Spatially explicit information on forest management at a global scale is critical for understanding the status of forests, for planning sustainable forest management and restoration, and conservation activities. Here, we produce the first reference data set and a prototype of a globally consistent forest management map with high spatial detail on the most prevalent forest management classes such as intact forests, managed forests with natural regeneration, planted forests, plantation forest (rotation up to 15 years), oil palm plantations, and agroforestry. We developed the reference dataset of 226 K unique locations through a series of expert and crowdsourcing campaigns using Geo-Wiki (https://www.geo-wiki.org/). We then combined the reference samples with time series from PROBA-V satellite imagery to create a global wall-to-wall map of forest management at a 100 m resolution for the year 2015, with forest management class accuracies ranging from 58% to 80%. The reference data set and the map present the status of forest ecosystems and can be used for investigating the value of forests for species, ecosystems and their services.
Climate change continues to threaten forests and their ecosystem services while substantially altering natural disturbance regimes. Land cover changes and consequent management entail discrepancies in carbon sequestration provided by forest ecosystems and its accounting. Currently there is a lack of sufficient and harmonized data for Ukraine that can be used for the robust and spatially explicit assessment of forest provisioning and regulation of ecosystem services. In the frame of this research, we established an experimental polygon (area 45 km2) in Northern Ukraine aiming at estimating main forest carbon stocks and fluxes and determining the impact caused by natural disturbances and harvest for the study period of 2010–2015. Coupled field inventory and remote sensing data (RapidEye image for 2010 and SPOT 6 image for 2015) were used. Land cover classification and estimation of biomass and carbon pools were carried out using Random Forest and k-Nearest Neighbors (k-NN) method, respectively. Remote sensing data indicates a ca. 16% increase of carbon stock, while ground-based computations have shown only a ca. 1% increase. Net carbon fluxes for the study period are relatively even: 5.4 Gg C·year−1 and 5.6 Gg C C·year−1 for field and remote sensing data, respectively. Stand-replacing wildfires, as well as insect outbreaks and wind damage followed by salvage logging, and timber harvest have caused 21% of carbon emissions among all C sources within the experimental polygon during the study period. Hence, remote sensing data and non-parametric methods coupled with field data can serve as reliable tools for the precise estimation of forest carbon cycles on a regional spatial scale. However, featured land cover changes lead to unexpected biases in consistent assessment of forest biophysical parameters, while current management practices neglect natural forest dynamics and amplify negative impact of disturbances on ecosystem services.
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Stem taper equations are crucial for forest management allowing to reliably estimate merchantable wood volume. Their main benefit is the ability to predict stem diameters at a certain height of the stem. Ukraine has recently adopted European Union standards for round wood classification, which prompted the necessity to model stem taper and updates all reference data to conform with the new standards. This study is a systematic attempt to develop a set of taper equations for the most common forest tree species in the Polissia and Forest steppe of Ukraine. For this purpose, we used a data set of 1994 sample trees representing eight tree species collected on 238 sample plots. The Kozak A. (2004, My last words on taper equations. For. Chron.80, 507–515) model was chosen to fit the taper equations. To characterize the variability in stem shape among tree species, mixed-effect models were calibrated for this equation. In this model, random-effect parameters were selected based on their coefficients of variation through a bootstrapping process. This is a novel feature we suggest for the process of calibrating taper models. The Kozak A. (2004, My last words on taper equations. For. Chron.80, 507–515) equation showed a good performance in predicting diameters outside bark and estimating the total stem volume. Our mixed-effect modelling approach accurately characterizes the variation in stem form for different tree species based on adequately chosen random-effect parameters. The stem volumes derived from the developed taper models were compared with existing volume equations outputs (divergence up to 0.5 per cent). A deviation up to 5 per cent was found between the values of fitted and observed cylindrical form factors for the studied tree species. We expect that our taper equations will complement the future steps towards the development of reliable merchantable volume distribution models for the main tree species in the forests of flat land Ukraine, thus, contributing to transparency, reliability and sustainability of forest management and markets in Europe.
In this paper, the possibilities of using stereophotogrammetry methods for measurements using unmanned aerial vehicles (UAVs) for the conditions of a mature pine stand with uneven density are examined. Here, we carried out a comparison of measurements using altimeters and remote sensing data collected with a UAV optical camera. In particular, the height of growing trees was estimated by three different field-based devices and applying the three methods of data collection and processing with UAVs. Specifically, one method implied the direct measurements using on-board UAV equipment. The following two methods are based on the data provided by the stereophotogrammetrical approach, while the aerial images for that were collected using a UAV optical camera. In particular, there was a modeling of the points cloud from one-sided vertical shooting of sample trees and determination of height of trees from digital canopy height model (CHM) from data of aerial photography of horizontal spans over a stand. Our investigation confirmed the highest accuracy of laser measuring tools among the ground measuring devices used in research. Respective value of the average random measurement error was less than 3 % (0.88 m). Among the results obtained from the analysis of the original data collected by UAVs, the best method was to utilize the CHM, namely, the average random error was less than 2% (0.64 m). This exceeds the accuracy of laser altimeter measurements 33 %. Thus, this method of measuring height in pine stands meets the standards of accuracy in determining the height for production assessment, according to the “Inventory guidelines for the forest fund of Ukraine”, and can be used for survey, inventory, forest management and other works related to forestry and monitoring the changes in forest ecosystems.
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