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Forest cover mapping based on a combination of aerial images and Sentinel-2 satellite data compared to National Forest Inventory data / Selina Ganz in Forests, vol 11 n° 12 (December 2020)
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Titre : Forest cover mapping based on a combination of aerial images and Sentinel-2 satellite data compared to National Forest Inventory data Type de document : Article/Communication Auteurs : Selina Ganz, Auteur ; Petra Adler, Auteur ; Gerald Kändler, Auteur Année de publication : 2020 Article en page(s) : n° 1322 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse comparative
[Termes IGN] Bade-Wurtemberg (Allemagne)
[Termes IGN] carte forestière
[Termes IGN] image aérienne
[Termes IGN] image Sentinel-MSI
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] modèle numérique de surface
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Research Highlights: This study developed the first remote sensing-based forest cover map of Baden-Württemberg, Germany, in a very high level of detail.
Background and Objectives: As available global or pan-European forest maps have a low level of detail and the forest definition is not considered, administrative data are often oversimplified or out of date. Consequently, there is an important need for spatio-temporally explicit forest maps. The main objective of the present study was to generate a forest cover map of Baden-Württemberg, taking the German forest definition into account. Furthermore, we compared the results to NFI data; incongruences were categorized and quantified. Materials and
Methods: We used a multisensory approach involving both aerial images and Sentinel-2 data. The applied methods are almost completely automated and therefore suitable for area-wide forest mapping.
Results: According to our results, approximately 37.12% of the state is covered by forest, which agrees very well with the results of the NFI report (37.26% ± 0.44%). We showed that the forest cover map could be derived by aerial images and Sentinel-2 data including various data acquisition conditions and settings. Comparisons between the forest cover map and 34,429 NFI plots resulted in a spatial agreement of 95.21% overall. We identified four reasons for incongruences: (a) edge effects at forest borders (2.08%), (b) different forest definitions since NFI does not specify minimum tree height (2.04%), (c) land cover does not match land use (0.66%) and (d) errors in the forest cover layer (0.01%).
Conclusions: The introduced approach is a valuable technique for mapping forest cover in a high level of detail. The developed forest cover map is frequently updated and thus can be used for monitoring purposes and for assisting a wide range of forest science, biodiversity or climate change-related studies.Numéro de notice : A2020-845 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.3390/f11121322 Date de publication en ligne : 12/12/2020 En ligne : https://doi.org/10.3390/f11121322 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98633
in Forests > vol 11 n° 12 (December 2020) . - n° 1322[article]Geomorphological analysis of the San Domino Island (Tremiti Islands, Southern Adriatic Sea). Results from the 2019 Geomorphological Field Camp of the MSc in Geological Science and Technology (University of Chieti-Pescara) / Marcello Buccolini in Journal of maps, vol 16 n° 3 ([01/12/2020])
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Titre : Geomorphological analysis of the San Domino Island (Tremiti Islands, Southern Adriatic Sea). Results from the 2019 Geomorphological Field Camp of the MSc in Geological Science and Technology (University of Chieti-Pescara) Type de document : Article/Communication Auteurs : Marcello Buccolini, Auteur ; Cristiano Carabella, Auteur ; Giorgio Paglia, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 10 - 18 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie thématique
[Termes IGN] 1:5.000
[Termes IGN] analyse des risques
[Termes IGN] archipel
[Termes IGN] cartographie géologique
[Termes IGN] données de terrain
[Termes IGN] géologie locale
[Termes IGN] géomorphologie locale
[Termes IGN] Italie
[Termes IGN] morphométrieRésumé : (auteur) The 2019 Geomorphological Field Camp at San Domino Island (Tremiti Islands, Southern Adriatic Sea) is the result of geological and geomorphological field work activities carried out by a group of students attending the Geomorphological field mapping course of the Master’s Degree in Geological Science and Technology (University of Chieti-Pescara). The main map (1:5000 scale) was obtained through an integrated approach that incorporates morphometric analysis, geological and geomorphological field mapping, and geomorphological profiles drawing. Activities were carried out by all students, divided into six working groups of three to four persons each. The field camp and field work activities made it possible to produce a detailed thematic map, as a scientific tool to depict the San Domino Island landscape, and to outline some geomorphological issues in terms of possible constraints to landscape evolution, geomorphological processes distribution, and natural hazard assessment. Numéro de notice : A2020-816 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/17445647.2020.1831979 Date de publication en ligne : 16/11/2020 En ligne : https://doi.org/10.1080/17445647.2020.1831979 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96982
