Вісник Київського національного університету імені Тараса Шевченка

ГЕОГРАФІЯ

Bulletin of Taras Shevchenko National University of Kyiv

GEOGRAPHY

LAND COVER CHANGE DETECTION FOR AMALGAMATED TERRITORIAL COMMUNITIES: EXAMPLE OF USING REMOTE SENSING FOR FOREST CLASSIFICATION AND DEFORESTATION DISCLOSURE

Panchenko V.

Taras Shevchenko National University of Kyiv, Kyiv, Ukraine

Abstract:
The study is aimed to apply remote sensing for purposes of land cover detection in researches of new territorial units in Ukraine. The example of forest detection using Landsat images is particularly presented in the study. While the study area presented by Korovyntsi amalgamated territorial community in the Sumy region. The forest classification and deforestation detection have been processed every 5 years from 1990 through 2020.
The Landsat 5, 7, and 8 data from the United States Geological Survey (USGS) have been used for the research. The image choice depended on the date of data availability and reliability, but in time between mid-May to early July. The dataset of 11 total images was processed in the Harris Geospatial Solutions’ Environment for Visualizing Images (ENVI). The data were calibrated by using the ENVI Landsat calibration tool, the atmospheric correction applied by using the ENVI FLAASH tool, and seamless mosaicking was used for some periods with more than one image needed.
Normalized Difference Vegetation Index (NDVI) is the basis for forest classification applied. Comparing remote sensing data from different years and different Landsat satellites allowed not just to identify vegetation type of forest, but also to detect land cover changes. The change detection has been analyzed in two ways. The first method was based on changes in classification status. The second method was based on a difference in NDVI values, while forest classification was held for masking out non-forest areas.
The applied study observed ways of cost-efficient land use research for local communities. Those methods could be used by NGO’s, local activists, citizen scientists, local authorities for improving land use management with the most updated data, and identifying problems of deforestation, in the case of the study presented. Nonetheless, land cover change detection is not limited to forest cover presented in the study. Anyway, in the case of forest detection, Landsat images from different satellites could be compared and present historical data for the rural areas, which had a low research interest in the past, but it changed due to administrative reform in Ukraine and switching governance power to the local communities.

Keywords: remote sensing, land cover change detection, deforestation, rural community.

Language:
English

 

DOI: http://doi.org/10.17721/1728-2721.2020.76-77.15

References:

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Full-text PDF (.pdf)

Suggested citation:

Panchenko V., 2020. Land cover change detection for amalgamated territorial communities: example of using remote sensing for forest classification and deforestation disclosure. Visnyk Kyivskogo nacionalnogo universytetu imeni Tarasa Shevchenka, Geografiya [Bulletin of Taras Shevchenko National University of Kyiv, Geography], 1/2 (76/77), 101-107 (in English, abstr. in Ukranian), doi: 10.17721/1728-2721.2020.76-77.15

Received Editorial Board 28.09.2020
Accepted for publication 
12.11.2020