-information, vol 10 n° 9 (September 2021)  

Public [article]  inISPRS International journal of geo-information > vol 10 n° 9 (September 2021) . - n° 598 Titre : GIS models for vulnerability of coastal erosion assessment in a tropical protected area Type de document : Article/Communication Auteurs : Luís Russo Vieira, Auteur ; José Guilherme Vieira, Auteur ; Isabel Marques da silva, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 598 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] Brésil [Termes IGN] érosion côtière [Termes IGN] géoréférencement [Termes IGN] mangrove [Termes IGN] modèle de simulation [Termes IGN] système d'information géographique [Termes IGN] vulnérabilité [Termes IGN] zone intertropicale Résumé : (auteur) Coastal erosion is considered a major worldwide challenge. The vulnerability assessment of coastal areas, in relation to climate change, is a key topic of worldwide increasing interest. The integration of methodologies supported by Remote Sensing, Geographical Information Systems (GIS) and in situ monitoring has allowed a viable identification of vulnerable areas to erosion. In the present study, a model was proposed to the assessment of the estuarine system of Cananéia-Iguape (Brazil), by applying the evaluation and prediction of vulnerability models for the conservation and preservation of mangroves. Approximately 1221 Km2 were classified, with 16% of the total presenting high and very high vulnerability to erosion. Other relevant aspects, were the identification and georeferencing sites that showed strong evidence of erosion and, thus, having a huge influence on the final vulnerability scores. The obtained results led to the development of a multidisciplinary approach through the application of a prediction and description model that resulted from the adaptation of the study system from a set of implemented models for coastal regions, in order to contribute to the erosion vulnerability assessment in the mangroves ecosystems (and associated localities, municipalities and communities). Numéro de notice : A2021-685 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10090598 date de publication en ligne : 10/09/2021 En ligne : https://doi.org/10.3390/ijgi10090598 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98411 [article]

A hybrid data model for dynamic GIS: application to marine geomorphological dynamics / Younes Hamdani in International journal of geographical information science IJGIS, vol 35 n° 8 (August 2021)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 8 (August 2021) . - pp 1475 - 1499 Titre : A hybrid data model for dynamic GIS: application to marine geomorphological dynamics Type de document : Article/Communication Auteurs : Younes Hamdani, Auteur ; Rémy Thibaud, Auteur ; Christophe Claramunt, Auteur Année de publication : 2021 Article en page(s) : pp 1475 - 1499 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] base de données spatiotemporelles [Termes IGN] érosion [Termes IGN] interface utilisateur [Termes IGN] modèle conceptuel de données localisées [Termes IGN] modèle dynamique [Termes IGN] PostGIS [Termes IGN] PostgreSQL [Termes IGN] relief sous-marin [Termes IGN] SIG dynamique Résumé : (auteur) The search for the most appropriate GIS data model to integrate, manipulate and analyse spatio-temporal data raises several research questions about the conceptualisation of geographic spaces. Although there is now a general consensus that many environmental phenomena require field and object conceptualisations to provide a comprehensive GIS representation, there is still a need for better integration of these dual representations of space within a formal spatio-temporal database. The research presented in this paper introduces a hybrid and formal dual data model for the representation of spatio-temporal data. The whole approach has been fully implemented in PostgreSQL and its spatial extension PostGIS, where the SQL language is extended by a series of data type constructions and manipulation functions to support hybrid queries. The potential of the approach is illustrated by an application to underwater geomorphological dynamics oriented towards the monitoring of the evolution of seabed changes. A series of performance and scalability experiments are also reported to demonstrate the computational performance of the model. Numéro de notice : A2021-547 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1829628 date de publication en ligne : 12/10/2020 En ligne : https://doi.org/10.1080/13658816.2020.1829628 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98059 [article]

DEM- and GIS-based analysis of soil erosion depth using machine learning / Kieu Anh Nguyen in ISPRS International journal of geo-information, vol 10 n° 7 (July 2021)  

Public [article]  inISPRS International journal of geo-information > vol 10 n° 7 (July 2021) . - n° 452 Titre : DEM- and GIS-based analysis of soil erosion depth using machine learning Type de document : Article/Communication Auteurs : Kieu Anh Nguyen, Auteur ; Walter Chen, Auteur Année de publication : 2021 Article en page(s) : n° 452 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] apprentissage automatique [Termes IGN] bassin hydrographique [Termes IGN] carte de profondeur [Termes IGN] classification par forêts aléatoires [Termes IGN] érosion [Termes IGN] Extreme Gradient Machine [Termes IGN] modèle de simulation [Termes IGN] modèle numérique de surface [Termes IGN] morphométrie [Termes IGN] système d'information géographique Résumé : (auteur) Soil erosion is a form of land degradation. It is the process of moving surface soil with the action of external forces such as wind or water. Tillage also causes soil erosion. As outlined by the United Nations Sustainable Development Goal (UN SDG) #15, it is a global challenge to “combat desertification, and halt and reverse land degradation and halt biodiversity loss.” In order to advance this goal, we studied and modeled the soil erosion depth of a typical watershed in Taiwan using 26 morphometric factors derived from a digital elevation model (DEM) and 10 environmental factors. Feature selection was performed using the Boruta algorithm to determine 15 factors with confirmed importance and one tentative factor. Then, machine learning models, including the random forest (RF) and gradient boosting machine (GBM), were used to create prediction models validated by erosion pin measurements. The results show that GBM, coupled with 15 important factors (confirmed), achieved the best result in the context of root mean square error (RMSE) and Nash–Sutcliffe efficiency (NSE). Finally, we present the maps of soil erosion depth using the two machine learning models. The maps are useful for conservation planning and mitigating future soil erosion. Numéro de notice : A2021-551 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10070452 date de publication en ligne : 01/07/2021 En ligne : https://doi.org/10.3390/ijgi10070452 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98074 [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)  