in Journal of maps > vol 16 n° 3 [01/12/2020] . - pp 10 - 18[article]Infrastructure of the spatial information in the European Community (INSPIRE) based on examples of Italy and Poland / Marek Ogryzek in ISPRS International journal of geo-information, vol 9 n° 12 (December 2020)
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Titre : Infrastructure of the spatial information in the European Community (INSPIRE) based on examples of Italy and Poland Type de document : Article/Communication Auteurs : Marek Ogryzek, Auteur ; Eufemia Tarantino, Auteur ; Krzysztof Rząsa, Auteur Année de publication : 2020 Article en page(s) : n° 755 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Infrastructure de données
[Termes IGN] directive européenne
[Termes IGN] géoportail
[Termes IGN] INSPIRE
[Termes IGN] Italie
[Termes IGN] norme ISO
[Termes IGN] Pologne
[Termes IGN] WebSIGRésumé : (auteur) Binding and planned community regulations regarding INSPIRE and other documents resulting from work on INSPIRE have forced the member countries to implement new or updated regulations. The purpose of creating the spatial information infrastructure was to unify the exchange of geographical data at the national and international levels, create transparent and favorable conditions for the use of geographical data, facilitate decision-making and develop business activity, and, as a consequence, facilitate the creation of the INSPIRE geoportal by the European Research Center (JRC) of the European Commission, which aims be the central hub of the European spatial information infrastructure. Land management systems use layers from geoportals and are also a data source because their task is to develop sustainable space development. The article presents the rules for implementing EU directives in Poland and Italy at various levels of detail and examines access to data and spatial information infrastructure. A comparative analysis of geoportals was performed in terms of the functionality and availability of free data (types of data) at national and local levels in terms of verification of compliance with the Ubiquitous Public Access Context Information Model (UPA) defined by the International Organization for Standardization (ISO) 19100. National geoportals (Polish Geoportal 2 and the Italian-Geoportale Nazionale) and Municipal Spatial Information Systems from the cities of Olsztyn and Bari were compared. Numéro de notice : A2021-809 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9120755 Date de publication en ligne : 16/12/2020 En ligne : https://doi.org/10.3390/ijgi9120755 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96954
in ISPRS International journal of geo-information > vol 9 n° 12 (December 2020) . - n° 755[article]Large-scale stochastic flood hazard analysis applied to the Po River / A. Curran in Natural Hazards, vol 104 n° 3 (December 2020)
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Titre : Large-scale stochastic flood hazard analysis applied to the Po River Type de document : Article/Communication Auteurs : A. Curran, Auteur ; Karin De Bruijn, Auteur ; Alessio Domeneghetti, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 2027 – 2049 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse des risques
[Termes IGN] digue
[Termes IGN] inondation
[Termes IGN] modèle hydrographique
[Termes IGN] modèle stochastique
[Termes IGN] Pô (plaine)
[Termes IGN] prévention des risques
[Termes IGN] probabilité
[Termes IGN] surveillance hydrologiqueRésumé : (auteur) Reliable hazard analysis is crucial in the flood risk management of river basins. For the floodplains of large, developed rivers, flood hazard analysis often needs to account for the complex hydrology of multiple tributaries and the potential failure of dikes. Estimating this hazard using deterministic methods ignores two major aspects of large-scale risk analysis: the spatial–temporal variability of extreme events caused by tributaries, and the uncertainty of dike breach development. Innovative stochastic methods are here developed to account for these uncertainties and are applied to the Po River in Italy. The effects of using these stochastic methods are compared against deterministic equivalents, and the methods are combined to demonstrate applications for an overall stochastic hazard analysis. The results show these uncertainties can impact extreme event water levels by more than 2 m at certain channel locations, and also affect inundation and breaching patterns. The combined hazard analysis allows for probability distributions of flood hazard and dike failure to be developed, which can be used to assess future flood risk management measures. Numéro de notice : A2020-735 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s11069-020-04260-w Date de publication en ligne : 08/09/2020 En ligne : https://doi.org/10.1007/s11069-020-04260-w Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96350
