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The utility of fused airborne laser scanning and multispectral data for improved wind damage risk assessment over a managed forest landscape in Finland / Ranjith Gopalakrishnan in Annals of Forest Science [en ligne], vol 77 n° 4 (December 2020)  

Public [article]  inAnnals of Forest Science [en ligne] > vol 77 n° 4 (December 2020) . - 18 p. Titre : The utility of fused airborne laser scanning and multispectral data for improved wind damage risk assessment over a managed forest landscape in Finland Type de document : Article/Communication Auteurs : Ranjith Gopalakrishnan, Auteur ; Petteri Packalen, Auteur ; Veli-Pekka Ikonen, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 18 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes descripteurs IGN] cartographie des risques [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] Finlande [Termes descripteurs IGN] forêt boréale [Termes descripteurs IGN] image multibande [Termes descripteurs IGN] modèle de simulation [Termes descripteurs IGN] paysage forestier [Termes descripteurs IGN] risque naturel [Termes descripteurs IGN] tempête [Termes descripteurs IGN] vent [Termes descripteurs IGN] zone à risque Résumé : (auteur) Key message: The potential of airborne laser scanning (ALS) and multispectral remote sensing data to aid in generating improved wind damage risk maps over large forested areas is demonstrated. This article outlines a framework to generate such maps, primarily utilizing the horizontal structural information contained in the ALS data. Validation was done over an area in Eastern Finland that had experienced sporadic wind damage. Context: Wind is the most prominent disturbance element for Finnish forests. Hence, tools are needed to generate wind damage risk maps for large forested areas, and their possible changes under planned silvicultural operations. Aims: (1) How effective are ALS-based forest variables (e.g. distance to upwind forest stand edge, gap size) for identifying high wind damage risk areas? (2) Can robust estimates of predicted critical wind speeds for uprooting of trees be derived from these variables? (3) Can these critical wind speed estimates be improved using wind multipliers, which factor in topography and terrain roughness effects? Methods: We first outline a framework to generate several wind damage risk–related parameters from remote sensing data (ALS + multispectral). Then, we assess if such parameters have predictive power. That is, whether they help differentiate between damaged and background points. This verification exercise used 42 wind damaged points spread over a large area. Results: Parameters derived from remote sensing data are shown to have predictive power. Risk models based on critical wind speeds are not that robust, but show potential for improvement. Conclusion: Overall, this work described a framework to get several wind risk–related parameters from remote sensing data. These parameters are shown to have potential in generating wind damage risk maps over large forested areas. Numéro de notice : A2020-629 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-020-00992-8 date de publication en ligne : 09/10/2020 En ligne : https://doi.org/10.1007/s13595-020-00992-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96045 [article]

Mining spatiotemporal association patterns from complex geographic phenomena / Zhanjun He in International journal of geographical information science IJGIS, vol 34 n° 6 (June 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 6 (June 2020) . - pp 1162 -1 187 Titre : Mining spatiotemporal association patterns from complex geographic phenomena Type de document : Article/Communication Auteurs : Zhanjun He, Auteur ; Jiannan Cai, Auteur ; Zhong Xie, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 1162 -1 187 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] approche hiérarchique [Termes descripteurs IGN] Chine [Termes descripteurs IGN] diffusion spatiale [Termes descripteurs IGN] données localisées dynamiques [Termes descripteurs IGN] exploration de données géographiques [Termes descripteurs IGN] interaction spatiale [Termes descripteurs IGN] modèle entité-association [Termes descripteurs IGN] modélisation spatio-temporelle [Termes descripteurs IGN] phénomène géographique [Termes descripteurs IGN] pollution atmosphérique [Termes descripteurs IGN] tempête Résumé : (auteur) Spatiotemporal association pattern mining can discover interesting interdependent relationships among various types of geospatial data. However, existing mining methods for spatiotemporal association patterns usually model geographic phenomena as simple spatiotemporal point events. Therefore, they cannot be applied to complex geographic phenomena, which continuously change their properties, shapes or locations, such as storms and air pollution. The most salient feature of such complex geographic phenomena is the geographic dynamic. To fully reveal dynamic characteristics of complex geographic phenomena and discover their associated factors, this research proposes a novel complex event-based spatiotemporal association pattern mining framework. First, a complex geographic event was hierarchically modeled and represented by a new data structure named directed spatiotemporal routes. Then, sequence mining technique was applied to discover the spatiotemporal spread pattern of the complex geographic events. An adaptive spatiotemporal episode pattern mining algorithm was proposed to discover the candidate driving factors for the occurrence of complex geographic events. Finally, the proposed approach was evaluated by analyzing the air pollution in the region of Beijing-Tianjin-Hebei. The experimental results showed that the proposed approach can well address the geographic dynamic of complex geographic phenomena, such as the spatial spreading pattern and spatiotemporal interaction with candidate driving factors. Numéro de notice : A2020-340 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1566549 date de publication en ligne : 01/02/2019 En ligne : https://doi.org/10.1080/13658816.2019.1566549 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95216 [article]

