An Enhanced Smoke Detection Using MODIS Measurements

Smoke emitted from wildfire fires or prescribed fires is one of the major pollutions that pose a risk to human health and affect the air quality significantly. The remote sensing technique has been demonstrated as an efficient approach for detecting and tracing smoke plume. As a mixture pollutant, smoke does not have stable spectral signature because of diversified component mixing levels in different situation, but it has some particular characteristics different from others such as cloud, soil, water and so on. In earlier studies, we have already developed a multi-threshold algorithm to detect smoke in the eastern United States by combining both MODIS reflective solar bands and thermal emissive bands measurements. In order to apply out approach to global scale, we have enhanced the smoke detection algorithm by taking the land surface type into account. Smoke pixels will be output as well as the confidence in the quality of product in final result. In addition, smoke detection is also helpful to fire detection. With current fire detection algorithm, some small and cool fires can not be detected. However, understanding the features and spread direction of smoke can provide us a potential way to identify these fires.