in Natural Hazards > vol 104 n° 3 (December 2020) . - pp 2027 – 2049[article]Learning from urban form to predict building heights / Nikola Milojevic-Dupont in Plos one, vol 15 n° 12 (December 2020)
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Titre : Learning from urban form to predict building heights Type de document : Article/Communication Auteurs : Nikola Milojevic-Dupont, Auteur ; Nicolai Hans, Auteur ; Lynn H. Kaack, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : n° 0242010 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] Allemagne
[Termes IGN] apprentissage automatique
[Termes IGN] base de connaissances
[Termes IGN] données localisées des bénévoles
[Termes IGN] France (administrative)
[Termes IGN] hauteur du bâti
[Termes IGN] Italie
[Termes IGN] morphologie urbaine
[Termes IGN] OpenStreetMap
[Termes IGN] Pays-Bas
[Termes IGN] villeRésumé : (auteur) Understanding cities as complex systems, sustainable urban planning depends on reliable high-resolution data, for example of the building stock to upscale region-wide retrofit policies. For some cities and regions, these data exist in detailed 3D models based on real-world measurements. However, they are still expensive to build and maintain, a significant challenge, especially for small and medium-sized cities that are home to the majority of the European population. New methods are needed to estimate relevant building stock characteristics reliably and cost-effectively. Here, we present a machine learning based method for predicting building heights, which is based only on open-access geospatial data on urban form, such as building footprints and street networks. The method allows to predict building heights for regions where no dedicated 3D models exist currently. We train our model using building data from four European countries (France, Italy, the Netherlands, and Germany) and find that the morphology of the urban fabric surrounding a given building is highly predictive of the height of the building. A test on the German state of Brandenburg shows that our model predicts building heights with an average error well below the typical floor height (about 2.5 m), without having access to training data from Germany. Furthermore, we show that even a small amount of local height data obtained by citizens substantially improves the prediction accuracy. Our results illustrate the possibility of predicting missing data on urban infrastructure; they also underline the value of open government data and volunteered geographic information for scientific applications, such as contextual but scalable strategies to mitigate climate change. Numéro de notice : A2020-830 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.1371/journal.pone.0242010 Date de publication en ligne : 09/12/2020 En ligne : https://doi.org/10.1371/journal.pone.0242010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97658
in Plos one > vol 15 n° 12 (December 2020) . - n° 0242010[article]Legal aspects of registration the time of cadastral data creation or modification / Joanna Reczyńska in Reports on geodesy and geoinformatics, vol 110 n° 1 (December 2020)
PermalinkMapping forest tree species in high resolution UAV-based RGB-imagery by means of convolutional neural networks / Felix Schiefer in ISPRS Journal of photogrammetry and remote sensing, vol 170 (December 2020)
PermalinkMultistrategy ensemble regression for mapping of built-up density and height with Sentinel-2 data / Christian Geiss in ISPRS Journal of photogrammetry and remote sensing, vol 170 (December 2020)
PermalinkSemantic‐based urban growth prediction / Marvin Mc Cutchan in Transactions in GIS, Vol 24 n° 6 (December 2020)
PermalinkStand-level mortality models for Nordic boreal forests / Jouni Siipilehto in Silva fennica, vol 54 n° 5 (December 2020)
PermalinkThe crown condition of Norway spruce and occurrence of symptoms caused by Armillaria spp. in mixed stands / Petr Čermák in Journal of forest science, vol 66 n° 12 (December 2020)
PermalinkThe 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, vol 77 n° 4 (December 2020)
PermalinkTree mortality in the dynamics and management of uneven-aged Norway spruce stands in southern Finland / Sauli Valkonen in European Journal of Forest Research, vol 139 n° 6 (December 2020)
PermalinkVisualization of 3D property data and assessment of the impact of rendering attributes / Stefan Seipel in Journal of Geovisualization and Spatial Analysis, vol 4 n° 2 (December 2020)
PermalinkAdaptation de l'irrigation au changement climatique dans l'Union européenne : les actions engagées par les États membres pour économiser l'eau / Claire Serra-Wittling in Sciences, eaux & territoires, n° 34 (novembre 2020)
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