Improved algorithm for adaptive fire detection using MODIS data

Shuai Ge; Jiayin Li

doi:10.1117/12.2667537

10 February 2023 Improved algorithm for adaptive fire detection using MODIS data

Shuai Ge, Jiayin Li

Proceedings Volume 12552, International Conference on Geographic Information and Remote Sensing Technology (GIRST 2022); 1255233 (2023) https://doi.org/10.1117/12.2667537
Event: International Conference on Geographic Information and Remote Sensing Technology (GIRST 2022), 2022, Kunming, China

Abstract

The Moderate Resolution Imaging Spectroradiometer (MODIS) has 36 channels covering the visible to far infrared band range with a resolution of 250 m to 1 km, and is important for detecting fires in large areas. Traditional fire detection algorithms mainly rely on thermal infrared channels using threshold or contextual methods. Such methods usually fail to detect small fire and often misidentify high-temperature objects on the surface. This paper proposes a new adaptive fire detection algorithm, which focuses on two methods to improve the accuracy of fire detection. First, single-channel and multi-channel test conditions were added and new contextual algorithms were adopted; second, a method for weighting the fire test conditions based on the test conditions for differences in the sensitivity to fire was proposed. This method reduces the issue of small fires being overlooked because they do not satisfy certain test conditions. In addition, a priori database was built using twelve-year US wildfire reference records and highest confidence fire data in MODIS fire products, adaptive thresholds suitable for fires were selected using the bubble sorting method based on the radiation characteristics of global fires. Testing results show that the improved algorithm improved the accuracy of small fire identification and reduced the false detection rate of pseudo-fires.

Citation Download Citation

Shuai Ge and Jiayin Li "Improved algorithm for adaptive fire detection using MODIS data", Proc. SPIE 12552, International Conference on Geographic Information and Remote Sensing Technology (GIRST 2022), 1255233 (10 February 2023); https://doi.org/10.1117/12.2667537

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KEYWORDS

Fire

MODIS

Flame detectors

Detection and tracking algorithms

Algorithm testing

Combustion

Mid-IR

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