Open Access

Black-Bridge data in the detection of forest area changes in the example of Sudety and Beskidy


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Two change detection techniques (NDVI differencing and post-classification analysis) were compared, in order to detect canopy cover changes in forests on the area of twelve forest districts in the Sudety and West Beskidy Mountains in Poland, using 2012 and 2013 Black-Bridge satellite images. Although the classification accuracy of the respective images was high (about 95%), the accuracy of the difference in bi-temporal images was much worse because of the short time between the dates of images and the imperfection of the algorithm calculating the unclear boundary between the forest and no-forest areas. NDVI differencing method and thresholding brought much better overall results, although roads, clouds and fogs caused much problem performing pseudo-changes.

eISSN:
2199-5907
ISSN:
0071-6677
Language:
English
Publication timeframe:
4 times per year
Journal Subjects:
Life Sciences, Plant Science, Medicine, Veterinary Medicine