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Near-real time forecasting and change detection for an open ecosystem with complex natural dynamics / Jasper A. Slingsby in ISPRS Journal of photogrammetry and remote sensing, vol 166 (August 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 166 (August 2020) . - pp 15 - 25 Titre : Near-real time forecasting and change detection for an open ecosystem with complex natural dynamics Type de document : Article/Communication Auteurs : Jasper A. Slingsby, Auteur ; Glenn R. Moncrieff, Auteur ; Adam M. Wilson, Auteur Année de publication : 2020 Article en page(s) : pp 15 - 25 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] approche hiérarchique [Termes descripteurs IGN] biodiversité [Termes descripteurs IGN] classification bayesienne [Termes descripteurs IGN] détection de changement [Termes descripteurs IGN] écosystème [Termes descripteurs IGN] incendie [Termes descripteurs IGN] internet interactif [Termes descripteurs IGN] Le Cap [Termes descripteurs IGN] milieu naturel [Termes descripteurs IGN] modèle dynamique [Termes descripteurs IGN] Normalized Difference Vegetation Index [Termes descripteurs IGN] surveillance de la végétation [Termes descripteurs IGN] surveillance écologique Résumé : (auteur) Managing fire, water, biodiversity and carbon stocks can greatly benefit from early warning of changes in the state of vegetation. While near-real time tools to detect forest change based on satellite remote sensing exist, these ecosystems have relatively stable natural vegetation dynamics. Open (i.e. non-forest) ecosystems like grasslands, savannas and shrublands are more challenging as they show complex natural dynamics due to factors such as fire, postfire recovery, greater contribution of bare soil to observed vegetation indices, as well as high sensitivity to rainfall and strong seasonality. Tools to aid the management of open ecosystems are desperately required as they dominate much of the globe and harbour substantial biodiversity and carbon. We present an innovative approach that overcomes the difficulties posed by open ecosystems by using a spatio-temporal hierarchical Bayesian model that uses data on climate, topography, soils and fire history to generate ecological forecasts of the expected land surface signal under natural conditions. This allows us to monitor and detect abrupt or gradual changes in the state of an ecosystem in near-real time by identifying areas where the observed vegetation signal has deviated from the expected natural variation. We apply our approach to a case study from the hyperdiverse fire-dependent African shrubland, the fynbos of the Cape Floristic Region, a Global Biodiversity Hotspot and UNESCO World Heritage Site that faces a number of threats to vegetation health and ecosystem function. The case study demonstrates that our approach is useful for identifying a range of change agents such as fire, alien plant species invasions, drought, pathogen outbreaks and clearing of vegetation. We describe and provide our full workflow, including an interactive web application. Our approach is highly versatile, allowing us to collect data on the impacts of change agents for research in ecology and earth system science, and to predict aspects of ecosystem structure and function such as biomass, fire return interval and the influence of vegetation on hydrology Numéro de notice : A2020-349 Thématique : BIODIVERSITE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.05.017 date de publication en ligne : 05/06/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.05.017 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95231 [article]

Size dependency of variables influencing fire occurrence in Mediterranean forests of Eastern Spain / Marina Peris-Llopis in European Journal of Forest Research, vol 139 n°4 (August 2020)  

Public [article]  inEuropean Journal of Forest Research > vol 139 n°4 (August 2020) . - pp 525 - 537 Titre : Size dependency of variables influencing fire occurrence in Mediterranean forests of Eastern Spain Type de document : Article/Communication Auteurs : Marina Peris-Llopis, Auteur ; José Ramon Gonzalez-Olabarria, Auteur ; Blas Mola-Yudego, Auteur Année de publication : 2020 Article en page(s) : pp 525 - 537 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] altitude [Termes descripteurs IGN] cartographie numérique [Termes descripteurs IGN] combinaison linéaire ponderée [Termes descripteurs IGN] forêt méditerranéenne [Termes descripteurs IGN] fréquence [Termes descripteurs IGN] incendie de forêt [Termes descripteurs IGN] pente [Termes descripteurs IGN] Pinus (genre) [Termes descripteurs IGN] plan de prévention des risques [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Fires are among the most damaging disturbances to forests in the Mediterranean area. The study analyses the occurrence and characteristics of forest fires in Eastern Spain (1993–2015) to identify key variables related to burnt forest land, differentiating fires according to their burnt area. Data are retrieved from digital cartography, the Spanish Forest Map and data concerning fires. Based on previous research, the variables included are altitude, slope, aspect, fuel, species, population and road density. The fires are classified in small (5–50 ha), medium (50–500 ha) and large (> 500 ha). Four models are considered to explain the proportion of burnt area based on weighted generalized linear models: a general model and one per size class. The results highlight the different relations of similar variables with fires according to the size. When a single model is considered to explain all area burnt, the relationships are mainly driven by large fires. The larger area is burnt on forests with pine, bushes and small trees, whereas smaller fires tend to occur on lower altitude, low slope, high population and road densities. There are large differences in the variables according to the fire sizes, especially for the presence of pine (negative in the medium fires model but positive for the large fires model) and Pasture (which only explains the small fires). The models can be applied to analyse occurrence by fire size in Mediterranean areas, and the results can help elaborate fire prevention strategies and land-planning schemes. Numéro de notice : A2020-423 Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10342-020-01265-9 date de publication en ligne : 10/02/2020 En ligne : https://doi.org/10.1007/s10342-020-01265-9 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95486 [article]

