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1. Biodiversity is an important component of natural ecosystems, with higher species richness often correlating with an increase in ecosystem productivity. Yet, this relationship varies substantially across environments, typically becoming less pronounced at high levels of species richness. However, species richness alone cannot reflect all important properties of a community, including community evenness, which may mediate the relationship between biodiversity and productivity. If the evenness of a community correlates negatively with richness across forests globally, then a greater number of species may not always increase overall diversity and productivity of the system. Theoretical work and local empirical studies have shown that the effect of evenness on ecosystem functioning may be especially strong at high richness levels, yet the consistency of this remains untested at a global scale. 2. Here, we used a dataset of forests from across the globe, which includes composition, biomass accumulation and net primary productivity, to explore whether productivity correlates with community evenness and richness in a way that evenness appears to buffer the effect of richness. Specifically, we evaluated whether low levels of evenness in speciose communities correlate with the attenuation of the richness–productivity relationship. 3. We found that tree species richness and evenness are negatively correlated across forests globally, with highly speciose forests typically comprising a few dominant and many rare species. Furthermore, we found that the correlation between diversity and productivity changes with evenness: at low richness, uneven communities are more productive, while at high richness, even communities are more productive. 4. Synthesis. Collectively, these results demonstrate that evenness is an integral component of the relationship between biodiversity and productivity, and that the attenuating effect of richness on forest productivity might be partly explained by low evenness in speciose communities. Productivity generally increases with species richness, until reduced evenness limits the overall increases in community diversity. Our research suggests that evenness is a fundamental component of biodiversity–ecosystem function relationships, and is of critical importance for guiding conservation and sustainable ecosystem management decisions., Journal of Ecology, 111 (6), ISSN:0022-0477

Biodiversity is an important component of natural ecosystems, with higher species richness often correlating with an increase in ecosystem productivity. Yet, this relationship varies substantially across environments, typically becoming less pronounced at high levels of species richness. However, species richness alone cannot reflect all important properties of a community, including community evenness, which may mediate the relationship between biodiversity and productivity. If the evenness of a community correlates negatively with richness across forests globally, then a greater number of species may not always increase overall diversity and productivity of the system. Theoretical work and local empirical studies have shown that the effect of evenness on ecosystem functioning may be especially strong at high richness levels, yet the consistency of this remains untested at a global scale. 2. Here, we used a dataset of forests from across the globe, which includes composition, biomass accumulation and net primary productivity, to explore whether productivity correlates with community evenness and richness in a way that evenness appears to buffer the effect of richness. Specifically, we evaluated whether low levels of evenness in speciose communities correlate with the attenuation of the richness–productivity relationship. 3. We found that tree species richness and evenness are negatively correlated across forests globally, with highly speciose forests typically comprising a few dominant and many rare species. Furthermore, we found that the correlation between diversity and productivity changes with evenness: at low richness, uneven communities are more productive, while at high richness, even communities are more productive. 4. Synthesis. Collectively, these results demonstrate that evenness is an integral component of the relationship between biodiversity and productivity, and that the attenuating effect of richness on forest productivity might be partly explained by low evenness in speciose communities. Productivity generally increases with species richness, until reduced evenness limits the overall increases in community diversity. Our research suggests that evenness is a fundamental component of biodiversity–ecosystem function relationships, and is of critical importance for guiding conservation and sustainable ecosystem management decisions.

Publisher Copyright: © 2022 Mait Lang et al., published by Sciendo. The view angle range of Sentinel-1 SAR in the Interferometric Wide swath (IW) measurement mode is 29.1° - 46.0°. The dependence of backscatter on the arbitrary local incidence angle is usually corrected using a linear regression model where the incidence angle is a predictor variable. We analysed the whole time series of Sentinel-1 SAR VV-polarised backscatter over the flat 15×15 km test site in Laeva, Estonia (26° 26′ 43″ E; 58° 31′ 56″ N). Time series containing measurements from three different orbits were constructed for 3,159 stands from nighttime data and for 1,105 stands from daytime data. We can confirm that daytime backscatter is systematically greater than nighttime backscatter. We found a significant deviation from linearity in the backscatter dependence on local incidence angle. The empirical finding may be caused by the microwave scattering dependence on local incidence angle or by the influence of Sentinel-1 SAR sub-swath configuration in the Terrain Observation with Progressive Scans SAR (TOPSAR) method that is used for the measurements.

One of the most fundamental questions in ecology is how many species inhabit the Earth. However, due to massive logistical and financial challenges and taxonomic difficulties connected to the species concept definition, the global numbers of species, including those of important and well-studied life forms such as trees, still remain largely unknown. Here, based on global groundsourced data, we estimate the total tree species richness at global, continental, and biome levels. Our results indicate that there are 73,000 tree species globally, among which ∼9,000 tree species are yet to be discovered. Roughly 40% of undiscovered tree species are in South America. Moreover, almost one-third of all tree species to be discovered may be rare, with very low populations and limited spatial distribution (likely in remote tropical lowlands and mountains). These findings highlight the vulnerability of global forest biodiversity to anthropogenic changes in land use and climate, which disproportionately threaten rare species and thus, global tree richness.

The RAdiative transfer Model Intercomparison (RAMI) activity focuses on the benchmarking of canopy radiative transfer (RT) models. For the current fourth phase of RAMI, six highly realistic virtual plant environments were constructed on the basis of intensive field data collected from (both deciduous and coniferous) forest stands as well as test sites in Europe and South Africa. Twelve RT modelling groups provided simulations of canopy scale (directional and hemispherically integrated) radiative quantities, as well as a series of binary hemispherical photographs acquired from different locations within the virtual canopies. The simulation results showed much greater variance than those recently analysed for the abstract canopy scenarios of RAMI-IV. Canopy complexity is among the most likely drivers behind operator induced errors that gave rise to the discrepancies. Conformity testing was introduced to separate the simulation results into acceptable and non-acceptable contributions. More specifically, a shared risk approach is used to evaluate the compliance of RI model simulations on the basis of reference data generated with the weighted ensemble averaging technique from ISO-13528. However, using concepts from legal metrology, the uncertainty of this reference solution will be shown to prevent a confident assessment of model performance with respect to the selected tolerance intervals. As an alternative, guarded risk decision rules will be presented to account explicitly for the uncertainty associated with the reference and candidate methods. Both guarded acceptance and guarded rejection approaches are used to make confident statements about the acceptance and/or rejection of RT model simulations with respect to the predefined tolerance intervals. (C) 2015 The Authors. Published by Elsevier Inc.

