1. High-resolution Pan-European forest structure maps : an integration of earth observation and national forest inventory dataJukka Miettinen, Patricia Adame, Radim Adolt, Iciar Alberdi, Oleg Antropov, Ólafur Arnarsson, Rasmus Astrup, Ambros Berger, Jón Bogason, Gherardo Chirici, Luka Krajnc, Mitja Skudnik, 2024, complete scientific database of research data Keywords: uneven-aged forest, lidar data, canopy height model, voxels, canopy height diversity
Published in DiRROS: 13.08.2024; Views: 254; Downloads: 559
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2. Identifying even- and uneven-aged forest stands using low-resolution nationwide lidar dataAnže Martin Pintar, Mitja Skudnik, 2024, original scientific article Abstract: In uneven-aged forests, trees of different diameters, heights, and ages are located in a small area, which is due to the felling of individual trees or groups of trees, as well as small-scale natural disturbances. In this article, we present an objective method for classifying forest stands into even- and uneven-aged stands based on freely available low-resolution (with an average recording density of 5 points/m2) national lidar data. The canopy closure, dominant height, and canopy height diversity from the canopy height model and the voxels derived from lidar data were used to classify the forest stands. Both approaches for determining forest structural diversity (canopy height diversity—CHDCHM and CHDV) yielded similar results, namely two clusters of even- and uneven-aged stands, although the differences in vertical diversity between even- and uneven-aged stands were greater when using CHM. The first analysis, using CHM for the CHD assessment, estimated the uneven-aged forest area as 49.3%, whereas the second analysis using voxels estimated it as 34.3%. We concluded that in areas with low laser scanner density, CHM analysis is a more appropriate method for assessing forest stand height heterogeneity. The advantage of detecting uneven-aged structures with voxels is that we were able to detect shade-tolerant species of varying age classes beneath a dense canopy of mature, dominant trees. The CHDCHM values were estimated to be 1.83 and 1.86 for uneven-aged forests, whereas they were 1.57 and 1.58 for mature even-aged forests. The CHDV values were estimated as 1.50 and 1.62 for uneven-aged forests, while they were 1.33 and 1.48 for mature even-aged forests. The classification of stands based on lidar data was validated with data from measurements on permanent sample plots. Statistically significantly lower average values of the homogeneity index and higher values of the Shannon–Wiener index from field measurements confirm the success of the classification of stands based on lidar data as uneven-aged forests.
Keywords: uneven-aged forest, lidar data, canopy height model, voxels, canopy height diversity
Published in DiRROS: 13.08.2024; Views: 184; Downloads: 603
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3. Uporabnost nacionalnih podatkov laserskega skeniranja in cikličnega aerofotografiranja pri zaznavanju gozdnih vrzeliAnže Martin Pintar, Mitja Skudnik, 2024, original scientific article Abstract: Gozdna tla zastirajo drevesne krošnje in gozdna vrzel je vsaka večja ali manjša površina tal, ki je ne prekrivajo krošnje zgornjega sloja dreves. Velikost vrzeli vpliva na to, katera drevesna vrsta se bo pomladila, pa tudi na vertikalno in horizontalno strukturo gozda. Na Pohorju (Pahernikova gozdna posest, za katero so značilni gozdovi, v katerih se na majhnih površinah pojavljajo drevesa različnih premerov in starosti) smo analizirali možnosti samodejnega zaznavanja vrzeli na podlagi podatkov Laserskega skeniranja Slovenije (LSS) in Cikličnega aerofotografiranja Slovenije (CAS). Uporabili smo digitalna modela krošenj (DMK), pridobljena iz obeh virov podatkov. Skupna natančnost zaznavanja tudi najmanjših vrzeli (manjših od 50 m2 ) na podlagi podatkov LSS je znašala 94,4 %, na podlagi podatkov CAS pa 83,1 %. Na podlagi podatkov LSS je mogoče zaznati večje število in površino vrzeli, prav tako so vrzeli, pridobljene na podlagi podatkov LSS, bolj razčlenjene in podolgovate. Zaznavanje vrzeli s podatki CAS in LSS je medsebojno bolj primerljivo pri najmanjših površinah vrzeli 100 m2 , natančnost zaznave takšnih vrzeli je 85,4 oziroma 94,4 %. Rezultati kažejo, da je ob odsotnosti podatkov LSS uporaba podatkov CAS za določanje vrzeli smiselna na velikopovršinski ravni in pri zaznavanju vrzeli, večjih od 100 m2 .
