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Redukcja przyrostów rocznych daglezji zielonej i sosny pospolitej w zależności od warunków termiczno-pluwialnych w Nadleśnictwie Kędzierzyn

100%
Ziemianska M., Kalbarczyk R., Bilous A., Leshchenko O.
Sylwan
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2019
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tom 163
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nr 03
The main objective of the research was to evaluate the incremental response of Douglas fir and Scots pine subjected to strong environmental stress to variable thermal and precipitation conditions. We also attempted to determine periods of tree−ring width reduction caused by strong anthropopressure associated with the activities of nearby industrial plants, which are burdensome for the environment. The studied forest stands are located in the Kędzierzyn Forest District, in Kotlarnia forestry (50°27‵59‵‵N, 18°38‵42‵‵E) approximately 8 km away from the nitrogen production plants. We used standard methodology applied in the dendrochronological studies with the support of the TSAP−Win, Cofecha, Arstan and Quercus 06.01 softwares. We found that Douglas fir and Scots pine stands growing in the permanently damaged zone due to the adverse effects of industry responded to meteorological conditions in a manner typical of the species. In the study of the relationship between weather and growth, thermal and precipitation conditions were more important in the current year than in the year preceding the increment. A similar distribution of reductions and periods of partial regeneration in both species were also observed. In the same multi−annual period of 1961−1991 deeper reductions of annual increments were observed in Douglas fir (>70%) than in Scots pine (in the range of 50−70%). Conditions, in which trees grew in the Kędzierzyn Forest District, contributed to the decrease in annual increments of both Douglas fir and Scots pine, while the previous species turned out to be a more sensitive one, which had been indicated by other researchers ealier.
2
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Określanie lesistości Polesia Ukraińskiego na podstawie wyników klasyfikacji sezonowych obrazów kompozytowych Landsat 8 OLI

100%
Lakyda P., Myroniuk V., Bilous A., Boiko S.
Sylwan
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2019
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tom 163
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nr 09
Training dataset for modelling of forest cover was created after classification of multispectral satellite imagery IKONOS−2 with spatial resolution 3.2 m (acquisition date – 12.08.2011). As a result, we created binary forest cover map with 2 categories: ‘forest’ and ‘not−forest’. That allowed us to compute the tree canopy cover for each pixel of Landsat 8 OLI, using vector grid with cell size of 30×30 m. Classification model was developed using training dataset that included 17,000 observations, 10,000 of them represented results of IKONOS−2 classification. Aiming to avoid errors of agricultural lands inclusion into forest mask because of lack of data, additionally we collected about 7000 random observations with canopy cover 0% that had been evenly distributed within unforested area. Random Forest (RF) model we developed allowed us to create continuous map of forests within study area that represents in each pixel value of tree canopy closeness (0−100%). To convert it into a discrete map, we recoded all values less than 30% as ‘no data’ and values from 30 to 100% as 1. Forest mask for two selected administrative districts of Chernihiv region (NE Ukraine) was created after screening map from small pixel groups that covered area less than 0.5 ha. Obtained results were compared with Global Forest Change (GFC) map and proved that GFC data can be used for forest mapping with tree canopy closeness threshold 40%. On considerable areas of abandoned agricultural lands in the analysed regions of Ukraine, forest stands are formed by Scots pine, silver birch, black alder and aspen. Existence of such forests substantially increases (on 6−8%) the forested area of Gorodnya and Snovsk districts of Chernihiv region – comparing to official forest inventory data. However, such stands are not protected and have high risks to be severed by wildfires, illegal cuttings with aim to renew the agricultural production, by diseases, insects and other natural disturbances.
3
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Application of various approaches of multispectral and radar data fusion for modelling of aboveground forest biomass

88%
Movchan D., Bilous A., Yelistratova L., Apostolov A., Hodorovsky A.
Folia Forestalia Polonica. Series A . Forestry
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2023
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tom 65
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nr 2
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