[EN] The identity of the dominant root-associated microbial symbionts in a forest determines the ability of trees to access limiting nutrients from atmospheric or soil pools, sequester carbon and withstand the effects of climate change. Characterizing the global distribution of these symbioses and identifying the factors that control this distribution are thus integral to understanding the present and future functioning of forest ecosystems. Here we generate a spatially explicit global map of the symbiotic status of forests, using a database of over 1.1 million forest inventory plots that collectively contain over 28,000 tree species. Our analyses indicate that climate variables—in particular, climatically controlled variation in the rate of decomposition—are the primary drivers of the global distribution of major symbioses. We estimate that ectomycorrhizal trees, which represent only 2% of all plant species, constitute approximately 60% of tree stems on Earth. Ectomycorrhizal symbiosis dominates forests in which seasonally cold and dry climates inhibit decomposition, and is the predominant form of symbiosis at high latitudes and elevation. By contrast, arbuscular mycorrhizal trees dominate in aseasonal, warm tropical forests, and occur with ectomycorrhizal trees in temperate biomes in which seasonally warm-and-wet climates enhance decomposition. Continental transitions between forests dominated by ectomycorrhizal or arbuscular mycorrhizal trees occur relatively abruptly along climate-driven decomposition gradients; these transitions are probably caused by positive feedback effects between plants and microorganisms. Symbiotic nitrogen fixers—which are insensitive to climatic controls on decomposition (compared with mycorrhizal fungi)—are most abundant in arid biomes with alkaline soils and high maximum temperatures. The climatically driven global symbiosis gradient that we document provides a spatially explicit quantitative understanding of microbial symbioses at the global scale, and demonstrates the critical role of microbial mutualisms in shaping the distribution of plant species., This work was made possible by the Global Forest Biodiversity Database, which represents the work of over 200 independent investigators and their public and private funding agencies (see Supplementary Acknowledgements), Supplementary information is available for this paper at https://doi.org/10.1038/s41586-019-1128-0.

Uncertainties in estimation of albedo-related radiative forcing cause ambiguity in evaluation of net climate effects of forests and forest management. Numerous studies have reported local relations between forest structure and albedo in the boreal zone. However, more research is needed to establish these relations for geographically extensive areas, and to examine seasonal courses of albedo to understand the effects of forest structure on mean annual shortwave energy balance. Remote sensing is a viable option for accomplishing these goals, but there are many challenges related to e.g. long periods of cloud cover and low solar elevations in high latitudes. We used the new MODIS Collection 6 (MCD43A3) daily albedo product, and analyzed MODIS albedo dependence on airborne LiDAR-based forest structure in 22 study sites in Estonia, Finland, Sweden, and Russia (57 degrees-69 degrees N, 12 degrees-57 degrees E). Wall-to-wall LiDAR data allowed us to take into account the effective spatial resolution of MODIS, which notably improved correlations between albedo and forest structure. Use of the best quality backup algorithm (magnitude inversion) together with main algorithm results in the MODIS albedo product did not reduce the correlations compared to using main algorithm only. We quantified the effects of landscape-level forest structure (forest height, canopy cover, fraction of young forest) and fraction of broadleaved deciduous forest on mean annual albedo. We showed that because the forest structure-albedo relations are the strongest in snow-covered periods, and because the snow-covered period is longest in the north, the effect of forest structure on mean annual albedo increases towards the north. On the other hand, the effect of broadleaved fraction did not show such latitudinal trend. Our results indicate that even within a single climatic zone the optimal forest management solution to mitigate climate change depends on geographic location.

In this Letter, the middle initial of author G. J. Nabuurs was omitted, and he should have been associated with an additional affiliation: ‘Forest Ecology and Forest Management Group, Wageningen University and Research, Wageningen, The Netherlands’ (now added as affiliation 182). In addition, the following two statements have been added to the Supplementary Acknowledgements. (1): ‘We would particularly like to thank The French NFI for the work of the many field teams and engineers, who have made extraordinary efforts to make forest inventory data publicly available.’ (1): ‘Sergio de Miguel benefited from a Serra- Húnter Fellowship provided by the Generalitat of Catalonia.’ Finally, the second sentence of the Methods section should have cited the French NFI, which provided a national forestry database used in our analysis, to read as follows: ‘The GFBi database consists of individual-based data that we compiled from all the regional and national GFBi forest-inventory datasets, including the French NFI (IGN—French National Forest Inventory, raw data, annual campaigns 2005 and following, https://inventaire-forestier.ign.fr/spip.php?rubrique159, site accessed on 01 January 2015)’. All of these errors have been corrected online. © 2019, The Author(s), under exclusive licence to Springer Nature Limited.

The RAdiative transfer Model Intercomparison (RAMI) activity focuses on the benchmarking of canopy radiative transfer (RT) models. For the current fourth phase of RAMI, six highly realistic virtual plant environments were constructed on the basis of intensive field data collected from (both deciduous and coniferous) forest stands as well as test sites in Europe and South Africa. Twelve RT modelling groups provided simulations of canopy scale (directional and hemispherically integrated) radiative quantities, as well as a series of binary hemispherical photographs acquired from different locations within the virtual canopies. The simulation results showed much greater variance than those recently analysed for the abstract canopy scenarios of RAMI-IV. Canopy complexity is among the most likely drivers behind operator induced errors that gave rise to the discrepancies. Conformity testing was introduced to separate the simulation results into acceptable and non-acceptable contributions. More specifically, a sharedrisk approach is used to evaluate the compliance of RT model simulations on the basis of reference data generated with the weighted ensemble averaging technique from ISO-13528. However, using concepts from legal metrology, the uncertainty of this reference solution will be shown to prevent a confident assessment of model performance with respect to the selected tolerance intervals. As an alternative, guarded risk decision rules will be presented to account explicitly for the uncertainty associated with the reference and candidate methods. Both guarded acceptance and guarded rejection approaches are used to make confident statements about the acceptance and/or rejection of RT model simulations with respect to the predefined tolerance intervals.

