Earth and Atmospheric Sciences, Department of


Date of this Version

Summer 7-30-2015


Polivka, Thomas N. Improving Nocturnal Fire Detection with the VIIRS Day-Night Band. MS Thesis. University of Nebraska-Lincoln, Lincoln, NE, 2015.


A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Master of Science, Major: Earth and Atmospheric Sciences, Under the Supervision of Professor Jun Wang. Lincoln, Nebraska: August, 2015

Copyright (c) 2015 Thomas N. Polivka


As an important component in the Earth-atmosphere system, wildfires are a serious threat to life and property that—despite improving warning systems—have exacted greater costs in recent years. In addition, they impact global atmospheric chemistry by releasing potent trace gasses and aerosols. Using the Visible Infrared Imaging Radiometer Suite (VIIRS), this study investigates the adjustment of fire pixel selection criteria to include visible light signatures at night, creating the Firelight Detection Algorithm (FILDA). This allows for greatly improved detection of smaller and cooler fires from satellite observations. VIIRS scenes with coincident Advanced Spaceborne Thermal Emission and Reflection (ASTER) overpasses are examined after applying the operational VIIRS fire product algorithm and including a modified candidate fire pixel selection approach, which lowers the 4 μm brightness temperature threshold from 305 K but includes a minimum day-night band (DNB) radiance. FILDA is tested by applying it to scenes in different environments, including large forest fires like the Rim Fire in California and High Park fire in Colorado, in addition to gas flares. A large increase in the number of detected fire pixels is observed with small non-agricultural wildfires, as verified with the finer-resolution ASTER data (90 m). Quantitative use of the DNB to improve detection of these smaller fires could lead to reduced warning and response times as well as provide more accurate quantification of biomass burning emissions at night.

Adviser: Jun Wang