Automatic smoke detection using satellite imagery: preparatory to smoke detection from Insat‐3D

Abstract

Identification of smoke on satellite imagery is a prerequisite to study and retrieve physical, chemical, and optical properties of smoke and also forms a crucial part in fire‐management systems. Automatic detection of smoke is a challenge in itself, owing to the large overlap in the spectral signatures of smoke and other scene types, and it becomes all the more complex over the Indian region owing to less contrast between background and target. In this study, an algorithm, which is based on multiband thresholding technique, employing a conventional as well as a pseudo‐channel, is developed for the Indian region with the help of radiative transfer simulation and is a preparatory exercise for setting up algorithms for application of INSAT 3D imager data. The algorithm has been executed using MODIS data on agricultural fire spread over north‐western India for the year 2005. The outputs are validated using MODIS AOD and Cloud Fraction products, and the results suggest that the algorithm is able to isolate smoke pixels in the presence of other scene types such as clouds, although it performs better in identifying fresh dense smoke as compared with highly diffused smoke.

Acknowledgements

The authors would like to thank Dr V. K. Agarwal, Group Director, Meteorology and Oceanography Group, Dr P. C. Joshi, Head, Atmospheric Sciences Division, and Dr Ajai, Group Director, Marine and Earth Science Group for their encouragement, help and support. The authors would also like to thank the anonymous reviewers for their valuable suggestions and NASA LAADS team for the MODIS data. This work was carried out under the IMDPS Project.