Lõppenud Keskkonnainvesteeringute Keskuse finantseeritud uurimisprojekti eesmärgiks oli metsade kaugseire meetodi arendamine metsaga alade pindala muutuste jälgimiseks.

FORMIT-M is a widely applicable, open-access, simple and flexible, climate-sensitive forest management simulator requiring only standard forest inventory data as input. It combines a process-based carbon balance approach with a strong inventory-based empirical component. The model has been linked to the global forest sector model EFI-GTM to secure consistency between timber cutting and demand, although prescribed harvest scenarios can also be used. Here we introduce the structure of the model and demonstrate its use with example simulations until the end of the 21st century in Europe, comparing different management scenarios in different regions under climate change. The model was consistent with country-level statistics of growing stock volumes (R2 = 0.938) and its projections of climate impact on growth agreed with other studies. The management changes had a greater impact on growing stocks, harvest potential and carbon balance than projected climate change, at least in the absence of increased disturbance rates., Environmental Modelling & Software, 115, ISSN:1364-8152, ISSN:1873-6726

Magistritöö Metsamajanduse ja metsaökoloogia õppekaval Puistute harvendamise vajadust hinnatakse tavaliselt metsa inventeerimisandmete ja välivaatluste abil, mis on kulukad, ning tihedama intervalliga teavet puistu erinevate takseertunnuste kohta võib saada aerolaserskaneerimisega tehtud mõõtmistest. Käesoleva lõputöö eesmärk oli uurida aerolidari mõõdistusel põhineva harvendusraie vajaduse hindamise mudeli tegemise võimalikkust ja võrrelda tulemusi varasemate sarnaste uuringutega. Harvendusraie vajadust hinnati välitööde põhjal 2022. aasta kevadest kuni 2023. aasta talveni kokku 188 metsaeraldisel Lääne-Virumaal. Maa-ameti kodulehelt laeti alla suvise mõõdistuse 2020. aasta punktipilved ja igale eraldisele arvutati lidarimeetrikud. Koguandmestikust jagati 152 eraldist treeningandmestikuks ja 36 eraldist valideerimisandmestikuks. Harvendusraie vajaduse hindamise mudelid koostati treeningandmestiku põhjal logistilise regressioonianalüüsiga. Kokku loodi võrdlemiseks 20 mudelit. Valideerimisel oli erinevate mudelite prognoositäpsus 78–94% (2–8 erinevust 36 eraldise kohta võrreldes välitööde hinnangutega). Mudelitele tehti tundlikkuse test, selleks jagati kogu andmestikust kümnel korral juhuslikkuse alusel uuesti 36 eraldist testandmestikku. Kõigil kümnel korral testiti mudeleid saadud andmestikel uuesti. Tundlikkuse testi järgi erinesid kümnel korral mudelite prognoosid ja välitööde hinnangud keskmiselt 5,1–6,7 eraldisel. Kõik mudelid prognoosisid küllaltki samaväärselt. Lõputöö tulemuste põhjal võib öelda, et erinevad katvuse ja kõrgusjaotuse meetrikute kombinatsioonid prognoosivad harvendusraie vajadust küllaltki võrdväärselt. Edaspidistes uuringutes võiks analüüsida lidaripõhiste harvendusraiemudelite toimimist erametsade puhul, kuna sealsed puistud võivad olla erineva struktuuri ja majanduspraktikatega. The need for thinning of stands is usually assessed using forest inventory data and field observations which are expensive. In order to obtain information about the various stand characteristics in a shorter time interval, measurements with airborne laser scanning can be made. This thesis aims to investigate the possibility of constructing a model for predicting the need for commercial thinning based on airborne laser scanning. The results are compared with previous similar studies. The need for thinning was assessed based on field work conducted from spring 2022 to winter 2023 in a total of 188 stand subcompartments in Lääne-Virumaa. Point clouds were downloaded from the Estonian Land Board public access website and lidar metrics were calculated for each subcompartment. From the total dataset, 152 partitions were divided into training datasets and 36 partitions into validation datasets. Models for assessing the need for thinning were created using logistic regression analysis based on training data. All in all, 20 models were constructed. Based on validation, the different models had a prediction accuracy of 78–94% (2–8 differences per 36 subcompartments compared to field estimates). The models were subjected to a sensitivity test by randomly dividing the entire dataset ten times into 36 separate test datasets. Each time the models were retested on the resulting datasets. According to the sensitivity test, the mean difference between the models' predictions compared to the field estimates was between 5.1–6.7 differences for the 36 subcompartments on ten occasions. All models made fairly similar predictions. Based on the results of the thesis, it can be said that different combinations of canopy cover and height distribution metrics predict the need for thinning fairly equally. In future studies, the performance of lidar-based thinning models can also focus on private forests, as the stands there may have different structures and previous forest management practices.

