Centre de documentation
scientifique

Estimating storm damage with the help of low-altitude photographs and different sampling designs and estimators / Pekka Hyvönen in Silva fennica, vol 52 n° 3 ([01/08/2018])  

Public [article]  inSilva fennica > vol 52 n° 3 [01/08/2018] Titre : Estimating storm damage with the help of low-altitude photographs and different sampling designs and estimators Type de document : Article/Communication Auteurs : Pekka Hyvönen, Auteur ; Jaakko Heinonen, Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse diachronique [Termes IGN] dommage matériel [Termes IGN] estimateur [Termes IGN] Finlande [Termes IGN] forêt [Termes IGN] image aérienne [Termes IGN] inventaire forestier étranger (données) [Termes IGN] modèle de simulation [Termes IGN] plan de vol Mots-clés libres : Théorème central limite Résumé : (Auteur) Climate change has been estimated to increase the risk of storm damage in forests in Finland. There is a growing need for methods to obtain information on the extent and severity of storm damage after a storm occurrence. The first objective of this study was to test whether digital photographs taken from aircrafts flying at low-altitude can be utilized in locating storm-damaged areas and estimating the need for harvesting of wind-thrown trees. The second objective was to test the performance of selected estimators. Depending on distances between flight lines, plots on lines and the used estimator, the relative standard errors of storm area estimates varied between 7.7 and 48.7%. For the area for harvesting and volume of wind-thrown trees, the relative standard errors of estimates varied between 16.8 and 167.3%. Using forest area information from Multisource National Forest Inventory data improved the accuracy of the estimates. However, performance of a simple random sampling estimator and ratio estimator were quite similar. Lindeberg’s method for variance estimation based on adjacent lines was sensitive to line directions in relation to possible trends in storm-damaged area locations. Our results showed that the tested method could be used in estimating storm-damaged area provided that the network of flight lines and photographs on lines are sufficiently dense. The developed model for simulations can be utilized also with forthcoming storms as model’s parameters can be freely adjusted to meet, e.g., the intensity and extent of the storm. Numéro de notice : A2018-508 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14214/sf.7710 Date de publication en ligne : 05/06/2018 En ligne : https://doi.org/10.14214/sf.7710 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91189 [article]

Combining machine-learning topic models and spatiotemporal analysis of social media data for disaster footprint and damage assessment / Bernd Resch in Cartography and Geographic Information Science, Vol 45 n° 4 (July 2018)  

Public [article]  inCartography and Geographic Information Science > Vol 45 n° 4 (July 2018) . - pp 362 - 376 Titre : Combining machine-learning topic models and spatiotemporal analysis of social media data for disaster footprint and damage assessment Type de document : Article/Communication Auteurs : Bernd Resch, Auteur ; Florian Usländer, Auteur ; Clemens Havas, Auteur Année de publication : 2018 Article en page(s) : pp 362 - 376 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse spatio-temporelle [Termes IGN] apprentissage automatique [Termes IGN] carte thématique [Termes IGN] catastrophe naturelle [Termes IGN] dommage matériel [Termes IGN] données issues des réseaux sociaux [Termes IGN] empreinte [Termes IGN] gestion de crise Résumé : (Auteur) Current disaster management procedures to cope with human and economic losses and to manage a disaster’s aftermath suffer from a number of shortcomings like high temporal lags or limited temporal and spatial resolution. This paper presents an approach to analyze social media posts to assess the footprint of and the damage caused by natural disasters through combining machine-learning techniques (Latent Dirichlet Allocation) for semantic information extraction with spatial and temporal analysis (local spatial autocorrelation) for hot spot detection. Our results demonstrate that earthquake footprints can be reliably and accurately identified in our use case. More, a number of relevant semantic topics can be automatically identified without a priori knowledge, revealing clearly differing temporal and spatial signatures. Furthermore, we are able to generate a damage map that indicates where significant losses have occurred. The validation of our results using statistical measures, complemented by the official earthquake footprint by US Geological Survey and the results of the HAZUS loss model, shows that our approach produces valid and reliable outputs. Thus, our approach may improve current disaster management procedures through generating a new and unseen information layer in near real time. Numéro de notice : A2018-136 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2017.1356242 Date de publication en ligne : 03/08/2017 En ligne : https://doi.org/10.1080/15230406.2017.1356242 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89678 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
032-2018041	RAB	Revue	Centre de documentation	En réserve L003	Disponible

