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Spatio-Temporal Dynamic of Disturbances in Planted and Natural Forests for the Saihanba Region of China
Spatio-Temporal Dynamic of Disturbances in Planted and Natural Forests for the Saihanba Region of China
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Spatio-Temporal Dynamic of Disturbances in Planted and Natural Forests for the Saihanba Region of China
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Spatio-Temporal Dynamic of Disturbances in Planted and Natural Forests for the Saihanba Region of China
Spatio-Temporal Dynamic of Disturbances in Planted and Natural Forests for the Saihanba Region of China

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Spatio-Temporal Dynamic of Disturbances in Planted and Natural Forests for the Saihanba Region of China
Spatio-Temporal Dynamic of Disturbances in Planted and Natural Forests for the Saihanba Region of China
Journal Article

Spatio-Temporal Dynamic of Disturbances in Planted and Natural Forests for the Saihanba Region of China

2023
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Overview
Various disturbances like extreme climate events, fires, and insect outbreak severely impact forest ecosystems, and differences are expected between planted and natural forests. However, there is little information on the spatio-temporal dynamics of the disturbances in terms of both forest types. In this study, we used the LandTrendr algorithm to detect disturbances in planted and natural forests in a temperate region of Northern China from 1985 to 2020 using Landsat and Sentinel 2 satellite data. The planted and natural forests suffered severe disturbances in 1994 in the south (park establishment) and in 2012 in the north (severe drought). More than one third of the area of planted (37.5%) or natural (35.8%) forests was highly disturbed. The duration of forest disturbances was mostly 1 to 3 years in terms of planted or natural forests. The NDVI anomaly of the planted forests decreased from 0.24 to −0.08 after drought events, while the reduction was from 0.22 to −0.06 for natural forests. Afterwards, the NDVI anomaly of the planted forests showed a slow upward variation but not for the natural forests. This study allows us to evaluate the response of various forest types to disturbance regimes.