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Satellite imagery of 25–30 m spatial resolution has been recognized as an effective tool for monitoring the spatial and temporal dynamics of forest cover at different scales. However, the precise mapping of forest cover over fragmented landscapes is complicated and requires special consideration. We have evaluated the performance of four global forest products of 25–30 m spatial resolution within three flatland subregions of Ukraine that have different forest cover patterns. We have explored the relationship between tree cover extracted from the global forest change (GFC) and relative stocking density of forest stands and justified the use of a 40% tree cover threshold for mapping forest in flatland Ukraine. In contrast, the canopy cover threshold for the analogous product Landsat tree cover continuous fields (LTCCF) is found to be 25%. Analysis of the global forest products, including discrete forest masks Global PALSAR-2/PALSAR Forest/Non-Forest Map (JAXA FNF) and GlobeLand30, has revealed a major misclassification of forested areas under severe fragmentation patterns of landscapes. The study also examined the effectiveness of forest mapping over fragmented landscapes using dense time series of Landsat images. We collected 1548 scenes of Landsat 8 Operational Land Imager (OLI) for the period 2014–2016 and composited them into cloudless mosaics for the following four seasons: yearly, summer, autumn, and April–October. The classification of images was performed in Google Earth Engine (GEE) Application Programming Interface (API) using random forest (RF) classifier. As a result, 30 m spatial resolution forest mask for flatland of Ukraine was created. The user’s and producer’s accuracy were estimated to be 0.910 ± 0.015 and 0.880 ± 0.018, respectively. The total forest area for the flatland Ukraine is 9440.5 ± 239.4 thousand hectares, which is 3% higher than official data. In general, we conclude that the Landsat-derived forest mask performs well over fragmented landscapes if forest cover of the territory is higher than 10–15%. Full article

Ukraine is a country of the Mid-Latitude ecotone—a transition zone between forest zone and forestless dry lands. Availability of water defines distribution of the country’s forests and decreases their productivity towards the south. Climate change generates a particular threat for Ukrainian forests and stability of agroforestry landscapes. This paper considers the impacts of expected climate change on vulnerability of Ukrainian forests using ensembles of global and regional climatic models (RCM) based on Scenarios B1, A2, A1B of the Intergovernmental Panel for Climate Change, and a “dry and warm” scenario A1B+T−P (increasing temperature and decreasing precipitation). The spatially explicit assessment was provided by RCM for the WMO standard period (1961–1990), “recent” (1991–2010) and three future periods: 2011–2030, 2031–2050 and 2081–2100. Forest-climate model by Vorobjov and model of amplitude of flora’s tolerance to climate change by Didukh, as well as a number of specialized climatic indicators, were used in the assessment. Different approaches lead to rather consistent conclusions. Water stress is the major limitation factor of distribution and resilience of flatland Ukrainian forests. Within Scenario A1B, the area with unsuitable growth conditions for major forest forming species will substantially increase by end of the century occupying major part of Ukraine. Scenario A1B+T−P projects even a more dramatic decline of the country’s forests. It is expected that the boundary of conditions that are favorable for forests will shift to north and northwest, and forests of the xeric belt will be the most vulnerable. Consistent policies of adaptation and mitigation might reduce climate-induced risks for Ukrainian forests. Full article