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Simulation of land use/land cover changes and urban expansion in Estonia by a hybrid ANN-CA-MCA model and utilizing spectral-textural indices / Najmeh Mozaffaree Pour in Environmental Monitoring and Assessment, vol 194 n° 9 (September 2022)
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Titre : Simulation of land use/land cover changes and urban expansion in Estonia by a hybrid ANN-CA-MCA model and utilizing spectral-textural indices Type de document : Article/Communication Auteurs : Najmeh Mozaffaree Pour, Auteur ; Oleksandr Karasov, Auteur ; Iuliia Burdun, Auteur ; Tõnu Oja, Auteur Année de publication : 2022 Article en page(s) : n° 584 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] automate cellulaire
[Termes IGN] chaîne de Markov
[Termes IGN] croissance urbaine
[Termes IGN] Estonie
[Termes IGN] Google Earth Engine
[Termes IGN] image Landsat-8
[Termes IGN] modèle de simulation
[Termes IGN] occupation du sol
[Termes IGN] réseau neuronal artificielRésumé : (auteur) Over the recent two decades, land use/land cover (LULC) drastically changed in Estonia. Even though the population decreased by 11%, noticeable agricultural and forest land areas were turned into urban land. In this work, we analyzed those LULC changes by mapping the spatial characteristics of LULC and urban expansion in the years 2000–2019 in Estonia. Moreover, using the revealed spatiotemporal transitions of LULC, we simulated LULC and urban expansion for 2030. Landsat 5 and 8 data were used to estimate 147 spectral-textural indices in the Google Earth Engine cloud computing platform. After that, 19 selected indices were used to model LULC changes by applying the hybrid artificial neural network, cellular automata, and Markov chain analysis (ANN-CA-MCA). While determining spectral-textural indices is quite common for LULC classifications, utilization of these continues indices in LULC change detection and examining these indices at the landscape scale is still in infancy. This country-wide modeling approach provided the first comprehensive projection of future LULC utilizing spectral-textural indices. In this work, we utilized the hybrid ANN-CA-MCA model for predicting LULC in Estonia for 2030; we revealed that the predicted changes in LULC from 2019 to 2030 were similar to the observed changes from 2011 to 2019. The predicted change in the area of artificial surfaces was an increased rate of 1.33% to reach 787.04 km2 in total by 2030. Between 2019 and 2030, the other significant changes were the decrease of 34.57 km2 of forest lands and the increase of agricultural lands by 14.90 km2 and wetlands by 9.31 km2. These findings can develop a proper course of action for long-term spatial planning in Estonia. Therefore, a key policy priority should be to plan for the stable care of forest lands to maintain biodiversity. Numéro de notice : A2022-458 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE/URBANISME Nature : Article DOI : 10.1007/s10661-022-10266-7 Date de publication en ligne : 13/07/2022 En ligne : http://dx.doi.org/10.1007/s10661-022-10266-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101258
in Environmental Monitoring and Assessment > vol 194 n° 9 (September 2022) . - n° 584[article]Advancements in underground mine surveys by using SLAM-enabled handheld laser scanners / Artu Ellmann in Survey review, vol 54 n° 385 (July 2022)
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Titre : Advancements in underground mine surveys by using SLAM-enabled handheld laser scanners Type de document : Article/Communication Auteurs : Artu Ellmann, Auteur ; Kaia Kütimets, Auteur ; Sander Varbla, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 363 - 374 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] arpentage
[Termes IGN] carrière souterraine
[Termes IGN] cartographie et localisation simultanées
[Termes IGN] données lidar
[Termes IGN] Estonie
[Termes IGN] géoréférencement
[Termes IGN] industrie minière
[Termes IGN] mine
[Termes IGN] modélisation 3D
[Termes IGN] schiste
[Termes IGN] semis de points
[Termes IGN] système de numérisation mobile
[Termes IGN] télémètre laser terrestreRésumé : (auteur) Applicability of SLAM (simultaneous localization and mapping) technology for mine surveys and subsequent 3D modelling of post-extracted surfaces is assessed. The resulting surface geometry is validated via terrestrial laser scanner (TLS) acquired reference data. Typical discrepancies remained within 2 and 5 cm in horizontal and vertical directions, respectively. Discrepancies between TLS, SLAM-enabled handheld scanner and conventional surveying results are small and fully satisfy the contemporary accuracy requirements, yet evidence that the conventional mine survey results are affected by the subjectivity of the surveyors. The SLAM-enabled laser scanning hence appears to be the most suitable method for underground mining surveys. Numéro de notice : A2022-537 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2021.1944545 Date de publication en ligne : 07/07/2021 En ligne : https://doi.org/10.1080/00396265.2021.1944545 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101093
