Related Experiment Video
Updated: Sep 2, 2026

Collecting and Processing Drone-based Remotely Sensed Data for Use in Forest Recovery Monitoring
Published on: October 24, 2025
Assessing trends and drivers of burned areas in forest areas in the Kurdistan Region
Azad Rasul1,2, Ismahil Shkur Zahir3
1Department of Geography, Soran University, Soran, Erbil, Iraq. azad.rasul@soran.edu.iq.
Abstract:
Wildfires pose an escalating threat to the oak-dominated forests of the Kurdistan Region of Iraq, where long-term fire trends and predictors have remained poorly quantified. This study assessed interannual variability and long-term trends in total and forest-specific burned area from 2001 to 2024, examined spatial differences, and identified primary climatic predictors of fire extent using MODIS MCD64A1 Version 6.1 burned-area data masked to a 2024 NDVI-based forest mask (~ 10,660 km2). Across the entire Kurdistan Region, burned area averaged 687 km2 year⁻1 (SD = 640 km2), totalled 16,486 km2 over the 24-year period, and exhibited a statistically significant upward trend of 31 km2 year⁻1 (Theil-Sen slope; Mann-Kendall p = 0.026). Forest burned area averaged 356 km2 year⁻1 (equivalent to an annual burn rate of 3.3% of forest cover), displayed a significant increasing trend of 15 km2 year⁻1 (Mann-Kendall p = 0.021), and reached a cumulative 8541 km2, with Duhok and Sulaymaniyah together accounting for 77% of cumulative forest burned area and showing the strongest upward trends. Maximum temperature and drought severity were the dominant climatic predictors: each 1 °C rise in monthly maximum temperature increased expected burned area by 14.3% (incidence-rate ratio [IRR] = 1.143, p < 0.001). Drought severity (negated PDSI, positive values = greater drought severity) demonstrated a dual effect on fire dynamics. In the count model predicting fire magnitude, drought was significantly and negatively associated with burned area (IRR = 0.787, p < 0.001), reducing expected fire size by 21.3% per unit increase in drought severity; the zero-inflation component showed a similar but non-significant trend (p = 0.417). Model results showed pronounced non-linear escalation of predicted fire activity above ~ 32 °C and negated PDSI > 2 (severe drought conditions).