Magistritöö Metsamajanduse ja metsaökoloogia õppekaval Puutüvede läbimõõdu mõõtmine pakub infot puude kasvu ja füsioloogiliste protsesside kohta. Mida paremini me puude kasvutsüklit mõistame ning mida täpsemad ja standardsemad on seejuures rakendatavad mõõtmisvõtted, seda võrreldavamana kujunevad metsakorralduslikud mõõtmistulemused. Puutüve läbimõõt on metsatakseerimisel ainuke kontaktmõõtmiste abil mõõdetav tunnus. Teame, et kasvava puu rinnasläbimõõtu mõõdetakse takseerimisel nii klupiga kui ka ümbermõõdulindiga. Töö toob erinevates tingimustes tehtud välitööde põhjal välja erisusi mõõtmistes – olgu erisus tingitud ilmastikust, ajast, mõõtmistehnikast, mõõtmisvahendist. Töö eesmärgiks on hinnata erinevate tegurite mõju mõõtmisele, võrrelda omavahel metsaklupi ja lindiga tehtud mõõtmisi, tuvastada mõõtmisvigu ja läbimõõdu muutumisi. Mõõtmised toimusid kolmes jaos üheksakümnel puul, tehes igal puul läbimõõdu mõõtmisi kolmel erineval kõrgusel juurekaelast nii klupiga kui ka ümbermõõdulindiga. Ümbermõõdulindiga ja klupiga mõõtmistel on statistiline vahe (p≥ 0,05), kuid see pole nii suur, et nende erinevus metsakorralduses üht teisele eelistama paneks. Mõõtmisi mõjutavad ilmastik, mõõtmistehnika ja rinnasdiameetri kõrguse hindamise oskus. Nii praegu kui ka tulevikus on tarvilik uurida arvutipõhiseid mõõtetehnikaid, näiteks kaugseiremeetodeid, droonide ja kaamerate tõhusamat kasutamist. Nende mõõtmiste tulemuslikkust saab mehaaniliste mõõtevahendite mõõtmistulemustega võrrelda. Measuring the diameter of tree stems provides information about tree growth and physiological processes. The better one understands tree measurement techniques and the more accurate and standardized the measurement methods are, the more comparable the results of forest management measurements become. Stem diameter is the only measurable characteristic in forest inventory that is measured through direct contact measurements. It is known that the diameter at breast height of a growing tree is measured by using both a caliper and a diameter tape. The current study marks differences in measurements made under diferent circumstances, whether influenced by weather, time, measurement technique or measuring instrument. The objective of this research is to assess the impact of various factors on measurements, compare measurements made with a caliper and a diameter tape, and ascertain measurement errors and changes in diameter. The measurements were conducted in three parts using a sample of ninety trees, taking diameter measurements at three different heights from the root collar using both a caliper and a diameter tape. There is a statistical difference between measurements with a diameter tape and caliper, but it is not significant enough to favor one over the other in forest management. Measurements are influenced by weather, measurement techniques, and the skill of assessing breast height diameter. It is necessary to explore computer-based measurement techniques, such as remote sensing methods, drones, and more efficient use of cameras, both now and in the future. The effectiveness of these measurements can be compared with the results provided by mechanical measuring instruments.

Magistritöö Metsamajanduse ja metsaökoloogia õppekaval Metsainventeerimise põhieesmärk on tuvastada muutused metsas ja hinnata takseertunnuste väärtuseid metsakorralduse jaoks. Selline muutuste tuvastamine toimub tavaliselt välimõõtmistel. Lisaks välimõõtmistele on võimalik tuvastada muutuseid puittaimestikus aerolidari andmete põhjal, mida uuritaksegi selles magistritöös. Töö vaatlusvõrk asub Loode-Eestis. Vaatlusalune ala on 10×10 km, millel on 100 proovitükki. Vaatlusalusete proovitükkide kohta uuriti kogu saadavat aerolaserskaneerimise aegrida. Aerolidari punktipilvedest arvutati meetrikud programmi FUSION mooduliga CloudMetrics. Järgnevalt tehti pilootuuring 3D andmete kasutamisvõimaluste kohta maakatte ja kasutuse seireks. Töö hüpoteesid olid (1) metsamaastikul domineerivad taimkatte kõrguse ja teiseks tiheduse muutused ja (2) mitme aasta aerolidarmõõtmise koos kasutamisel saame täpsema hinnagu metsas toimunud muutuste kohta. ALS andmete analüüsi põhjal oli võimalik vaadeldud proovitükkidel eristada tüüpjuhtumeid, mis kirjeldasid enamikke proovitükke. Andmed klasterdati esimestel peegeldustel põhineva katvuse ja kõrguse protsentiili Hp80 järgi nelja klastrisse. The main objective of forest inventory is to detect changes in forests. That kind of changes are usually detected by field measurements. In addition to field work, it is possible to detect changes in forest cover based on aerolidari data, which is also explored in this master's thesis. The observation network is located in North-West Estonia. The area is 10 x 10 km with 100 sample plots. Total available timeline of ALS data were examined. Metrics were calculated from ALS point clouds with Fusion module CloudMetrics. On the basis of the data collected, the main goal of the thesis was to conduct a pilot study on the use of 3D data to monitor land use and cover. The hypotheses are (1) that the forest landscape is dominated by changes in forest cover height and density and (2) usage of multi-year ALS measurements together can get more accurate estimate of changes in forest cover. On the basis of ALS data analysis it is possible to isolate standard cases which describe most of the sample plots. The data was clustered by ALS metrics Hp80 and K1 into 4 clusters.

