We are excited to share with you an article published recently that glimpses into the details of eLENS development, and aims to test the capability of the developed Earth observation (EO) algorithm and corresponding processing chain to detect deforestation using Sentinel-2 imagery. Such an algorithm is a key component of the EO services of the eLENS portal that relies on the Copernicus data to provide cost-effective and easily available information to its users to detect land-use change.

The deforestation detection algorithm was tested on the bird habitats in Montenegro, where the threats and monitoring requirements were previously identified through the users’ consultation. The sites of Velika Plaža, Ulcinj Salina, Nikšićko polje, and the Lake Skadar National Park are rich in biodiversity and in need of monitoring of construction, illegal logging, and water level fluctuations, among other environmental variables.
The analysis of imagery from 2016 to 2019 showed that the studied landscapes experience little change in terms of forest removal with 3% of forest loss in the area of the Velika Plaža and Skadar Lake sites. The study area around the Nikšićko polje had 4,73% of the forest cover destructed, likely by forest fires during 2016-2019 due to excess human pressure.
This research proved that the proposed approach:
- Is efficient for deforestation detection;
- Is appropriate for the short time series currently available from the Sentinel-2 satellite; and
- Could help identify potential environmental violations and generate the deforestation alerts.
The enviroLENS partners, the Aristotle University of Thessaloniki (AUTH) and GeoVille led the research and published the resulting article in the International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Read the full article here
Full article citation: Patias, P., Mallinis, G., Tsioukas, V., Georgiadis, C., Kaimaris, D., Tassopoulou, M., Verde, N., Dohr, M., and Riffler, M.: EARTH OBSERVATIONS AS A TOOL FOR DETECTING AND MONITORING POTENTIAL ENVIRONMENTAL VIOLATIONS AND POLICY IMPLEMENTATION, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 1491–1496, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-1491-2020, 2020.