The influence of drought on remote sensing indicators of hornbeam and mixed coniferous forest in the Młochowski Forest – analysis of Sentinel-2 satellite images of protected and economic forests in 2017–2021
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Keywords
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NDWI, MSI, Sentinel-2, mixed coniferous forest, oak-hornbeam forest., NDVI, drought
Abstract
The purpose of this paper was to describe processes that took place in the Łowicz-Błonia plain during the long-term drought of 2018 and the series of short-term droughts in 2019. For our analysis we used multispectral satellite images of highground hornbeam and mixed coniferous forest in the Młochowski Forest from 2017–2021. Sentinel-2 images provided the means to investigate the impact of mild droughts on the values of the NDVI ( Normalized Difference Vegetation Index ), NDWI ( Normalized Difference Water Index ), and MSI ( Moisture Stress Index ) as well as their monthly variability and differences between forest divisions. During periods without drought, the variability of all three indices was typical for each phase of the vegetation cycle: in the spring months the value of NDVI and MSI increased, NDWI decreased. During the autumn months, the behavior of the indicators reversed. In the period of long-term drought in 2018, the NDWI was higher in forest divisions with a species composition characteristic of a mixed coniferous forest compared to divisions with a higher share of deciduous trees such as oaks and hornbeams, including the rigorously protected area of high–hornbeam forest. NDWI was the only index to show a downward trend during mild droughts, while during moderate droughts, also a decrease in NDVI and MSI was observed. This was most clearly seen in deciduous forests. We did not observed any correlation of NDVI, NDWI, or MSI with the protection status of the forest or the absence thereof.
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How to Cite
Kotlarz, Jan. “The Influence of Drought on Remote Sensing Indicators of Hornbeam and Mixed Coniferous Forest in the Młochowski Forest – Analysis of Sentinel-2 Satellite Images of Protected and Economic Forests in 2017–2021”. Leśne Prace Badawcze, vol. 82, no. 3, June 2022, pp. 87-100, doi:10.48538/lpb-2021-0010.
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