Magistritöö Metsamajanduse õppekaval Kultuuride hoolduse ja valgustusraiega parandatakse puude valgus- ja toitetingimusi ning suurendatakse puistu majanduslikku tasuvust. Üks võimalus kultuuride hoolduse ja valgustusraie vajaduse hindamiseks on kasutada aerolaserskaneerimise (ALS – Airborne laser scanning) tulemusel saadud punktipilve andmeid. Magistritöö eesmärgiks on uurida kultuuride hoolduse ja valgustusraie vajaduse hindamise võimalusi pungade puhkemise eel tehtud madala punktitihedusega ALS andmete põhjal. Vaadeldud eraldistel oli kultuuride hoolduse ja valgustusraie vajadus suurem kui enamik lidari emiteeritud impulsse registreeriti maapinnalt või punktipilve kõrguste keskväärtusest madalamal. Maapinnale jõuab suurem osa peegeldusi varakevadisel ALS mõõdistuslennul enne vegetatsiooniperioodi, mil lehtpuudel pole lehti ning rohttaimestik praktiliselt puudub. Kultuuride hoolduse ja valgustusraie vajadus on enim seotud (r = 0,63) ALS meetrikuga HCV ehk punktipilve kõrguste variatsioonikoefitsiendiga. Valiti välja 24 sisukat ALS meetrikut ning logistilise regressioonanalüüsi meetodil koostati 12 mudelit. Mudelite testimiseks kasutati RMK 2020. aastal tehtud ning 2021. aastaks planeeritud kultuuride hoolduste ja valgustusraiete andmeid, kokku 450 eraldist. Paremaks osutusid kolm mudelit, mis sisaldasid kaks kuni kolm ALS meetriku elementi. Mudelite rakendamine RMK testandmestikul näitas, et seosed kultuuride hoolduse ja valgustusraie vajaduse ning ALS meetrikute vahel on olemas. Mudelid prognoosisid enamikule RMK eraldistele suurt hooldusraie vajadust ning väiksemat hooldusraie vajadust prognoositi eraldistele, kus kultuuride hooldus ja valgustusraie oli ALS mõõdistuslennu ajaks juba tehtud. Seoste uurimist tasub tulevikus jätkata, seejuures on soovitatav kasutada vegetatsiooniperioodil tehtud ALS mõõdistuslennu andmeid. Praktikas rakendatavate mudelite koostamiseks on vaja suuremat alusandmestikku ning valideerimisandmestik peab sisaldama nii hooldusraiet vajavaid kui mittevajavaid eraldisi. Tulevastel uuringutel võib seoste otsimisel kasutada ka otsustuspuu meetodit. Cleaning and precommercial thinning are necessary for improving the light and nutrition conditions within the remaining stand which in turn increases the economic value of a forest stand. One possibility to evaluate the necessity of cleaning and precommercial thinning of a stand is to use the data obtained from airborne laser scanning (ALS). The aim of this master’s thesis is to find different possibilities of evaluating the necessity of cleaning and precommercial thinning within a stand based on low point density ALS data. The necessity of cleaning and precommercial thinning of the observed forest stands increased when the majority of pulse returns are registered from the ground. Majority of pulse returns are reflected from the ground during ALS which takes place in early spring before the vegetation period. The necessity of cleaning and precommercial thinning is strongly correlated (r = 0,63) with point cloud metric HCV (coefficient of variation of the point cloud heights). 24 informative point cloud metrics were chosen and by using logistic regression method 12 models were constructed. The validation of the models was based on data from Estonian State Forest Management Centre (RMK) – cleaning and precommercial thinning treatment done in 2020 and treatment plans for 2021 (450 forest stand compartments). Better models consisted of two to three ALS point cloud metric elements. Model validation showed that there is a correlation between ALS data and the necessity of cleaning and precommercial thinning. The models predicted higher need for the cleaning and precommercial thinning treatment for most of the forest stand compartments of RMK and less of a need for a treatment in those forest stand compartments where the treatment was done before ALS flight. For the further research it is recommended to use ALS data observed during the vegetation period. For practical models it is necessary to obtain more observations and the data must include forest stands with and without the necessity of cleaning and precommercial thinning. The decision tree method can be used to find the correlation between ALS data and the necessity of cleaning and precommercial thinning.

A Thesis for applying for the degree of Doctor of Philosophy in Forestry. Forest management and planning requires up-to-date data, which commonly is acquired using field experts and ground measurements. Nowadays, more and more of data about forest stands is measured using remotely sensing methods. Most common methods include aerial photography and laser scanning from airplanes, also spectral measurements from satellites or even drone images and applications. This doctoral thesis focuses on developing applications and methods for utilising the airborne laser scanning (ALS) data that is freely available for the whole Estonia. The ALS measurements are carried out by the Estonian Land Board on a routine basis twice a year – in spring and summer. The first variable that was studied in this thesis was forest height. Based on the thesis, the most reliable method for forest height assessment was using the ALS point-cloud 80th height percentile (HP80). The small circular plot (radius of 15…30 m) and stand based studies showed high correlations with the field-measured forest heights and with great confidence it can be said, that ALS-based forest height estimations are close or even with higher accuracy, than field inspected. The second studied variable was standing wood volume. The ALS-based methods and models that were developed throughout this thesis used the idea, that standing wood volume is based on forest height and density. For this the HP80 and a threshold-based point count ratio was used (canopy cover - CC). ALS-based CC (CCALS) estimates were studied and compared with digital hemispherical photo based measurements. The results showed similar errors as were shown in other similar studies, with around 10-15% root mean square error (RMSE). The strongest correlation was shown using all echoes above a 1.3 metre threshold. Combining the CCALS and HP80 showed standing wood volume estimates with a similar error as we would receive from field measurements (

Bakalaureusetöö Metsanduse õppekaval Antud lõputöö uurimusülesandeks oli teha andmetöötlust QGIS tarkvaras, kus sisendandmeteks olid drooni pealt tehtud aerofotod proovitükkidest ja proovitükkide takseerandmed. Põhieesmärgiks oli õppida tundma andmeid ja andmetöötluse protsessi. Lisaks tehti asukohamääramise täpsuse eksperiment nutitelefoni ja android veebipoes tasuta saadaval oleva GPS Status and Toolbox asukohamääramise rakendusega. Katse eesmärk oli teada saada kui täpselt saab nutitelefoni GPS äpiga kõrgust mõõta ehk kui panna nutitelefon näiteks 100 € maksva drooni külge, mis on paljudele taskukohane hind, siis võiks saada sellega puude kõrgusi mõõta. Samuti antakse töös ülevaade mehitamata õhusõidukitest. Ülevaates kirjeldatakse droonide klassifitseerimist, kasutatavaid seadmeid, seaduseid ja eeskirju ning näiteid mehitamata õhusõidukite kasutamisest metsanduses. Andmetöötluseks vaja minevad sisendandmed saadi Raul Sampaio de Limalt, Diana Laarmannilt ja Mait Langilt, Eesti Maaülikool. Tulemustest järeldati, et andmetöötlus osutus edukaks ja protsessist saadi ülevaade. Varasema kogemuse puudumise tõttu õpiti, kuidas siduda proovitükkide andmestike ja aerofotosid proovitükkidest ning teha pilditöötlust selle põhjal. Samuti saadi nutitelefoni asukoha määramise eksperimendi tulemustele tuginedes kinnitust, et ei ole mõistlik telefoni drooni külge panna ja puude kõrgusi mõõta. Tulemustest selgus, et kõrguslik viga on suurem kui horisontaalne. Nutitelefoni GPS-i antenn on väike ja varjatud, mille tõttu saadakse ebatäpseid andmeid. The aim of this bachelor study was to do basic data processing in QGIS software, where the input were sample plot aerophotos obtained from drone and sample plot datasets. The main purpose of this study was to learn about datasets and data processing. Futhermore, a positioning accuracy experiment was performed with a smartphone and GPS Status and Toolbox application which is available for free on the android online store. The purpose of the experiment was to find out how accurate is smartphone GPS height measure, for example if we put a smartphone on a simple 100€ costing drone, which is an affordable price, we could use it to measure the height of trees. The thesis gives also an overview of unmanned aircrafts. The overview describes the classification of drones, the equipment used, the laws and regulations and examples of the use of unmanned aerial veichles in forestry. The datasets required for data processing were obtained from Raul Sampaio de Lima, Diana Laarmann and Mait Lang, Estonian University of Life Sciences. The results showed that the data processing was successful and that an overview of the data process was obtained. It was possible use sample plot datasets and aerial photography of sample plots together and apply basic image processing. According to the results of the smartphone positioning experiment it is not reasonable to use a smartphone on the drone for measuring the heights of trees. The results showed that the height error is larger than the horizontal error. The GPS antenna of smartphone is small and hidden, which results in inaccurate datasets.