Public [article]  inJournal of forest science > vol 67 n° 6 (July 2021) . - pp 258 - 271 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 [article]

Analysing the impact of climate change on hydrological ecosystem services in Laguna del Sauce (Uruguay) using the SWAT model and remote sensing data / Celina Aznarez in Remote sensing, vol 13 n°10 (May 2021)  

Public [article]  inRemote sensing > vol 13 n°10 (May 2021) . - n° 2014 Titre : Analysing the impact of climate change on hydrological ecosystem services in Laguna del Sauce (Uruguay) using the SWAT model and remote sensing data Type de document : Article/Communication Auteurs : Celina Aznarez, Auteur ; Patricia Jimeno-Sáez, Auteur ; Adrián López-Ballesteros, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 2014 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] algue [Termes IGN] bassin hydrographique [Termes IGN] changement climatique [Termes IGN] eau potable [Termes IGN] érosion [Termes IGN] gestion de l'eau [Termes IGN] image satellite [Termes IGN] modèle hydrographique [Termes IGN] ressources en eau [Termes IGN] risque naturel [Termes IGN] service écosystémique [Termes IGN] Uruguay Résumé : (auteur) Assessing how climate change will affect hydrological ecosystem services (HES) provision is necessary for long-term planning and requires local comprehensive climate information. In this study, we used SWAT to evaluate the impacts on four HES, natural hazard protection, erosion control regulation and water supply and flow regulation for the Laguna del Sauce catchment in Uruguay. We used downscaled CMIP-5 global climate models for Representative Concentration Pathways (RCP) 2.6, 4.5 and 8.5 projections. We calibrated and validated our SWAT model for the periods 2005–2009 and 2010–2013 based on remote sensed ET data. Monthly NSE and R2 values for calibration and validation were 0.74, 0.64 and 0.79, 0.84, respectively. Our results suggest that climate change will likely negatively affect the water resources of the Laguna del Sauce catchment, especially in the RCP 8.5 scenario. In all RCP scenarios, the catchment is likely to experience a wetting trend, higher temperatures, seasonality shifts and an increase in extreme precipitation events, particularly in frequency and magnitude. This will likely affect water quality provision through runoff and sediment yield inputs, reducing the erosion control HES and likely aggravating eutrophication. Although the amount of water will increase, changes to the hydrological cycle might jeopardize the stability of freshwater supplies and HES on which many people in the south-eastern region of Uruguay depend. Despite streamflow monitoring capacities need to be enhanced to reduce the uncertainty of model results, our findings provide valuable insights for water resources planning in the study area. Hence, water management and monitoring capacities need to be enhanced to reduce the potential negative climate change impacts on HES. The methodological approach presented here, based on satellite ET data can be replicated and adapted to any other place in the world since we employed open-access software and remote sensing data for all the phases of hydrological modelling and HES provision assessment. Numéro de notice : A2021-472 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs13102014 date de publication en ligne : 20/05/2021 En ligne : https://doi.org/10.3390/rs13102014 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97820 [article]

Multicriterial method of AHP analysis for the identification of coastal vulnerability regarding the rise of sea level: case study in Ilha Grande Bay, Rio de Janeiro, Brazil / Julia Caon Araujo in Natural Hazards, vol 107 n° 1 (May 2021)  

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Evolution of the beaches in the regional Park of Salinas and Arenales of San Pedro del Pinatar (Southeast of Spain) (1899–2019) / Daniel Ibarra-Marinas in ISPRS International journal of geo-information, vol 10 n° 4 (April 2021)  

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Assessing land use–land cover change and soil erosion potential using a combined approach through remote sensing, RUSLE and random forest algorithm / Siddhartho Shekhar Paul in Geocarto international, vol 36 n° 4 ([01/03/2021])  

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Structure-from-motion-derived digital surface models from historical aerial photographs: A new 3D application for coastal dune monitoring / Edoardo Grottoli in Remote sensing, vol 13 n° 1 (January 2021)  

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The use of deep machine learning for the automated selection of remote sensing data for the determination of areas of arable land degradation processes distribution / Dimitri I. Rukhovitch in Remote sensing, vol 13 n° 1 (January 2021)  

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Analysis of shoreline changes in Vishakhapatnam coastal tract of Andhra Pradesh, India: an application of digital shoreline analysis system (DSAS) / Mirza Razi Imam Baig in Annals of GIS, vol 26 n° 4 (December 2020)  

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Displacement monitoring of upper Atbara dam based on time series InSAR / Q.Q. Wang in Survey review, vol 52 n° 375 (November 2020)  

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Soil erosion assessment using RUSLE model and its validation by FR probability model / Amiya Gayen in Geocarto international, vol 35 n° 15 ([01/11/2020])  

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Use of visible and near-infrared reflectance spectroscopy models to determine soil erodibility factor (K) in an ecologically restored watershed / Qinghu Jiang in Remote sensing, vol 12 n° 18 (September-2 2020)  

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Arctic tsunamis threaten coastal landscapes and communities – survey of Karrat Isfjord 2017 tsunami effects in Nuugaatsiaq, western Greenland / Mateusz C. Strzelecki in Natural Hazards and Earth System Sciences, vol 20 n° 9 (September 2020)  

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