Abstract
In this article, we investigated the detection of forest vegetation changes during the period of 2017 to 2019 in the Low Tatras National Park (Slovakia) and the Sumava National Park (Czechia) using Sentinel-2 data. The evaluation was based on a time-series analysis using selected vegetation indices. The case studies represented five different areas according to the type of the forest vegetation degradation (one with bark beetle calamity, two areas with forest recovery mode after a bark beetle calamity, and two areas without significant disturbances). The values of the trajectories of the vegetation indices (normalized difference vegetation index (NDVI) and normalized difference moisture index (NDMI)) and the orthogonal indices (tasseled cap greenness (TCG) and tasseled cap wetness (TCW)) were analyzed and validated by in situ data and aerial photographs. The results confirm the abilities of the NDVI, the NDMI and the TCW to distinguish disturbed and undisturbed areas. The NDMI vegetation index was particularly useful for the detection of the disturbed forest and forest recovery after bark beetle outbreaks and provided relevant information regarding the health of the forest (the individual stages of the disturbances and recovery mode). On the contrary, the TCG index demonstrated only limited abilities. The TCG could distinguish healthy forest and the gray-attack disturbance phase; however, it was difficult to use this index for detecting different recovery phases and to distinguish recovery phases from healthy forest. The areas affected by the disturbances had lower values of NDVI and NDMI indices (NDVI quartile range Q2–Q3: 0.63–0.71; NDMI Q2–Q3: 0.10–0.19) and the TCW index had negative values (Q2–Q3: −0.06–−0.05)). The analysis was performed with a cloud-based tool—Sentinel Hub. Cloud-based technologies have brought a new dimension in the processing and analysis of satellite data and allowed satellite data to be brought to end-users in the forestry sector. The Copernicus program and its data from Sentinel missions have evoked new opportunities in the application of satellite data. The usage of Sentinel-2 data in the research of long-term forest vegetation changes has a high relevance and perspective due to the free availability, distribution, and well-designed spectral, temporal, and spatial resolution of the Sentinel-2 data for monitoring forest ecosystems.
Highlights
One possibility to monitor and evaluate forest vegetation is to use Earth Observation (EO) methods
The areas of interest sensed by the Sentinel-2 with the 10-m spatial resolution contained nine times more pixels than the same area sensed by the Landsat 8
We evaluated the changes in forest vegetation affected by the bark beetle in selected national parks in Czechia and Slovakia
Summary
One possibility to monitor and evaluate forest vegetation is to use Earth Observation (EO) methods. Satellites are equipped with various sensors that provide images with information that the human eye cannot see. This is especially useful for detecting the early stages of forest disturbance when there are no visual signs of damage [2]. Other authors evaluated a forest affected by bark beetles with vegetation indices from Landsat images, and the subsequent pixel classification achieved a total accuracy of 80–82% [10] or focused on the classification of three categories of the forest using the maximum likelihood classifier: healthy trees, damaged trees, and grasslands [11]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