Bakalaureusetöö Metsanduse õppekaval Aerolaserskaneerimist on Eestis teostatud alates 2008. aastast ja piisava tihedusega (>10 p/ m2 ) aerolidari andmete abil on võimalik hinnata väga hea täpsusega üksikpuude kõrguseid. Töö tehti hõredate andmete põhjal punktitihedusega 0.18 p/m2 . Töö eesmärgiks oli uurida, kuidas on võimalik kasutada lidari andmeid kõrgeimate puude otsimiseks üle Eesti Järvselja Õppe- ja Katsemetskonna näitel. Töös kasutati Eesti põhikaarti ja Maa-ameti lidari kõrgusandmeid 2012-2015 aastatel tehtud lendudest. Punktipilvede töötlemise tulemusena tekitati Järvselja taimkatte kõrguskaart, mille abil otsiti välja potentsiaalsete kõrgete puude asukohad ja välitööde käigus mõõdeti üle asukohas asuvad puud. Lidari andmetöötluseks kasutati FUSIONi erinevaid mooduleid. Töös selgus, et kõrgusandmed olid poolte puude puhul sarnased (±2 m), ülejäänud kordadel oli erinevus küllaltki suur võrreldes lidari andmetel põhineva kõrgusega ja metsas mõõdetud kõrgusega. Tihtipeale on raskendatud metsas puu mõõtmine, see sõltub puistu tihedusest ja sealt võib omakorda viga tekkida. Lidari kõrgusandmete täpsus sõltub suuresti alustaimestiku kasvufaasist. Problemaatiliseks võib kujuneda ka õige asukoha leidmine, sest kasutatud GPS (Global Positioning System) vastuvõtja täpsus ei pruugi olla alati piisav ja asukohavead metsa all võivad olla kuni 10 meetrit. Airborne laser scanning has been carried out in Estonia since 2008. Laser scanning data with sufficient point density (>10 p/ m2 ), has the potential to estimate the height of single trees with very good accuracy. This study was done with sparse data at point density of 0.18 p/m2 . The purpose of this study is to analyse and develop methods for using lidar data to find tall single trees in Järvselja and potentially develop a method for whole Estonia. The data used in this study was measured by Estonian Land Board during 2012-2015. First a vegetation height map with 10×10 m pixel was created for Järvselja area. The vegetation height map was used to find locations of possible tall trees and these locations were checked and measured during fieldwork. Lidar data processing was carried out using FUSION and its different modules. The work revealed that height data was in good correlations with field measured tree height data for half of the trees (±2 m), but differences for the other plots were rather big compared with lidar based height estimations. A significant reason for such differences is often caused by the difficulties on measuring tree height in the forest, because it depends largely on the density of the stand and it might cause some errors. The accuracy of lidar-based estimations depends largely from forest undergrowth. Finding the right location can also be problematic, because GPS (Global Positioning System) receiver might not be always accurate and positioning errors in forest may be up to 10 meters.

Bakalaureusetöö Metsanduse õppekaval Käesoleva bakalaureusetöö eesmärk oli anda ülevaade metsamajandusliku kaugseire tehnikast ja meetoditest ning rakendamisest Eestis, kasutades referentsiks metsade kaugseiret kirjeldanud uurimusi mitmetest erinevatest riikidest. Põhjaliku ülevaate saamiseks kasutati teadustöid Eestist ning välismaalt. Käesolevas töös on refereeritud uurimusi, mis sidusid endas metsamajanduslikku kaugseiret ja metsade takseerimist. Erinevate uurimuste läbi töötamine andis kinnitust, et võrreldes välismaal tehtud metsade kaugseire rakenduslike uurimustega, on Eestis läbi viidud teadustööd olnud väga hea rakendusliku potentsiaaliga. Tehnika ning teaduse arenguga suureneb ka vajadus üha täpsemate metsade inventeerimisandmete järgi, seega on inventeerimisandmete kvaliteedil tähtis osa tõhusa metsamajandusliku kaugseire toimimiseks. The aim of this bachelor thesis was to give a general overview of remote sensing technology, methods and applications for forest inventory in Estonia. Diferent scientific articles on remote sensing in forestry were used which asessed the combination of forest inventory and application of remote sensing in forestry. These articles were from Estonia and from abroad. Conclusion of collating these articles, was that remote sensing in forestry in Estonia has been well applied to resolve multiple issues in forest managment. The growing need of accurate forest inventory data for algoritm training will be one problem to solve to increase the efficiency of remote sensing-based estimates in the future.