A spatio-temporal scenario model for emergency decision / Cheng Liu in Geoinformatica, vol 22 n° 2 (April 2018)  

Public [article]  inGeoinformatica > vol 22 n° 2 (April 2018) . - pp 411 - 433 Titre : A spatio-temporal scenario model for emergency decision Type de document : Article/Communication Auteurs : Cheng Liu, Auteur ; Jing Qian, Auteur ; Danhuai Guo, Auteur ; Yi Liu, Auteur Année de publication : 2018 Article en page(s) : pp 411 - 433 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] cadre conceptuel [Termes IGN] catastrophe naturelle [Termes IGN] dommage matériel [Termes IGN] données spatiotemporelles [Termes IGN] modèle conceptuel de données [Termes IGN] outil d'aide à la décision [Termes IGN] relation topologique [Termes IGN] représentation [Termes IGN] secours d'urgence Résumé : (Auteur) A structural and quantitative representation of disaster status contributes to efficient emergency decision-making, for this purpose, a representation model for disaster status is developed in this paper, called spatio-temporal scenario model (short for STSM model). Concept of the term `scenario' is discussed at first. Then, based on the concept, STSM model is proposed and introduced in detail. It contains two components: developing scenario connotation and developing spatio-temporal framework. Scenario connotation is to develop representation of disaster status of each object, consisting of object representation and damage representation. Spatio-temporal framework is to develop representation of evolution of disaster status, consisting of representation of spatial relation, temporal relation, natural environment and emergency response. Finally, an example is provided to show the effectiveness of STSM model. Advantages of the developed model lie in four aspects: flexibility in describing dynamic disaster status; universal representation of disaster status contributing to similarity assessment; helping in evaluating emergency severity with the quantitative representation of disaster status. Moreover, it helps decision-makers obtain a more comprehensive representation for disaster evolution in a certain time space. Numéro de notice : A2018-368 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10707-017-0313-2 Date de publication en ligne : 20/12/2017 En ligne : https://doi.org/10.1007/s10707-017-0313-2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90733 [article]

Contextual classification using photometry and elevation data for damage detection after an earthquake event / Ewelina Rupnik in European journal of remote sensing, vol 51 n° 1 (2018)  

Public [article]  inEuropean journal of remote sensing > vol 51 n° 1 (2018) . - pp 543 - 557 Titre : Contextual classification using photometry and elevation data for damage detection after an earthquake event Type de document : Article/Communication Auteurs : Ewelina Rupnik , Auteur ; Francesco Nex, Auteur ; Isabella Toschi, Auteur ; Fabio Remondino, Auteur Année de publication : 2018 Projets : 3-projet - voir note / Article en page(s) : pp 543 - 557 Note générale : bibliographie This work was supported by RAPIDMAP, a CONCERT-Japan project, i.e. a European Union (EU) funded project in the International Cooperation Activities under the Capacities Programme the 7th Framework Programme for Research and Technology Development. https://cordis.europa.eu/project/id/266604/reporting Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] cartographie d'urgence [Termes IGN] chaîne de traitement [Termes IGN] champ aléatoire conditionnel [Termes IGN] classification contextuelle [Termes IGN] classification dirigée [Termes IGN] classification non dirigée [Termes IGN] détection de changement [Termes IGN] dommage matériel [Termes IGN] image aérienne [Termes IGN] modèle numérique de surface [Termes IGN] orthoimage [Termes IGN] photométrie [Termes IGN] prise en compte du contexte [Termes IGN] zone urbaine Résumé : (auteur) This research presents a processing workflow to automatically find damaged building areas in an urban context. The input data requirements are high-resolution multi-view images, acquired from airborne platform. The elevations are derived from a dense surface model generated with photogrammetric methods. With the principal objective of rapid response in emergency situations, two different processing roadmaps are proposed, semi-supervised and unsupervised. Both of them follow a two-step workflow of building detection and building health estimation. Optionally, cadastral layers may serve as a-priori knowledge on building location. The semi-supervised approach involves a data training step, while the unsupervised approach exploits the similarities and dissimilarities between sets of features calculated over the detected buildings. The change detection task is formulated as a classification task defined over a conditional random field. The algorithms are evaluated using two datasets (Vexcel and Midas cameras) and results are compared with ground truth data and specific metrics. Numéro de notice : A2018-664 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/22797254.2018.1458584 Date de publication en ligne : 16/05/2018 En ligne : https://doi.org/10.1080/22797254.2018.1458584 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94250 [article]