Real-time mapping of natural disasters using citizen update streams / Iranga Subasinghe in International journal of geographical information science IJGIS, vol 34 n° 2 (February 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 2 (February 2020) . - pp 393 - 421 Titre : Real-time mapping of natural disasters using citizen update streams Type de document : Article/Communication Auteurs : Iranga Subasinghe, Auteur ; Silvia Nittel, Auteur ; Michael Cressey, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 393 - 421 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes descripteurs IGN] approche participative [Termes descripteurs IGN] cartographie collaborative [Termes descripteurs IGN] catastrophe naturelle [Termes descripteurs IGN] classification par réseau neuronal [Termes descripteurs IGN] diagramme de Voronoï [Termes descripteurs IGN] données localisées des bénévoles [Termes descripteurs IGN] effondrement de terrain [Termes descripteurs IGN] incendie [Termes descripteurs IGN] inondation [Termes descripteurs IGN] positionnement cinématique en temps réel [Termes descripteurs IGN] système multi-agents [Termes descripteurs IGN] tempête [Termes descripteurs IGN] temps réel [Termes descripteurs IGN] ville intelligente Résumé : (auteur) Natural disasters such as flooding, wildfires, and mudslides are rare events, but they affect citizens at unpredictable times and the impact on human life can be significant. Citizens located close to events can provide detailed, real-time data streams capturing their event response. Instead of visualizing individual updates, an integrated spatiotemporal map yields ‘big picture’ event information. We investigate the question of whether information from affected citizens is sufficient to generate a map of an unfolding natural disaster. We built the Citizen Disaster Reaction Multi-Agent Simulation (CDR-MAS), a multi-agent system that simulates the reaction of citizens to a natural disaster in an urban region. We proposed an rkNN classification algorithm to aggregate the update streams into a series of colored Voronoi event maps. We simulated the 2018 Montecito Creek mudslide and customized the CDR-MAS with the local environment to systematically generate stream data sets. Our experimental evaluation showed that event mapping based on citizen update streams is significantly influenced by the amount of citizen participation and movement. Compared with a baseline of 100% participation, with 40% citizen participation, the event region was predicted with 40% accuracy, showing that citizen update streams can provide timely information in a smart city. Numéro de notice : A2020-031 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1639185 date de publication en ligne : 15/07/2019 En ligne : https://doi.org/10.1080/13658816.2019.1639185 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94486 [article]

Space, time, and situational awareness in natural hazards: a case study of Hurricane Sandy with social media data / Zheye Wang in Cartography and Geographic Information Science, Vol 46 n° 4 (July 2019)  

Public [article]  inCartography and Geographic Information Science > Vol 46 n° 4 (July 2019) . - pp 334 - 346 Titre : Space, time, and situational awareness in natural hazards: a case study of Hurricane Sandy with social media data Type de document : Article/Communication Auteurs : Zheye Wang, Auteur ; Xinyue Ye, Auteur Année de publication : 2019 Article en page(s) : pp 334 - 346 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Information géographique [Termes descripteurs IGN] catastrophe naturelle [Termes descripteurs IGN] données localisées des bénévoles [Termes descripteurs IGN] espace-temps [Termes descripteurs IGN] gestion de crise [Termes descripteurs IGN] modèle de Markov [Termes descripteurs IGN] modélisation 3D [Termes descripteurs IGN] New York (Etats-Unis ; ville) [Termes descripteurs IGN] outil d'aide à la décision [Termes descripteurs IGN] réseau social [Termes descripteurs IGN] risque naturel [Termes descripteurs IGN] tempête Résumé : (Auteur) Various methods have been developed to investigate the geospatial information, temporal component, and message content in disaster-related social media data to enrich human-centric information for situational awareness. However, few studies have simultaneously analyzed these three dimensions (i.e. space, time, and content). With an attempt to bring a space–time perspective into situational awareness, this study develops a novel approach to integrate space, time, and content dimensions in social media data and enable a space–time analysis of detailed social responses to a natural disaster. Using Markov transition probability matrix and location quotient, we analyzed the Hurricane Sandy tweets in New York City and explored how people’s conversational topics changed across space and over time. Our approach offers potential to facilitate efficient policy/decision-making and rapid response in mitigations of damages caused by natural disasters. Numéro de notice : A2019-201 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2018.1483740 date de publication en ligne : 18/06/2018 En ligne : https://doi.org/10.1080/15230406.2018.1483740 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92657 [article]

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Interpreting effects of multiple, large-scale disturbances using national forest inventory data: A case study of standing dead trees in east Texas, USA / Christopher B. Edgar in Forest ecology and management, vol 437 (1 April 2019)  

