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Evaluation of GNSS-based volunteered geographic information for assessing visitor spatial distribution within protected areas: A case study of the Bavarian Forest National Park, Germany / Laura Horst in Applied Geography, vol 150 (January 2023)
[article]
Titre : Evaluation of GNSS-based volunteered geographic information for assessing visitor spatial distribution within protected areas: A case study of the Bavarian Forest National Park, Germany Type de document : Article/Communication Auteurs : Laura Horst, Auteur ; Karolina Taczanowska, Auteur ; Florian Porst, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 102825 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] aire protégée
[Termes IGN] ArcGIS
[Termes IGN] Bavière (Allemagne)
[Termes IGN] distribution spatiale
[Termes IGN] données GNSS
[Termes IGN] données issues des réseaux sociaux
[Termes IGN] données localisées des bénévoles
[Termes IGN] géodatabase
[Termes IGN] parc naturel national
[Termes IGN] piétonRésumé : (auteur) Systematic monitoring of recreational use in vulnerable ecosystems is crucial to balance human needs and site capacities. Recently, publicly available digital data, including Global Navigation Satellite System-based Volunteered Geographic Information, gained attention as a potential resource depicting visitor movement. However, there is a need to critically assess its reliability for visitor monitoring across countries, regions and available databases. Our research evaluates the usability of GNSS-based VGI-data obtained from three common platforms: GPSies, Outdooractive, and Komoot for assessing the spatial distribution of hikers in the Bavarian Forest National Park. A total sample of 1742 GNSS-tracks uploaded between 2013 and 2018 were compared across data platforms. Additionally, available systematic field counts, carried out between 2013 and 2014 (11 Eco-Counter sensors), were compared to GNSS-based VGI data uploaded within the corresponding period. The comparisons at individual and collective levels (route lengths, kernel density, optimized hotspot analysis along with fishnet-based counts of GNSS-tracks) showed similarities between VGI data platforms. Data obtained from GPSies and Outdooractive displayed a higher correlation with each other than with those obtained from Komoot. Also, for GPSies, there was a significant positive correlation between VGI-data and field count data. Data sample of Outdooractive and Komoot within the specified spatio-temporal frame was too small to compare with available field count data. We highlight the necessity of systematic validation of GNSS-based VGI data resources, being complementary rather than the primary data source in visitor monitoring and recreation planning. Also, systematic long-term visitor monitoring using other methods is crucial to assess the validity of novel data resources, such as GNSS-based VGI. Numéro de notice : A2023-020 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.apgeog.2022.102825 Date de publication en ligne : 25/11/2023 En ligne : https://doi.org/10.1016/j.apgeog.2022.102825 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102220
in Applied Geography > vol 150 (January 2023) . - n° 102825[article]Improving methods to predict aboveground biomass of Pinus sylvestris in urban forest using UFB model, LiDAR and digital hemispherical photography / Ihor Kozak in Urban Forestry & Urban Greening, vol 79 (January 2023)
[article]
Titre : Improving methods to predict aboveground biomass of Pinus sylvestris in urban forest using UFB model, LiDAR and digital hemispherical photography Type de document : Article/Communication Auteurs : Ihor Kozak, Auteur ; Mikhail Popov, Auteur ; Igor Semko, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 127793 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] biomasse aérienne
[Termes IGN] détection d'arbres
[Termes IGN] données lidar
[Termes IGN] forêt urbaine
[Termes IGN] houppier
[Termes IGN] image hémisphérique
[Termes IGN] Leaf Area Index
[Termes IGN] méthode de Monte-Carlo
[Termes IGN] modèle de régression
[Termes IGN] modèle numérique de terrain
[Termes IGN] photographie numérique
[Termes IGN] Pinus sylvestris
[Termes IGN] Pologne
[Termes IGN] semis de points
