Remote monitoring of reforestation on the abandoned agricultural lands in the Republic of Mari El using the method of principal component analysis-Reference-Cited by-同舟云学术

Remote monitoring of reforestation on the abandoned agricultural lands in the Republic of Mari El using the method of principal component analysis

Published:2024-08-24 Issue:2 Volume: Page:21-31
ISSN:0205-9614
Container-title:Исследования Земли из космоса
language:
Short-container-title:Issledovanie Zemli iz Kosmosa

Author:

Lezhnin S. A.¹,Gubaev A. V.¹,Vorobev O. N.¹,Kurbanov E. A.¹,Dergunov D. M.¹

Affiliation:

1. Volga State University of Technology

Abstract

The paper presents the results of monitoring natural forest regrowth on abandoned agricultural land in the Middle Volga Region using remote sensing methods. The Mari El Republic was chosen as the test site for this research. The use of modern remote sensing methods makes it possible to identify and evaluate areas of natural forest regrowth on abandoned agricultural lands with higher accuracy and at lower financial and labour costs. Minimum noise fraction transformed images (Landsat-8 OLI-8) were used in a combination of sixth (mid-infrared), fifth (near-infrared) and second (blue) spectral channels for the research. The findings revealed that there is a steady process of mass forest regrowth on abandoned agricultural land in Mari El. The total area of agricultural land used in the research was 763.69 thousand hectares. Reforestation with deciduous species is observed on a territory of 135.5 thousand hectares, which makes up 17.7% of the total area of agricultural land and 49.9% of the territory of fallow land in the Republic of Mari El. Reforestation with coniferous species is observed on 26.7 thousand hectares, which amounts to 3.5% and 9.85%, respectively. Future studies can address anthropogenic and natural impacts on the structure and dynamics of new forest stands. A comprehensive analysis of the density of forest regrowth on abandoned agricultural lands should be carried out using existing maps of agricultural land, population density, and other socio-economic factors.

Publisher

The Russian Academy of Sciences

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