in Survey review > vol 54 n° 385 (July 2022) . - pp 363 - 374[article]Planning of commercial thinnings using machine learning and airborne Lidar data / Tauri Arumäe in Forests, vol 13 n° 2 (February 2022)
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Titre : Planning of commercial thinnings using machine learning and airborne Lidar data Type de document : Article/Communication Auteurs : Tauri Arumäe, Auteur ; Mait Lang, Auteur ; Allan Sims, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 206 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] apprentissage automatique
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] éclaircie (sylviculture)
[Termes IGN] Estonie
[Termes IGN] gestion forestière
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] modèle linéaire
[Termes IGN] planification
[Termes IGN] semis de pointsRésumé : (auteur) The goal of this study was to predict the need for commercial thinning using airborne lidar data (ALS) with random forest (RF) machine learning algorithm. Two test sites (with areas of 14,750 km2 and 12,630 km2) were used with a total of 1053 forest stands from southwestern Estonia and 951 forest stands from southeastern Estonia. The thinnings were predicted based on the ALS measurements in 2019 and 2017. The two most important ALS metrics for predicting the need for thinning were the 95th height percentile and the canopy cover. The prediction accuracy based on validation stands was 93.5% for southwestern Estonia and 85.7% for southeastern Estonia. For comparison, the general linear model prediction accuracy was less for both test sites—92.1% for southwest and 81.8% for southeast. The selected important predictive ALS metrics differed from those used in the RF algorithm. The cross-validation of the thinning necessity models of southeastern and southwestern Estonia showed a dependence on geographic regions. Numéro de notice : A2022-122 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/f13020206 Date de publication en ligne : 29/01/2022 En ligne : https://doi.org/10.3390/f13020206 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99674
in Forests > vol 13 n° 2 (February 2022) . - n° 206[article]Consolidation of crowd-sourced geo-ragged data for parameterized travel recommendations / Ago Luberg (2021)
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Titre : Consolidation of crowd-sourced geo-ragged data for parameterized travel recommendations Type de document : Thèse/HDR Auteurs : Ago Luberg, Auteur ; Tanel Tammet, Directeur de thèse Editeur : Tallinn [Estonia] : Tallinn University of Technology Année de publication : 2021 Importance : 159 p. Format : 21 x 30 cm Note générale : bibliographie
Dissertation accepted for the defence of the degree of Doctor of Philosophy in Computer ScienceLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] apprentissage automatique
[Termes IGN] base de données
[Termes IGN] conception orientée utilisateur
[Termes IGN] données localisées des bénévoles
[Termes IGN] extraction de données
[Termes IGN] géoréférencement
[Termes IGN] point d'intérêt
[Termes IGN] Riga
[Termes IGN] site wiki
[Termes IGN] système de recommandation
[Termes IGN] Tallinn
[Termes IGN] taxinomie
[Termes IGN] tourismeRésumé : (auteur) The research covered in this thesis is focused on different aspects of the task of creating automated recommendations for tourism, focusing mostly on places of interest like beautiful views, architectural landmarks, charming areas etc. A significant amount of work has been spent on designing and developing actual recommender systems - Sightsplanner, Sightsmap and the automated recommender of Visit Estonia - and their data harvesting methods in order to create a platform for showing the feasibility of the new methods designed and experimented with. The main results of our research are split between three subfields:
• Knowledge engineering: we have shown how to formalize fuzzy and uncertain POI categories along with suitable ontologies and reasoner-based algorithms for object matching and score calculation in a real-life context of actual POI-s, available data and easily expressable user preferences.
• Machine learning: we have designed a learnable detection system for detecting duplicate POIs from different databases, usable for cross- category, cross-language and cross-city datasets.
• We show that learning on Tallinn eateries improved the algorithm parameters to such a degree that on Riga data containing also museums and galleries it gave us 98% accuracy versus 85% accuracy achieved by tuning the algorithm parameters manually.