[Termes IGN] surface terrièreRésumé : (auteur) The article proposes methods for combining Airborne Laser Scanning (ALS) with Digital Hemispherical Photography (DHP) data required by the Urban Forest Biomass (UFB) model to predict the aboveground biomass (AGB) of Scotch pine (Pinus sylvestris L.) in urban forests of Lublin (Poland). The article also demonstrates the potential of ALS and DHP data in urban AGB estimation. ALS and Leaf Area Index (LAI) data were calculated using a voxels-vector approach based on the measurements taken at eight permanent sample plots (PSPs). The research was conducted in 2014 and the prediction was made until 2030. It was found that the determination coefficients (R2) for the Basal Area (BA) of the trees are 0.97, and the BA modeling parameters have a high correlation with those observed in the field (model efficiency (ME) 0.94). 83 % growth trajectory based on the measured BA was appropriately modeled using the UFB model (P > 0.9). The results for AGB show that the degree of fitting and accuracy are greatest for the Monte Carlo (MC) simulation technique based on ALS and DHP data (UBF with ALS and DHP) where R2 = 0.98, RMSE = 2.97 t/ha, MAE = 2.35 t/ha, rRMSE = 1.28 %, which performed better than MC simulation technique without ALS and DHP (UBF without ALS and DHP) where R2 = 0.94, RMSE = 4.58 t/ha, MAE = 3.64 t/ha, rRMSE = 3.29 %. The results indicate that the proposed method based on combining the UFB model, LiDAR and DHP allows us to improve the accuracy of the AGB prediction. Numéro de notice : A2023-023 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.ufug.2022.127793 Date de publication en ligne : 23/11/2022 En ligne : https://doi.org/10.1016/j.ufug.2022.127793 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102246
in Urban Forestry & Urban Greening > vol 79 (January 2023) . - n° 127793[article]A machine learning method for Arctic lakes detection in the permafrost areas of Siberia / Piotr Janiec in European journal of remote sensing, vol 56 n° 1 (2023)
[article]
Titre : A machine learning method for Arctic lakes detection in the permafrost areas of Siberia Type de document : Article/Communication Auteurs : Piotr Janiec, Auteur ; Jakub Nowosad, Auteur ; Sbigniew Zwoliński, Auteur Année de publication : 2023 Article en page(s) : n° 2163923 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage automatique
[Termes IGN] Arctique
[Termes IGN] classification et arbre de régression
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] image Landsat-8
[Termes IGN] lac glaciaire
[Termes IGN] MERIT
[Termes IGN] modèle numérique de surface
[Termes IGN] pergélisol
[Termes IGN] Short Waves InfraRed
[Termes IGN] SibérieRésumé : (auteur) Thermokarst lakes are the main components of the vast Arctic and subarctic landscapes. These lakes can serve as geoindicators of permafrost degradation; therefore, proper lake distribution assessment methods are necessary. In this study, we compared four machine learning methods to improve existing lake detection systems. The northern part of Yakutia was selected as the study area owing to its complex environment. We used data from Landsat 8 and spectral indices to take into account the spectral characteristics of the lakes, and MERIT DEM data to take into account the topography. The lowest accuracy was found for the classification and regression trees (CART) method (overall accuracy = 81%). On the other hand, the random forests (RF) classification provided the best results (overall accuracy = 92%), and only this classification coped well in all problematic areas, such as shaded and humid areas, near steep slopes, burn scars, and rivers. The altitude and bands SWIR1 (Short wave infrared 1), SWIR2 (Short wave infrared 2), and Green were the most important. Spectral indices did not have significant impact on the classification results in the specific conditions of the thermokarst lakes environment. 17,700 lakes were identified with the total area of 271.43 km2. Numéro de notice : A2023-218 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/22797254.2022.2163923 Date de publication en ligne : 19/01/2023 En ligne : https://doi.org/10.1080/22797254.2022.2163923 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103156
in European journal of remote sensing > vol 56 n° 1 (2023) . - n° 2163923[article]Mapping the anthropic occupation of the territory. Tracing dynamics of human settlement from archaeological records and historic cartographies / Marina López Sánchez in Journal of maps, vol 18 n° 1 (January 2023)
[article]
Titre : Mapping the anthropic occupation of the territory. Tracing dynamics of human settlement from archaeological records and historic cartographies Type de document : Article/Communication Auteurs : Marina López Sánchez, Auteur ; Mercedes Linares Gómez Del Pulgar, Auteur ; Antonio Tejedor Cabrera, Auteur Année de publication : 2023 Article en page(s) : pp 916 - 931 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie thématique
[Termes IGN] Andalousie
[Termes IGN] carte ancienne
[Termes IGN] convergence
[Termes IGN] données localisées historiques
[Termes IGN] gestion du patrimoine
[Termes IGN] interconnexion
[Termes IGN] patrimoine culturel
[Termes IGN] paysage
[Termes IGN] site archéologique