Predicting displacement of bridge based on CEEMDAN-KELM model using GNSS monitoring data / Qian Fan in Journal of applied geodesy, vol 14 n° 3 (July 2020)  

Public [article]  inJournal of applied geodesy > vol 14 n° 3 (July 2020) . - pp 253 – 261 Titre : Predicting displacement of bridge based on CEEMDAN-KELM model using GNSS monitoring data Type de document : Article/Communication Auteurs : Qian Fan, Auteur ; Xiaolin Meng, Auteur ; Dinh Tung Nguyen, Auteur ; Yilin Xie, Auteur ; Jiayong Yu, Auteur Année de publication : 2020 Article en page(s) : pp 253 – 261 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Topographie moderne [Termes descripteurs IGN] apprentissage automatique [Termes descripteurs IGN] combinaison linéaire [Termes descripteurs IGN] données GNSS [Termes descripteurs IGN] méthode fondée sur le noyau [Termes descripteurs IGN] pont [Termes descripteurs IGN] prévention des risques [Termes descripteurs IGN] série temporelle [Termes descripteurs IGN] surveillance d'ouvrage Résumé : (auteur) Bridges are critical to economic and social development of a country. In order to ensure the safe operation of bridges, it is of great significance to accurately predict displacement of monitoring points from bridge Structural Health System (SHM). In the paper, a CEEMDAN-KELM model is proposed to improve the accuracy of displacement prediction of bridge. Firstly, the original displacement monitoring time series of bridge is accurately and effectively decomposed into multiple components called intrinsic mode functions (IMFs) and one residual component using a method named complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN). Then, these components are forecasted by establishing appropriate kernel extreme learning machine (KELM) prediction models, respectively. At last, the prediction results of all components including residual component are summed as the final prediction results. A case study using global navigation satellite system (GNSS) monitoring data is used to illustrate the feasibility and validity of the proposed model. Practical results show that prediction accuracy using CEEMDAN-KELM model is superior to BP neural network model, EMD-ELM model and EMD-KELM model in terms of the same monitoring data. Numéro de notice : A2020-396 Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1515/jag-2019-0057 date de publication en ligne : 27/03/2020 En ligne : https://doi.org/10.1515/jag-2019-0057 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95431 [article]

Analysis of dam deformation with robust weight functions / Berkant Konakoglu in Geodetski vestnik, vol 64 n° 2 (June - August 2020)  

Public [article]  inGeodetski vestnik > vol 64 n° 2 (June - August 2020) . - 16 p. Titre : Analysis of dam deformation with robust weight functions Type de document : Article/Communication Auteurs : Berkant Konakoglu, Auteur Année de publication : 2020 Article en page(s) : 16 p. Note générale : bibliographie Langues : Anglais (eng) Slovène (slv) Descripteur : [Vedettes matières IGN] Topographie moderne [Termes descripteurs IGN] barrage [Termes descripteurs IGN] déformation d'édifice [Termes descripteurs IGN] données GNSS [Termes descripteurs IGN] méthode robuste [Termes descripteurs IGN] surveillance d'ouvrage [Termes descripteurs IGN] surveillance géologique [Termes descripteurs IGN] Turquie Résumé : (auteur)Civil engineering structures (e.g., bridges, dams) are exposed to deformation under the influence of various factors such as water level changes, landslides, tectonic phenomena, etc. These deformations must be periodically monitored. Various deformation analysis approaches have been developed to describe the behaviour of a structure or natural process. The most significant task in deformation analysis is to correctly classify whether the points are stable or unstable. In this study, various robust weight functions for determination of stable/unstable points were applied to the Deriner Dam using GNSS (Global Navigation Satellite System) data measured over four different periods. The robust weight functions examined included the Andrews, Beaton−Tukey, Cauchy, Danish, Fair, German−McClure, Hampel, Huber, L1, and L1−L2. Test results were evaluated, and the performances of the different deformation analysis methods were determined. It was concluded that the horizontal deformations based on GNSS data determined by these robust weight functions were in good agreement with each other, except for the L1−L2. The results of all approaches were also compared with the results of the θ2–Criteria method. According to the results obtained, although the θ2–Criteria and the robust methods yielded nearly similar results, the results of the θ2–Criteria method were thought to be more reliable. Numéro de notice : A2020-404 Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : 10.15292/geodetski-vestnik.2020.02.198-213 date de publication en ligne : 12/06/2020 En ligne : http://dx.doi.org/10.15292/geodetski-vestnik.2020.02.198-213 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95457 [article]

