The TUBIN spacecraft launched in June 2021 is tasked with the detection of high-temperature events. To this end, it employs two microbolometer focal plane arrays and a complementary sensor sensitive in the visible range. Using simulated data, a fire detection algorithm was developed. Within the first 18 months of mission operations, several hundred scenes containing wildfires and other high-temperature events were captured. The detected high-temperature events can be categorized into volcanic features, vegetation fires and artificial events such as gas flares. Fire maps were manually created for all scenes meeting the criteria of nadir or close to nadir imaging and the availability of recent calibration data. These maps were validated using secondary space-borne instruments such as MODIS, VIIRS. The individual validation of the data was performed with satellite data with close temporal proximity to the time of image capture. The available fire products feature various ground sampling distances (GSD) mostly lower than the approximately 150 m GSD of the TUBIN sensor suite. The fire detection algorithm is based on the brightness temperature values of the pixels. Through a series of steps, cloud and background pixels are isolated from candidate fire pixels that are further evaluated based on their relative response. This paper evaluates the results from the TUBIN fire detection algorithm on the gathered data and determines the accuracy within the data set.
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