Magistritöö Metsatööstuse õppekaval Uurimustöö eesmärk oli koostada metsa laserskanneerimise (ALS) andmetel töötav mudel, mis võimaldaks hinnata puistute harvendusraie-eelset hõredust. Selle eesmärgi saavutamiseks modifitseeriti olemasolevat metsaregistri andmetel töötavat raie-eelse hõreduse (Lre) arvutamise mudelit, mille sisendparameetriteks on puistu keskmine diameeter (D) ja kõrgusindeks (H100). Töö esimeseks etapiks oli Maa-Ameti poolt 2013. aastal Laeva katseala kohta kogutud lidariandmete töötlemine, mille tulemusena saadi iga katsealal oleva eraldise kohta punktipilv. Sellele järgnes metsaregistri andmete töötlemine, kust valiti välja potentsiaalselt harvendusraiet vajavad puistud. Kolmanda etapina koostati nende andmetega mudelid, kus prognoositavaks tunnuseks oli Lre. Mudelite koostamisel asendati D erinevate lidari andmete põhjal arvutatud punktipilve kõrgusjaotuse protsentiilidega. Lisaks prooviti mudelisse lisada erinevaid võrastiku katvuse hinnanguid, laserimpulsi peegelduste kõrguste keskväärtust ja standardhälvet. Tulemuseks saadi 14 erineva kujuga kuid statistiliste karakteristikute poolest sarnast mudelit. Mudelites kasutatud ALS meetrikuteks olid kõrgusjaotuse 90 ja 95 protsentiilid (HP90, HP95), kõigi peegelduste katvuse hinnang 1,3 m kõrguselt (KA1,3), esimeste peegelduste katvuse hinnangud 1,3 m ja 8 m kõrguselt (K1_1,3, K1_8) ning punktipilve kõrguste standardhälve (HSD). Kõik mudelid osutusid oluliseks (p>0,001), determinatsioonikordaja (R 2 ) varieerus 0,67-0,72, jääkviga (σ) 0,27-0,29, keskmine hinnangu viga (MEE) 0,08-0,13 ja ruutkeskmine viga (RMSE) 0,37-0,44. Saadud tulemuste valideerimiseks kasutati eraldi andmestikku. Graafikute tõlgendamise ja mudelites kasutatud liikmete seoste uurimisel puistu hõredusega (L) võiks esile tõsta mudelid LreALS7 ja LreALS8, kus olid sõltumatuteks tunnusteks HSD, HP90 ja HP95. The objective of this thesis was to construct models that predict thinning necessity in forest stands by using airborne laser scanning (ALS) data and site index from forest inventory database. To achieve this, a model that predicts the stand sparsity when thinning is required (Lre), was taken as a starting point and modified. First step was to process ALS data gathered by Estonian Land Board in 2013 for Laeva test site. That was followed by processing data from National Register of Forest Resource for the Laeva test site. Third step was to create glm (generalized linear model) models with the data where Lre was the predicted variable. ALS point cloud metrics were used to replace stand breast height diameter (DBH) in the original Lre model. In total 14 models (LreALSn) were created this way. Models were validated using an independent data set from the Laeva test site. The models had 90th and 95th height percentiles (HP90, HP95), canopy cover estimation from all returns at 1,3 m (KA1,3), canopy cover estimations from first returns at 1,3 m and 8 m (K1_1,3, K1_8) and standard deviation of the height points (HSD) as independent variables. Determination coefficient (R2 ) of the models varied from 0,67-0,75, standard deviation (σ) 0,27-0,29, mean estimated error (MEE) 0,08-0,13 and root mean square error (RMSE) 0,37-0,44. All the models were significant (p>0,001). After interpreting validation graphs and looking at correlations between L and all the variables used in the models it can be said that models LreALS7 and LreALS8 should be looked at first when doing further research.

Magistritöö Loodusvarade kasutamise ja kaitse õppekaval Puistute liigilise koosseisu info on kasulik nii looduskaitse korraldamisel kui ka metsade majandamisel, kuna see kirjeldab metsade liigirikkust ning on vajalik metsakasvatuslike võtete planeerimisel. Metsade liigilist kooseisu määratakse peamiselt takseerimise teel, mis on ajamahukas töö. Kaugseire andmeid ja andmetöötlust kasutades on võimalik kiirelt anda ligikaudne hinnang suurtele aladele. Uurimustöö eesmärk oli testida puistute liigilise koosseisu hindamist multispektraalsete satelliidipiltide abil kasutades kasvuperioodi käigus puistute spektraalses signatuuris toimuvaid muutusi. Töös on kasutatud kolme erineva satelliidi multispektraalsete sensorite aegridade ülesvõtteid aastatest 2000 ja 2015. Analüüsi meetodina on kasutatud k–lähima naabri algoritmi. Töö tulemusena selgus, et näiteks männi, kuuse ja vanemate kaasikute puhtpuistud eristusid küllaltki hästi, mida näitas ka kuni väärtuseni 0,9 küündinud Kappa kokkulangevuse indeks. Teiste uuritavate klasside eristamine osutus keerukamaks, nimelt heitlehiste puuliikide, mille spektraalne signatuur samades fenoloogilistes etappides on üsna sarnane, täpsemaks kaardistamiseks peab tulevastes uurimustes kasutama täiendavaid kirjeldavaid tunnuseid. Information about stand species composition is useful for many applications in nature preservation and forest management, because it helps to describe biodiversity and creates a basis for better planning of silvicultural interventions. Forest species composition is usually acquired from forest inventory, but the fieldwork is time consuming. Remote sensing methods can quickly provide an approximate estimation for large areas. The aim for this study is to test the species composition estimation using multispectral satellite images based on phenology induces changes in spectral signature. Three different multispectral satellite image series were used in this study from years 2000 and 2015. An implementation of k–nearest neighbour algorithm provided by IDRISI spatial analysis environment was used to analyse the data. The work showed that pure stands of pine, spruce and older birch were well distinguished from others with Kappa indexes of agreement reaching to 0.9. However, to distinguish some classes from each other turned out to be troublesome. The discrimination of deciduous tree species from each other, which have very similar spectral signatures during the same phenological stages, calls for future studies to be conducted by using additional descriptive features.

