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· Drawing insights from studies like those in Myanmar (see https://www.sciencedirect.com/science/article/pii/S004896972101826X#bb0410), using very-high-resolution satellite imageries to classify land cover changes in conflict zones. The classification of land cover was divided into five main classes: Forest, Mangrove, Cropland (Paddy Field), Barren Soil, and vegetation. And using VHRI data, a total of seven categories: Residential Area, Forest, Barren/Scrubland, Development (roads and large infrastructures), Planted/Cultivated, Water/Wetland, and Burned Area were classified based on the objective of the study. A similar approach could be applied to Syria, identifying areas most affected by conflict since 2011, something similar to these charts:
The text was updated successfully, but these errors were encountered:
This analysis has been done using MODIS and Dynamic World Laand Cover datasets to show change in land use pre war and present years.
Generating yearly cropland area statistics and plotting yearly trend across years.
Generating maps to show cropland change from 2010 to 2011 (MODIS)
Map to show cropland area change from 2016 (since DW dataset is available since then) to years 2023 and 2024 respectively.
· Drawing insights from studies like those in Myanmar (see https://www.sciencedirect.com/science/article/pii/S004896972101826X#bb0410), using very-high-resolution satellite imageries to classify land cover changes in conflict zones. The classification of land cover was divided into five main classes: Forest, Mangrove, Cropland (Paddy Field), Barren Soil, and vegetation. And using VHRI data, a total of seven categories: Residential Area, Forest, Barren/Scrubland, Development (roads and large infrastructures), Planted/Cultivated, Water/Wetland, and Burned Area were classified based on the objective of the study. A similar approach could be applied to Syria, identifying areas most affected by conflict since 2011, something similar to these charts:
The text was updated successfully, but these errors were encountered: