Smoke & Air Quality
Fire & Smoke Models
Lidar-data processing techniques are analyzed, which allow determining smoke-plume heights and their dynamics and can be helpful for the improvement of smoke dispersion and air quality models. The data processing algorithms considered in the paper are based on the analysis of two alternative characteristics related to the smoke dispersion process: the regularized intercept function, extracted directly from the recorded lidar signal, and the square-range corrected backscatter signal, obtained after determining and subtracting the constant offset in the recorded signal. The analysis is performed using experimental data of the scanning lidar obtained in the area of prescribed fires.