• Knowledge extraction: we have designed an algorithm for high-quality keyword extraction from short crowd-sourced POI descriptions in different languages, able to find a suitable name and to add suitable types to the POI. Our clusterization algorithm is able to merge the POIs based on the extracted data: on the Panoramio and Wikipedia data about U.K. and French locations it was able to find 56% of Wikipedia objects from the textual titles/annotations of Panoramio pictures in the area.Note de contenu : 1- Introduction
2- Related work
3- Involvement in recommender projects
4- Data acquisition and information extraction
5- Data deduplication (using machine learning)
6- Location category and name detection
7- Data storage and object score calculation
8- Conclusions
9- Future workNuméro de notice : 28600 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Thèse étrangère Note de thèse : PhD Thesis : Computer Science : Tallinn University of Technology : 2021 DOI : 10.23658/taltech.23/2021 En ligne : https://doi.org/10.23658/taltech.23/2021 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99407 Impact of deadwood decomposition on soil organic carbon sequestration in Estonian and Polish forests / Ewa Blonska in Annals of Forest Science, Vol 76 n° 4 (December 2019)
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Titre : Impact of deadwood decomposition on soil organic carbon sequestration in Estonian and Polish forests Type de document : Article/Communication Auteurs : Ewa Blonska, Auteur ; Jaroslaw Lasota, Auteur ; Arvo Tullus, Auteur ; et al., Auteur Année de publication : 2019 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] bois mort
[Termes IGN] déchet organique
[Termes IGN] Estonie
[Termes IGN] forêt boréale
[Termes IGN] forêt tempérée
[Termes IGN] Pologne
[Termes IGN] teneur en carbone
[Vedettes matières IGN] Ecologie forestièreRésumé : (auteur) Key message : The deadwood of different tree species with different decomposition rates affects soil organic carbon sequestration in Estonian and Polish forests. In warmer conditions (Poland), the deadwood decomposition process had a higher rate than in cooler Estonian forests. Soil organic matter fractions analysis can be used to assess the stability and turnover of organic carbon between deadwood and soil in different experimental localities. Context : Deadwood is an important element of properly functioning forest ecosystem and plays a very important role in the maintenance of biodiversity, soil fertility, and carbon sequestration. Aims : The main aim was to estimate how decomposition of deadwood of different tree species with different decomposition rates affects soil organic carbon sequestration in Estonian and Polish forests. Methods : The investigation was carried out in six forests in Poland (51° N) and Estonia (58° N). The study localities differ in their mean annual air temperature (of 2 °C) and the length of the growing season (of 1 month). The deadwood logs of Norway spruce (Picea abies (L.) Karst.), common aspen (Populus tremula L.), and silver birch (Betula pendula Roth) were included in the research. Logs in three stages of decomposition (III–V) were selected for the analysis.
Results : There were differences in the stock of soil organic carbon in two experimental localities. There was a higher soil carbon content under logs and in their direct vicinity in Polish forests compared to those in the cooler climate of Estonia. Considerable differences in the amount of soil organic matter were found. The light fraction constituted the greatest quantitative component of organic matter of soils associated with deadwood. Conclusion : A higher carbon content in surface soil horizons as an effect of deadwood decomposition was determined for the Polish (temperate) forests. More decomposed deadwood affected soil organic matter stabilization more strongly than less decayed deadwood. This relationship was clearer in Polish forests. Higher temperatures and longer growing periods primarily influenced the increase of soil organic matter free light fraction concentrations directly under and in close proximity to logs of the studied species. The slower release of deadwood decomposition products was noted in Estonian (hemiboreal) forests. The soil organic matter mineral fraction increased under aspen and spruce logs at advanced decomposition in Poland.Numéro de notice : A2019-530 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-019-0889-9 Date de publication en ligne : 29/10/2019 En ligne : https://doi.org/10.1007/s13595-019-0889-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94118
in Annals of Forest Science > Vol 76 n° 4 (December 2019)[article]Mapping changes of residence with passive mobile positioning data : the case of Estonia / Pilleriine Kamenjuk in International journal of geographical information science IJGIS, vol 31 n° 7-8 (July - August 2017)
PermalinkEffects of environmental factors on the species richness, composition and community horizontal structure of vascular plants in Scots pine forests on fixed sand dunes / Mari Tilk in Silva fennica, vol 51 n° 3 (2017)
PermalinkPlant community mycorrhization in temperate forests and grasslands: relations with edaphic properties and plant diversity / Maret Gerz in Journal of vegetation science, vol 27 n° 1 (January 2016)
PermalinkPermalinkHabitat directive forest type western taiga (*9010) in Estonia : the first description of stand structure according to mapping and monitoring data / Anneli Palo in Baltic forestry, vol 21 n° 1 ([01/02/2015])
PermalinkLes industries baltes du bois en plein essor / Al Arter in Le Bois International : l'officiel du bois [édition verte], vol 2008 n° 17 (3 et 10 mai 2008)
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