[Termes IGN] système d'information géographiqueRésumé : (auteur) The convergence of research on landscape and heritage holds great strategic potential for establishing novel connections between the heritage resources of a territory. This text reflects on the ability of the landscape to situate inherited assets within a framework of spatial coherence in relation to the peri-urban spaces of large cities, heritage areas of great historical depth that have been particularly aggressively exposed to the urban development dynamics of the second half of the twentieth century. In order to address these often forgotten spaces, this text presents a system for heritage management argued from the standpoint of and towards the landscape and based on historical interpretation, cartographic analysis, mapping and digital documentation. Geographic technologies and graphic expression are basic pillars to integrate historical information with the language and resources of the disciplines involved in landscape planning and design, advancing criteria for a forward-looking landscape-based heritage management. Numéro de notice : A2023-053 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/01426397.2021.1921717 Date de publication en ligne : 06/05/2021 En ligne : https://doi.org/10.1080/17445647.2021.2009924 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102385
in Journal of maps > vol 18 n° 1 (January 2023) . - pp 916 - 931[article]
Titre : Metsätilastollinen vuosikirja 2022 Titre original : Finnish statistical yearbook of forestry 2022 Type de document : Rapport Auteurs : Eeva Vaahtera, Éditeur scientifique Editeur : Natural Resources Institute Finland Luke Année de publication : 2023 Importance : 198 p. Langues : Finnois (fin) Anglais (eng) Descripteur : [Termes IGN] Finlande
[Termes IGN] forêt
[Termes IGN] ressources forestières
[Vedettes matières IGN] ForesterieRésumé : (éditeur) The Statistical Yearbook of Forestry compiles key annual statistics on Finland's forests, forestry and forest industry. The book also covers forest biodiversity and conservation. The final chapter presents international forest statistics. The book forms part of Finland's forest statistics system, which, by international standards, is among the best in the world. The most recent statistics in the book mainly cover the year 2021.
The Forest Statistics Yearbook has a long tradition. It has been produced in seven different decades, since the late 1960s. The content of the book has been continuously developed to meet the growing demand for up-to-date information.
The editor-in-chief is Eeva Vaahtera. The book was prepared by an expert editorial team familiar with forest statistics. The editorial team included Irma Kulju, Tuomas Niinistö, Aarre Peltola, Minna Räty, Tiina Sauvula-Seppälä, Jukka Torvelainen and Esa Uotila.Numéro de notice : 17755 Affiliation des auteurs : non IGN Autre URL associée : http://urn.fi/URN:ISBN:978-952-380-584-2 Thématique : FORET Nature : Rapport statistique DOI : sans En ligne : https://jukuri.luke.fi/bitstream/handle/10024/553167/Metsatilastollinen_vuosikir [...] Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103170 Mitigating the risk of wind damage at the forest landscape level by using stand neighbourhood and terrain elevation information in forest planning / Roope Ruotsalainen in Forestry, an international journal of forest research, vol 96 n° 1 (January 2023)PermalinkModern vectorization and alignment of historical maps: An application to Paris Atlas (1789-1950) / Yizi Chen (2023)PermalinkPrecipitation frequency in Med-CORDEX and EURO-CORDEX ensembles from 0.44° to convection-permitting resolution: impact of model resolution and convection representation / Minh Ha-Truong in Climate Dynamics, vol 60 n° inconnu (2023)PermalinkDes relevés sur mesure pour la sentinelle des Pyrénées / Marielle Mayo in Géomètre, n° 2209 (janvier 2023)PermalinkSimplified automatic prediction of the level of damage to similar buildings affected by river flood in a specific area / David Marín-García in Sustainable Cities and Society, vol 88 (January 2023)PermalinkTaller and slenderer trees in Swedish forests according to data from the National Forest Inventory / Alex Appiah Mensah in Forest ecology and management, vol 527 (January-1 2023)PermalinkTree diversity and identity modulate the growth response of thermophilous deciduous forests to climate warming / Giovanni Jacopetti in Oikos, vol 2023 n° inconnu (2023)PermalinkTree height-growth trajectory estimation using uni-temporal UAV laser scanning data and deep learning / Stefano Puliti in Forestry, an international journal of forest research, vol 96 n° 1 (January 2023)PermalinkTree position estimation from TLS data using hough transform and robust least-squares circle fitting / Maja Michałowska in Remote Sensing Applications: Society and Environment, RSASE, vol 29 (January 2023)PermalinkWavelet-like denoising of GNSS data through machine learning. Application to the time series of the Campi Flegrei volcanic area (Southern Italy) / Rolando Carbonari in Geomatics, Natural Hazards and Risk, vol 14 n° 1 (2023)Permalink