Assessment of the post-fire forest restoration dynamics in the Olekminsky State Nature Reserve (Russia) according to data of Landsat satellite images

Nature Conservation Research: Zapovednaâ Nauka. 2019;4(Suppl.1):1-10 DOI 10.24189/ncr.2019.014

 

Journal Homepage

Journal Title: Nature Conservation Research: Zapovednaâ Nauka

ISSN: 2500-008X (Print)

Publisher: Fund for Support and Development of Protected Areas

LCC Subject Category: Geography. Anthropology. Recreation

Country of publisher: Russian Federation

Language of fulltext: Russian, English

Full-text formats available: PDF

 

AUTHORS

Yuri F. Rozhkov (State Nature Reserve «Olekminsky»)
Maria Yu. Kondakova (Hydrochemical Institute)

EDITORIAL INFORMATION

Double blind peer review

Editorial Board

Instructions for authors

Time From Submission to Publication: 13 weeks

 

Abstract | Full Text

The use of time series of satellite images allows us to trace the dynamics in the processes of reforestation and forest formation. We estimated the use of the results of cluster analysis of the pixel distribution in the monitoring of post-fire forest restoration. We processed multispectral mid-resolution satellite images (and their fragments) of Landsat 8, Landsat TM/ЕТМ+, Landsat MSS taken in 1973–2016 using the following cluster analysis tools: unmanaged ISODATA classification and thematic difference. The thematic difference was calculated between the results of classifying data into two, four, six, and ten classes. We demonstrated that the post-fire forest restoration takes place in different burned areas with different wildfire intensity. It also depends on the proportion of post-fire wastelands. For example, greater areas of post-fire disturbance have been noted in conditions of a larger proportion of post-fire wastelands. In severely fire-damaged areas, the post-fire vegetation restoration was more intense than in slightly fire-damaged. We calculated the index characterising the forest cover in burned areas. We demonstrated its increase over the time. We considered the relationship between the change in the index characterising the forest cover over the time and the thematic difference of pixels.