Global forest management data for 2015 at a 100 m resolution.

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.

Scots pine stands biomass assessment using 3D data from unmanned aerial vehicle imagery in the Chernobyl Exclusion Zone.

Thirty-five years after the accident, large forest areas in the Chernobyl Exclusion Zone still contain huge amounts of radionuclides released from the Chernobyl Nuclear Power Plant Unit 4 in April 1986. An assessment of the radiological and radioecological consequences of persistent radioactive contamination and development of remediation strategies for Chernobyl forests imply acquiring comprehensive data on their contamination levels and dynamics of biomass inventories. The most accurate forest inventory data can be obtained in ground timber cruises. However, such cruises in radioactive contaminated forest ecosystems in the Chernobyl Exclusion Zone result in radiation exposures of the personnel involved, which means the need for development of the remote sensing methods. The purpose of this study is to analyze the applicability and limitations of the photogrammetric method for the remote large-scale monitoring of aboveground biomass inventories. Based on field measurements, we estimated the biomass inventories in 31 Scots pine stands including both artificial plantations and natural populations. The stands differed significantly in age (from a few years in natural populations to 115 years in the oldest plantation), productivity (from 0.4 to 19.8 kg m-2), mean height (from 4.1 to 36 m), and other parameters. Photogrammetric data were obtained from the same stands using unmanned aerial vehicle (UAV). These data were then processed using two approaches to derive the canopy height model (CHM) parameters which were tested for correlation with the aboveground biomass inventories. In the first approach, we found that the inventories correlated well with the mean value of CHM of the site (R2 = 0.79). In the second approach, the total aboveground biomass was approximated by a function of the average height of trees detected at the site and the total crown projection area (R2 = 0.78). Among other local parameters, the total crown projection area was identified as the major factor impacting the accuracy of the aboveground biomass inventory estimates from the UAV survey data in both approaches. In the dense stands with the high total crown projections areas (more than 0.90), the average relative deviations of the UAV-based aboveground biomass estimates from the results of the field measurements were close to 0, which means the adequate accuracy of the UAV surveys data for radioecological monitoring purposes. The relative deviations of the UAV-based estimates in both approaches increased in the stands consisting of separated groups of trees, which indicates potential limitation of the approaches and need for their further development.