Ola Ali Merhej1*
1 General Organization of Remote Sensing (GORS), Lecturer- Tishreen University, Latakia, Syria.
(*Corresponding author: Ola Merhej, Email: olamerhej@gmail.com, mobile: 0932044199).
Received: 6/ 2/ 2025 Accepted: 15/ 6/ 2025
Abstract
The rapid change in land cover has become a major problem resulting from various factors in the Cedar and Fir protected area in Syria, even though it is under protection. This study aimed at evaluating the usefulness of monitoring changes in land cover in the Cedar and Fir protected area in Syria during the last 5 years (2018-2023), using two imageries from the Sentinel-2A (S2A) satellite and applying the Random Forest “RF” algorithm within Google Earth Engine (GEE) platform. The overall accuracy (OA) of classification in the resulting land cover maps was 93.4% in the 2018 map, and 92.7% in the 2023 map. The maps showed a decrease in forest cover in the protected area by 36.07% during the study period. In contrast, the results strongly support the use of the GEE platform and Sentinel 2A satellite data in parallel with the random forest algorithm to enhance the accuracy of land cover classification in mountainous regions. This study recommended the need to take rapid action to preserve the rare natural resources in the protected area.
Keywords: Cedar and Fir Protected Area, Google Earth Engine Platform, Random Forest, Remote Sensing, Land Cover Maps.
Full paper in English: PDF