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)  

Public [article]  inForestry, an international journal of forest research > vol 91 n° 1 (January 2018) . - pp 27 - 37 Titre : Assessing forest windthrow damage using single-date, post-event airborne laser scanning data Type de document : Article/Communication Auteurs : Gherardo Chirici, Auteur ; Francesca Bottalico, Auteur ; Francesca Giannetti, Auteur ; Barbara Del Perugia, Auteur ; Davide Travaglini, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 27 - 37 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] arbre urbain [Termes IGN] dommage matériel [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] peuplement forestier [Termes IGN] tempête [Termes IGN] Toscane (Italie) [Termes IGN] zone urbaine Résumé : (Auteur) One of many possible climate change effects in temperate areas is the increase of frequency and severity of windstorms; thus, fast and cost efficient new methods are needed to evaluate wind-induced damages in forests. We present a method for assessing windstorm damages in forest landscapes based on a two-stage sampling strategy using single-date, post-event airborne laser scanning (ALS) data. ALS data are used for delineating damaged forest stands and for an initial evaluation of the volume of fallen trees. The total volume of fallen trees is then estimated using a two-stage model-assisted approach, where variables from ALS are used as auxiliary information in the difference estimator. In the first stage, a sample of the delineated forest stands is selected, and in the second stage the within-stand damages are estimated by means of line intercept sampling (LIS). The proposed method produces maps of windthrown areas, estimates of forest damages in terms of the total volume of fallen trees, and the uncertainty of the estimates. A case study is presented for a large windstorm that struck the Tuscany Region of Italy the night of the 4th and the 5th of March 2015 and caused extensive damages to trees in both forest and urban areas. The pure field-based estimates from LIS and the ALS-based estimates of stand-level fallen wood were very similar. Our positive results demonstrate the utility of the single-date approach for a fast assessment of windthrow damages in forest stands which is especially useful when pre-event ALS data are not available. Numéro de notice : A2018-630 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1093/forestry/cpx029 Date de publication en ligne : 06/07/2017 En ligne : https://doi.org/10.1093/forestry/cpx029 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93215 [article]

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

Permalink

Semiautomatic detection and classification of materials in historic buildings with low-cost photogrammetric equipment / Javier Sanchez in Journal of Cultural Heritage, vol 25 (May - June 2017)  

Permalink

Urban damage level mapping based on scattering mechanism investigation using fully polarimetric SAR Data for the 3.11 East Japan earthquake / Si-Wei Chen in IEEE Transactions on geoscience and remote sensing, vol 54 n° 12 (December 2016)  

Permalink

Assessing the ecosystem service flood protection of a riparian forest by applying a cascade approach / Nina-Christin Barth in Ecosystem Services, vol 21 Part A (October 2016)  

Permalink

Extreme events and climate change: the post-disaster dynamics of forest fires and forest storms in Sweden / Rolf Lidskog in Scandinavian journal of forest research, vol 31 n° 2 (March 2016)  

Permalink

Gestion de collecte des déchets post-inondation / Oumayma Kaabi (2016)

Permalink

The ill wind that blew some good / Miroslav Holubec in GEO: Geoconnexion international, vol 15 n° 1 (January 2016)

Permalink

Une infrastructure atlantique pour la recherche sur l'adaptation des forêts au changement climatique / Christophe Orazio in Forêt entreprise, n° 223 (juillet-août 2015)

Permalink

Developing predictive models of wind damage in Austrian forests / Ferenc Pasztor in Annals of Forest Science, vol 72 n° 3 (May 2015)  

Permalink

Laser scanning-based detection of morphological changes of a historical building occurred during a seismic sequence: Method and case study / Arianna Pesci in International Journal of Geomatics and Geosciences, vol 5 n° 3 (February 2015) 

Permalink