Töö käsitleb aerolidari andmestiku kasutamist metsa tüvemahu hindamisel. Töö eesmärk on anda uuritavale metsaleüksusele puidumahu ja kasvava metsa väärtuse hinnang kasutades aerolidari andmeid. Töös kasutati Järvselja Õppe- ja Katsemetskonna takseerandmeid, 2010. aasta Maa-ameti aerolidari andmeid, varasemates töödes välja töötatud arvutusmudeleid. Tehtud töö tulemusena saadi uuritavale metsale aerolidari andmestikul põhinevad tüvemahu hinnangud ja kasvava metsa rahaline väärtus. Saadud tulemusi võrreldi takseerandmete põhjal saadud samade tulemustega. Töö tulemustest saab järeldada, et kasutades varasemates töödes välja töötatud arvutusmudeleid, on lidari andmestiku põhjal võimalik anda metsale pädevaid hinnanguid. The major objective of this study is the use of airborne lidar data for estimating standing wood volume and price of forest. This study gives an estimated volume for standing wood to one specific forest, using airborne lidar data. The results are compared with the standing wood volume taken from the forest's inventory data. The results reveal that the estimating standing wood volume, using airborne lidar data is competent and can be an alternative for real estate evaluation in case forest inventory data are not available.

See uuring viidi läbi selleks, et uurida, kuidas saab eristada erinevaid puuliike üksteisest, kasutades multispektraalseid satelliidipilte. Peamiseks eesmärgiks oli välja selgitada, kas on olemas seos puuliikide määramise täpsuse ja puistu vanuse vahel. Uuringud näitavad, et reeglina vanemad puistud peegeldavad vähem elektromagnetilist kiirgust kui nooremad puistud ning see muudab lihtsamaks puistu vanuse määramine. Samuti, vanemates puistudes, erinevate puuliikide spektraalsed signatuurid erinevad rohkem kui nooremates puistudes. See teeb puuliigi määramist lihtsam ja täpsem, võrreldes nooremate puistutega, mis paljudel juhtudel võivad olla väga sarnaste spektraalsete signatuuridega. Ülaltoodud väidete kontrollimiseks kasutati Viljandi maakonna multispektraalsed satelliidipildid, sama regiooni metsakorralduse andmestik, mis sisaldas üksikasjalikke statistikat iga puistu kohta, ja maakasutuse kaarti. Andmete töötlemiseks, spektraalanalüüsiks ja visuaalseks tõlgendamiseks kasutati programme Idrisi Selva ja Quantum GIS. Selle uurimistöö tulemusena oli kinnitatud korrelatsioon niisuguste parameetrite vahel nagu puistute vanus ja puuliikide määramise täpsus satelliidipiltidelt. Klassifikatsiooni täpsuse paranemine leiti puistudel, mis olid üle 21 aasta vanad ja sisaldasid kõrge protsenti kuuske (üle 60%) This research was conducted to investigate the way how different tree species can be discriminated from each other, using multispectral satellite images. The main objective was to find out if there is a correlation between the accuracy of species discrimination and the age of forest stands. Researches show that as a rule, older forest stands reflect less electromagnetic radiation than younger forest stands, and that makes it easier to define whether the stand is young or old. Also, in the older forest stands, the spectral signatuures of different tree species become more differentiated from each other than in young stands. It makes species discrimination more easy to perform and more accurate, compared to the younger stands which might have a very similar spectral signature in many cases. In order to test the statements above, multispectral satellite images of the Viljandi county in Estonia, forest inventory database of this region, which included detailed statistics about every stand, and a land use map were used. For data processing, spectral analysis and visual interpretation were used in programs Idrisi Selva and Quantum GIS. As a result of research, the correlation between the age of forest stands and accuracy of species definition by satellite images was approved. Classification accuracy improvement was found for forest stands which were over 21 years old and included high percent of spruce (over 60%).

Kaugseire andmete põhjal on koostatud palju erinevaid digitaalseid kaarte. Kuna kaardid on koostatud erinevatel eesmärkidel, pole teada kui usaldatavad nende andmed on. Antud töö eesmärk on hinnata mõningate digitaalsete kaartide täpsust Eesti aladel. Kaartide analüüsimiseks kasutatakse nende võrdlemist maakatte uurimisel Eesti põhikaardiga ja metsade koosseisu vaatlemisel Metsakaardiga võrdlemist. Analüüs teostati programmi IDRISI keskkonnas üle-Eestilisena ja maakondade kaupa. Kaartide võrdlemisel selgus, et võrreldes Eesti põhikaardiga on kõik maakattekaardid rohkemal või vähemal määral ebatäpsed. Kõige täpsemalt oli kaartidel määratud metsade ja põllumaade levik, kuid teiste maakatteklassidega olid tulemused kehvemad. Metsade koosseisu määramisel olid kõik kaardid peale Euroopa metsakaardi väga ebatäpsed. Maakondade kaupa olid tulemused väga erinevad. Maakondadest olid maakatte määramisel kõikidel kaartidel mingil põhjusel ebatäpsed Ida-Virumaa ja Saaremaa. Nende maakondade ebatäpsus vajaks veel edasist uurimist. Üldiselt on praeguse võrdluse põhjal näha, et globaalsed maakattekaardid on vähemalt Eesti tasandil suhteliselt ebatäpsed ning nende andmete kasutamine vastutustundlikemal eesmärkidel on küsitav. Many digital maps have been made based on remotely sensed data. Since these maps have been produced for different purposes, it is not known how reliable their data is. The purpose of this work is to assess the accuracy of some digital maps on Estonian scale. For accuracy assessment of maps a comparative analysis is used with Estonian Basic Map and Forest Map to respectively determine accuracy of land cover and forest composition. Analysis were made with program IDRISI on over-Estonian and on county level. It was found after analysis, that when compared with Estonian Basic Map, all land cover maps are more or less inaccurate. On all maps, the extent of forests and croplands were most accurately identified, but other land cover classes were determined with worse accuracy. All maps, besides EU Forest Type Map, were very inaccurate when it comes to estimation of forests composition accuracy. For some reasons accuracy of land cover maps were worse in Ida-Viru and Saare county. The inaccuracy of those counties counties could use some further investigations. Generally, based on this investigation, it can be seen that global land cover maps are at least inaccurate on Estonian scale and their use for accuracy demanding purposes is questionable.