Keywords: raznomerni gozdovi, raznodobni gozdovi, digitalni model krošenj, gozdna vrzel, daljinsko zaznavanje, Lasersko skeniranje Slovenije, LSS, Ciklično aerofotografiranje Slovenije, CAS
Published in DiRROS: 08.07.2024; Views: 225; Downloads: 134
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4. Poročilo o spremljanju stanja gozdov za leto 2023 : vsebinsko poročilo o spremljanju stanja gozdov v skladu s Pravilnikom o varstvu gozdov (2009)Andrej Grah, Janez Kermavnar, Nike Krajnc, Lado Kutnar, Tom Levanič, Nikica Ogris, Anže Martin Pintar, Matej Rupel, Mitja Skudnik, Primož Simončič, Saša Šercer, Urša Vilhar, Daniel Žlindra, 2024, final research report Keywords: varstvo gozdov, monitoring, stanje gozdov, zdravstveno stanje krošenj, popis povzročiteljev poškodb, meteorološke meritve, osutost dreves, poročila, Slovenija
Published in DiRROS: 02.07.2024; Views: 226; Downloads: 253
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7. Harmonised statistics and maps of forest biomass and increment in EuropeValerio Avitabile, Roberto Pilli, Mirco Migliavacca, Bogdan Grégory Henry E. Duveiller, Andrea Camia, Viorel Blujdea, Radim Adolt, Iciar Alberdi, Susana Barreiro, Susann Bender, Mitja Skudnik, 2024, original scientific article Abstract: Forest biomass is an essential resource in relation to the green transition and its assessment is key for the sustainable management of forest resources. Here, we present a forest biomass dataset for Europe based on the best available inventory and satellite data, with a higher level of harmonisation and spatial resolution than other existing data. This database provides statistics and maps of the forest area, biomass stock and their share available for wood supply in the year 2020, and statistics on gross and net volume increment in 2010–2020, for 38 European countries. The statistics of most countries are available at a sub-national scale and are derived from National Forest Inventory data, harmonised using common reference definitions and estimation methodology, and updated to a common year using a modelling approach. For those counties without harmonised statistics, data were derived from the State of Europe’s Forest 2020 Report at the national scale. The maps are coherent with the statistics and depict the spatial distribution of the forest variables at 100 m resolution.
Keywords: harmonised statistics, harmonised maps, forest biomass, gorest increment, Europe
Published in DiRROS: 11.03.2024; Views: 408; Downloads: 210
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8. Stanje slovenskih gozdov : poročilo o rezultatih nacionalne gozdne inventure 2022Mitja Skudnik, Luka Krajnc, Gal Kušar, Anže Martin Pintar, 2023, treatise, preliminary study, study Keywords: monitoring, nacionalna gozdna inventura, odmrla lesna biomasa, temeljnica, površina gozda, lesna zaloga, vzorčne ploskve, poročila
Published in DiRROS: 21.11.2023; Views: 614; Downloads: 0 |
9. The LANDSUPPORT geospatial decision support system (S-DSS) vision : operational tools to implement sustainability policies in land planning and managementFabio Terribile, Marco Acutis, Antonella Agrillo, Erlisiana Anzalone, Sayed Azam-Ali, Marialaura Bancheri, Peter Baumann, Barbara Birli, Antonello Bonfante, Marco Botta, Mitja Ferlan, Jernej Jevšenak, Primož Simončič, Mitja Skudnik, 2023, original scientific article Abstract: Nowadays, there is contrasting evidence between the ongoing continuing and widespread environmental degradation and the many means to implement environmental sustainability actions starting from good policies (e.g. EU New Green Deal, CAP), powerful technologies (e.g. new satellites, drones, IoT sensors), large databases and large stakeholder engagement (e.g. EIP-AGRI, living labs). Here, we argue that to tackle the above contrasting issues dealing with land degradation, it is very much required to develop and use friendly and freely available web-based operational tools to support both the implementation of environmental and agriculture policies and enable to take positive environmental sustainability actions by all stakeholders. Our solution is the S-DSS LANDSUPPORT platform, consisting of a free web-based smart Geospatial CyberInfrastructure containing 15 macro-tools (and more than 100 elementary tools), co-designed with different types of stakeholders and their different needs, dealing with sustainability in agriculture, forestry and spatial planning. LANDSUPPORT condenses many features into one system, the main ones of which were (i) Web-GIS facilities, connection with (ii) satellite data, (iii) Earth Critical Zone data and (iv) climate datasets including climate change and weather forecast data, (v) data cube technology enabling us to read/write when dealing with very large datasets (e.g. daily climatic data obtained in real time for any region in Europe), (vi) a large set of static and dynamic modelling engines (e.g. crop growth, water balance, rural integrity, etc.) allowing uncertainty analysis and what if modelling and (vii) HPC (both CPU and GPU) to run simulation modelling ‘on-the-fly’ in real time. Two case studies (a third case is reported in the Supplementary materials), with their results and stats, covering different regions and spatial extents and using three distinct operational tools all connected to lower land degradation processes (Crop growth, Machine Learning Forest Simulator and GeOC), are featured in this paper to highlight the platform's functioning. Landsupport is used by a large community of stakeholders and will remain operational, open and free long after the project ends. This position is rooted in the evidence showing that we need to leave these tools as open as possible and engage as much as possible with a large community of users to protect soils and land.
Keywords: land degradation, land management, soil, spatial decision support system, sustainability
Published in DiRROS: 13.11.2023; Views: 627; Downloads: 318
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