Public [article]  inForest ecology and management > vol 437 (1 April 2019) . - pp 27-40 Titre : Interpreting effects of multiple, large-scale disturbances using national forest inventory data: A case study of standing dead trees in east Texas, USA Type de document : Article/Communication Auteurs : Christopher B. Edgar, Auteur ; James A. Westfall, Auteur ; Paul A. Klockow, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 27-40 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] agrégation temporelle [Termes descripteurs IGN] analyse diachronique [Termes descripteurs IGN] arbre mort [Termes descripteurs IGN] catastrophe naturelle [Termes descripteurs IGN] diamètre à hauteur de poitrine [Termes descripteurs IGN] données dendrométriques [Termes descripteurs IGN] échantillonnage [Termes descripteurs IGN] gestion forestière [Termes descripteurs IGN] insecte nuisible [Termes descripteurs IGN] inventaire forestier étranger (données) [Termes descripteurs IGN] jeu de données [Termes descripteurs IGN] maladie phytosanitaire [Termes descripteurs IGN] Pinus (genre) [Termes descripteurs IGN] politique forestière [Termes descripteurs IGN] quercus (genre) [Termes descripteurs IGN] sécheresse [Termes descripteurs IGN] tempête [Termes descripteurs IGN] Texas (Etats-Unis) [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) Understanding the impacts of large-scale disturbances on forest conditions is necessary to support forest management, planning, and policy decision making. National forest inventories (NFIs) are an important information source that provide consistent data encompassing large areas, covering all ownerships, and extending through time. Here we compare how temporal aggregation approaches with NFI data affects estimates of standing dead trees as these respond to extreme disturbance events. East Texas was selected for this study owing to the occurrence of three significant disturbance events in a short span: Hurricane Rita in 2005, Hurricane Ike in 2008, and a historic drought in 2011. Wide-spread tree damage and mortality were reported after each disturbance and estimates of standing dead trees were used as the inventory variable for assessment. In the NFI of the US, the plot network is systematically divided into panels and one panel is measured each year. A measurement cycle is completed when all panels have been measured, which varies between 5 and 10 years depending on the region. Using the standard estimation approach of the US NFI, we computed population estimates using data from the full set of panels (FSP), multiple sets of panels (MSP), and single set of panels (SSP). For estimation, a single plot observation is computed from the most recent measurement of the plot that does not exceed the estimate year. Because one panel is measured per year, FSP and MSP estimates will necessarily consist of plot observations whose measurements were collected over a number of years. The SSP estimate is computed from one panel and thus all the plot observations are based on measurements collected over one year. We found that interpretations of disturbance event impacts varied depending on which sets of estimates were considered. All sets of estimates suggested a large and significant drought impact. However, differences existed among the estimates in the timing and magnitude of the impacts. The FSP estimates showed clear lag bias and smoothing of trends relative to the SSP estimates. MSP estimates were intermediate between FSP and SSP estimates. Differences in Hurricane Rita impacts were also observed between sets of estimates. Evidence of a net impact on standing dead trees following Hurricane Ike was weak among all sets of estimates. Given the potential for lag bias and smoothing, we recommend that SSP and MSP estimates be considered along with FSP estimates in assessments of large-scale disturbance impacts on forest conditions. Numéro de notice : A2019-483 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.foreco.2019.01.027 date de publication en ligne : 28/01/2019 En ligne : https://doi.org/10.1016/j.foreco.2019.01.027 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93659 [article]

Forest conversion from Norway spruce to European beech increases species richness and functional structure of aboveground macrofungal communities / Peggy Heine in Forest ecology and management, vol 432 (15 January 2019)  

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Global observations of ocean surface winds and waves using spaceborne synthetic aperture radar measurements / Huimin Li (2019)  

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Assessing forest windthrow damage using single-date, post-event airborne laser scanning data / Gherardo Chirici in Forestry, an international journal of forest research, vol 91 n° 1 (January 2018)  

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Multifunctional operation and application of GPS / Rustam B. Rustamov (2018)  

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Stand-level wind damage can be assessed using diachronic photogrammetric canopy height models / Jean-Pierre Renaud in Annals of Forest Science [en ligne], vol 74 n° 4 (December 2017)  

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Microtopography and ecology of pit-mound structures in second-growth versus old-growth forests / Audrey Barker Plotkin in Forest ecology and management, vol 404 (15 November 2017)  

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A cloud-enabled automatic disaster analysis system of multi-sourced data streams: An example synthesizing social media, remote sensing and Wikipedia data / Qunying Huang in Computers, Environment and Urban Systems, vol 66 (November 2017)  

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HERA: A dynamic web application for visualizing community exposure to flood hazards based on storm and sea level rise scenarios / Jeanne M. Jones in Computers & geosciences, vol 109 (December 2017)  

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Frequency of extreme Sahelian storms tripled since 1982 in satellite observations / Christopher M. Taylor in Nature letters, vol 544 n° 7651 (27 April 2017)  

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The socio-environmental data explorer (SEDE) : a social media–enhanced decision support system to explore risk perception to hazard events / Eric Shook in Cartography and Geographic Information Science, vol 43 n° 5 (November 2016)  

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