Data-driven evidential belief function (EBF) model in exploring landslide susceptibility zones for the Darjeeling Himalaya, India / Subrata Mondal in Geocarto international, Vol 35 n° 8 ([01/06/2020])  

Public [article]  inGeocarto international > Vol 35 n° 8 [01/06/2020] . - pp 818 - 856 Titre : Data-driven evidential belief function (EBF) model in exploring landslide susceptibility zones for the Darjeeling Himalaya, India Type de document : Article/Communication Auteurs : Subrata Mondal, Auteur ; Sujit Mandal, Auteur Année de publication : 2020 Article en page(s) : pp 818 - 856 Note générale : bibbliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes descripteurs IGN] action anthropique [Termes descripteurs IGN] cartographie des risques [Termes descripteurs IGN] effondrement de terrain [Termes descripteurs IGN] géomorphologie locale [Termes descripteurs IGN] Himalaya [Termes descripteurs IGN] lithologie [Termes descripteurs IGN] Normalized Difference Vegetation Index [Termes descripteurs IGN] surveillance hydrologique [Termes descripteurs IGN] théorie de Dempster-Shafer [Termes descripteurs IGN] vulnérabilité Résumé : (auteur) In the present study, data-driven evidential belief function model (belief function) was employed to generate landslides susceptibility index map of Darjeeling Himalaya considering 15 landslide causative factors, which grouped into six categories, i.e. geomorphological factors (elevation, aspect, slope, curvature), lithological factors (geology, soil, lineament density, distance to lineament), hydrologic factors (drainage density, distance to drainage, stream power index, topographic wetted index), triggering factor (rainfall), protective factor (normalized differential vegetation index) and anthropogenic factor (land use and land cover). Total 2079 landslide locations were mapped and randomly divided it into training datasets (70% landslide locations) and validation datasets (30% landslide locations). The resultant susceptibility map was divided into five different susceptibility zones i.e. very low, low, moderate, high and very high which covered 5.60%, 25.65%, 34.47%, 24.67% and 9.61% area respectively of the Darjeeling Himalaya. Receiver operating characteristics curve suggested that 80.20% prediction accuracy of the prepared map whereas frequency ratio plot indicated towards the ideal landslides susceptibility index map. Numéro de notice : A2020-274 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10106049.2018.1544288 date de publication en ligne : 13/02/2019 En ligne : https://doi.org/10.1080/10106049.2018.1544288 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95059 [article]

Improved optical image matching time series inversion approach for monitoring dune migration in North Sinai Sand Sea: Algorithm procedure, application, and validation / Eslam Ali in ISPRS Journal of photogrammetry and remote sensing, vol 164 (June 2020)  

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Fusing adjacent-track InSAR datasets to densify the temporal resolution of time-series 3-D displacement estimation over mining areas with a prior deformation model and a generalized weighting least-squares method / Yuedong Wang in Journal of geodesy, vol 94 n° 5 (May 2020)  

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Incorporating Sentinel-1 SAR imagery with the MODIS MCD64A1 burned area product to improve burn date estimates and reduce burn date uncertainty in wildland fire mapping / Kristofer Lasko in Geocarto international, vol 35 n° 6 ([01/05/2020])  

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Tephra mass eruption rate from ground-based X-band and L-band microwave radars during the November 23, 2013, Etna Paroxysm / Frank S. Marzano in IEEE Transactions on geoscience and remote sensing, vol 58 n° 5 (May 2020)  

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Using GIS for disease mapping and clustering in Jeddah, Saudi Arabia / Abdulkader Murad in ISPRS International journal of geo-information, vol 9 n° 5 (May 2020)  

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Visualizing when, where, and how fires happen in U.S. parks and protected areas / Nicole C. Inglis in ISPRS International journal of geo-information, vol 9 n° 5 (May 2020)  

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A Fusion Approach for Water Area Classification Using Visible, Near Infrared and Synthetic Aperture Radar for South Asian Conditions / Shahryar K. Ahmad in IEEE Transactions on geoscience and remote sensing, vol 58 n° 4 (April 2020)  

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Monitoring of landslide activity at the Sirobagarh landslide, Uttarakhand, India, using LiDAR, SAR interferometry and geodetic surveys / Ashutosh Tiwari in Geocarto international, vol 35 n° 5 ([01/04/2020])  

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Assessing the shape accuracy of coarse resolution burned area identifications / Michael L. Humber in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)  

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A LiDAR–optical data fusion approach for identifying and measuring small stream impoundments and dams / Benjamin Swan in Transactions in GIS, Vol 24 n° 1 (February 2020)  

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