ISSN 2070-7401 (Print), ISSN 2411-0280 (Online)
Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa


Sovremennye problemy distantsionnogo zondirovaniya Zemli iz kosmosa, 2022, Vol. 19, No. 5, pp. 176-189

Time series analyses of forest cover change according to elevation gradient in Gansu province of China

Y. Wang 1 , E.A. Kurbanov 1 , O.N. Vorobiev 1 
1 Volga State University of Technology, Yoshkar-Ola, Russia
Accepted: 20.10.2022
DOI: 10.21046/2070-7401-2022-19-5-176-189
This study used the time series of Landsat satellite data to define the Remote Sensing Environmental Index (RSEI) for the forests around Zhangye city in Gansu province of China from 1990 to 2021 with respect to determining forest cover changes. The elevation gradient of the estimated territory was also studied and analysed. On the basis of traditional regression method, Landsat time series were divided into three RSEI (Remote Sensing Environmental Index) curve trends: logarithmic, logistic, and exponential type, which were used to evaluate the current ecological state of the forest. Over the past 32 years, Zhangye forest area ecology has consistently improved, with 96.0 % of the forest area RSEI increasing, 1.4 % decreasing and 2.6 % remaining unchanged. The linear trend dominates the ecological changes in the forest. The RSEI findings indicate that ecology of 89.9 % of the forest areas is stable, while 10.1 % of the forest areas are unstable. There are obvious differences in RSEI trends and among diverse types of forests according to the elevation gradient. The RSEI rise area shows approximately normal distribution between 2500 and 4500 m, and the RSEI decline area forms a bimodal distribution in the two intervals of 1500–2500 and 3000–4500 m. Through the detailed differentiation of forest cover time series trends, the forest areas that need to be protected are more clearly defined.
Keywords: RSEI, time series, forest cover, monitoring, Landsat, China, trend analysis, logistic model
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