Autor: Boiko, S. - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Specyfika leśnictwa regionów Ukrainy
The specificity of forestry in different regions of the Ukraine
Autorzy:: Boiko, S.
Powiązania:: https://bibliotekanauki.pl/articles/45322.pdf
Data publikacji:: 2012
Wydawca:: Instytut Badawczy Leśnictwa
Tematy:: lesnictwo
Ukraina
Polesie
lasostep
step
Polwysep Krymski
Karpaty
gospodarka lesna
lasy
ciecia pielegnacyjne
ciecia rebne
odnowienia lasu
Źródło:: Leśne Prace Badawcze; 2012, 73, 1
1732-9442
2082-8926
Pojawia się w:: Leśne Prace Badawcze
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Określanie lesistości Polesia Ukraińskiego na podstawie wyników klasyfikacji sezonowych obrazów kompozytowych Landsat 8 OLI
Estimation of forest cover in Ukrainian Polissia using classification of seasonal composite Landsat 8 OLI images
Autorzy:: Lakyda, P.
Myroniuk, V.
Bilous, A.
Boiko, S.
Powiązania:: https://bibliotekanauki.pl/articles/979663.pdf
Data publikacji:: 2019
Wydawca:: Polskie Towarzystwo Leśne
Tematy:: lesnictwo
Ukraina
Polesie
lesistosc
teledetekcja
zdjecia satelitarne
satelita Landsat 8 OLI
forest cover
remote sensing
random forest
ikonos−2
ndvi
Opis:: Training dataset for modelling of forest cover was created after classification of multispectral satel− lite 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.
Źródło:: Sylwan; 2019, 163, 09; 754-764
0039-7660
Pojawia się w:: Sylwan
Dostawca treści:: Biblioteka Nauki

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