Algorithm and assessment work of active fire detection based on FengYun-3C/VIRR
Abstract
The wildfire is one of the most destructive and uncontrollable disasters and causes huge environmental, ecological, social effects. To better serve scientific research and practical fire management, an algorithm and corresponding validation work of active fire detection based on FengYun-3C/VIRR data, which is an optical sensor onboard the Chinese polar-orbiting meteorological sun-synchronous satellite, is hereby introduced. While the main structure heritages the `contextual algorithm', some new concepts including `infrared channel slope' are introduced for better adaptions to different situations. The validation work contains three parts: 1) comparing with the current FengYun-3C fire product GFR; 2) comparing with MODIS fire products; 3) comparing with Landsat series data. Study areas are selected from different places all over the world from 2014 to 2016. The results showed great improvement on GFR files on accuracy of both positioning and detection rate. In most study areas, the results match well with MODIS products and Landsat series data (with over 85% match degree) despite the differences in imaging time. However, detection rates and match degrees in Africa and South-east Asia are not satisfied (around 70%), where the occurrences of numerous small fire events and corresponding smokes may strongly affect the results of the algorithm. This is our future research direction and one of the main improvements requires achieving.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2017
- Bibcode:
- 2017AGUFM.B13D1790L
- Keywords:
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- 0414 Biogeochemical cycles;
- processes;
- and modeling;
- BIOGEOSCIENCES;
- 0434 Data sets;
- BIOGEOSCIENCES;
- 0466 Modeling;
- BIOGEOSCIENCES;
- 1630 Impacts of global change;
- GLOBAL CHANGE