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ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa
CURRENT PROBLEMS IN REMOTE SENSING OF THE EARTH FROM SPACE

  

Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2022, Vol. 19, No. 4, pp. 207-222

Method for protective forest plantations mapping based on multi-temporal high spatial resolution satellite images and Bi-Season Forest Index

S.S. Shinkarenko 1, 2 , S.А. Bartalev 1 , A.A. Vasilchenko 2 
1 Space Research Institute RAS, Moscow, Russia
2 Federal Scientific Center of Agroecology, Complex Meliorations and Agroforestry RAS , Volgograd, Russia
Accepted: 16.08.2022
DOI: 10.21046/2070-7401-2022-19-4-207-222
Protective forest plantations (PFPs) are a very important component of the sustainable functioning of agricultural landscapes. They prevent the development of water and wind erosion. Over the recent decades, the rates of PFPs development in Russia have decreased many times over as compared to the middle of the last century. At the same time, due to natural and anthropogenic factors, the existing PFPs are subject to large-scale degradation processes, while there is a lack of information about their current state. Land cover type information products and forest monitoring systems cover only a part of the PFPs. Protective forest belts with a width of 10–20 m are reflected very fragmentarily on the existing global and national satellite maps of forests. The well-known approaches to the mapping of PFPs are based on expert interpretation of Earth remote sensing (ERS) data of ultra-high spatial resolution or ground-based surveys using GPS receivers. Such methods are time consuming and cannot be applied over large areas. The paper proposes a new approach for mapping PFPs based on multi-season satellite ERS data using the BSFI (Bi-Season Forest Index). The index is calculated as the normalized difference between the minimum NDVI value for the vegetation period and the maximum albedo determined in winter when there is snow cover on the earth’s surface. Pixels with positive values of this index can be attributed to the areas covered with tree vegetation. We have compared the PFP area with the results of expert interpretation of detailed satellite images and widely used information products of satellite land cover mapping. The PFP area was identified on the basis of the BSFI using satellite imagery data obtained by the Sentinel 2 toolbox. The comparative analysis showed a close connection between the results obtained using the Sentinel 2 data and the estimates of the PFP area based on expert interpretation of detailed satellite images. The connection was characterized by a correlation coefficient R = 0.99. The analysis also allowed establishing the value of accuracy of forest identification based on this index at the level of 91 %. The relative error in identifying field-protective forest belts in the 50 m zone around the field boundaries was 9 %. The proposed approach is recommended for mapping PFPs in sparsely forested regions, where it is possible to obtain satellite images of the earth’s surface with snow cover.
Keywords: shelterbelt, tree and shrub vegetation, agrolandscapes, agroforestry, remote sensing, Sentinel 2, NDVI
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