Abstract
The German Aerospace Center’s (DLR) TIMELINE project aims to develop an operational processing and data management environment to process 30 years of National Oceanic and Atmospheric Administration (NOAA)—Advanced Very High Resolution Radiometer (AVHRR) raw data into L1b, L2 and L3 products. This article presents the current status of the fully automated L2 active fire hotspot detection processor, which is based on single-temporal datasets in orbit geometry. Three different probability levels of fire detection are provided. The results of the hotspot processor were tested with simulated fire data. Moreover, the processing results of real AVHRR imagery were validated with five different datasets: MODIS hotspots, visually confirmed MODIS hotspots, fire-news data from the European Forest Fire Information System (EFFIS), burnt area mapping of the Copernicus Emergency Management Service (EMS) and data of the Piedmont fire database.
Highlights
Forest fires are a natural component which regulate the evolution, productivity and biodiversity of natural plant communities and ecosystems since millennia [1,2]
The model consists of a 50 × 50 pixel testing area with each pixel characterized by a size of 1 km2, which is equal to the spatial resolution of Advanced Very High Resolution Radiometer (AVHRR) at nadir conditions
The following parameters were applied to all four fires: the temperature of the fire itself was varied among 600 K, 800 K and 1000 K; and the background temperature within the fire pixel and the surrounding pixels was varied among 240 K, 255 K, 270 K, 285 K and 300 K
Summary
Forest fires are a natural component which regulate the evolution, productivity and biodiversity of natural plant communities and ecosystems since millennia [1,2]. Since humans started to change flora and fauna, and set artificial fires, wildfires have become one of the most devastating natural hazards worldwide. They destroy environment and property, impact air quality, contribute to global warming and even threaten lives [4,5,6,7,8,9,10,11,12,13,14]. Ongoing observation is relevant: for a detailed understanding of fire ecosystems, the terrestrial-atmospheric interactions and the impact of wildfires to global change, it is of utmost importance to map historical fire events accurately, reliably, objectively and consistently [15].
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