The DLR FireBIRD Small Satellite Mission: Evaluation of Infrared Data for Wildfire Assessment

Nolde, Michael; Plank, Simon; Richter, Rudolf; Klein, Doris; Riedlinger, Torsten

doi:10.3390/rs13081459

Cited by 9 publications

(5 citation statements)

References 23 publications

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“…The TET-1 sensor however shows a clear underestimation of FRP by almost a factor 2. This is not in agreement with the work of [53] which reported a 31% concordance between TET-1 and VIIRS using the same FRP formulation and synchronized overpasses of the same fire. As the TET-1 FRP seems to scale properly between Skukuza6 and Shabeni3 FRP, this does not seem to be a saturation problem.…”

Section: Application To Fire Radiative Power Time Series Estimationcontrasting

confidence: 95%

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Orthorectification of Helicopter-Borne High Resolution Experimental Burn Observation from Infra Red Handheld Imagers

et al. 2021

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To pursue the development and validation of coupled fire-atmosphere models, the wildland fire modeling community needs validation data sets with scenarios where fire-induced winds influence fire front behavior, and with high temporal and spatial resolution. Helicopter-borne infrared thermal cameras have the potential to monitor landscape-scale wildland fires at a high resolution during experimental burns. To extract valuable information from those observations, three-step image processing is required: (a) Orthorectification to warp raw images on a fixed coordinate system grid, (b) segmentation to delineate the fire front location out of the orthorectified images, and (c) computation of fire behavior metrics such as the rate of spread from the time-evolving fire front location. This work is dedicated to the first orthorectification step, and presents a series of algorithms that are designed to process handheld helicopter-borne thermal images collected during savannah experimental burns. The novelty in the approach lies on its recursive design, which does not require the presence of fixed ground control points, hence relaxing the constraint on field of view coverage and helping the acquisition of high-frequency observations. For four burns ranging from four to eight hectares, long-wave and mid infra red images were collected at 1 and 3 Hz, respectively, and orthorectified at a high spatial resolution (<1 m) with an absolute accuracy estimated to be lower than 4 m. Subsequent computation of fire radiative power is discussed with comparison to concurrent space-borne measurements.

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Section: Application To Fire Radiative Power Time Series Estimationcontrasting

confidence: 95%

“…The KNP14 fires took place in the early days of the TET-1 operation, a bias might has been present and corrected later. The oldest fire in [53] is from 2016. Using only the four fires from the KNP14 data set, it is difficult to draw any conclusion on the upscaling of FRP measurement.…”

Section: Application To Fire Radiative Power Time Series Estimationmentioning

confidence: 99%

Orthorectification of Helicopter-Borne High Resolution Experimental Burn Observation from Infra Red Handheld Imagers

et al. 2021

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“…• Stationary OI: Events such as wild fires or gas flares occur with high frequency around the globe and the latter also with low seasonal variability. [7][8][9] While gas flares provide a temperature of around 1800 K at maximum 9 , wild fires have an average temperature of around 1000 K 10,11 . According to Wien's displacement law, both targets provide their radiation peak in the Short-Wave Infrared (SWIR) to MWIR range.…”

Section: Objects Of Interest For Validation Purposesmentioning

confidence: 99%

Data pipeline of a multi-spectral satellite experiment for object detection and artificial intelligence-based processing

Müller,

Swami,

Haser

et al. 2023

Automatic Target Recognition XXXIII

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Recent developments in the military domain introduce the need to detect and track hypersonic glide vehicles in Earth's atmosphere.The Multispectral Object Sensing by Artificial Intelligence-processed Cameras (MOSAIC) experiment is part of the small-satellite ATHENE-1 of the Universität der Bundeswehr München. The primary scientific objective of MOSAIC is to demonstrate reliable detection, identification a nd t racking o f h ypersonic g lide v ehicles using primarily a cooled infrared camera and complementary a visual camera. To cope with a large amount of data from both high-resolution cameras in real-time, state-of-the-art computer vision on-board processing methods are used for detection and tracking. The secondary scientific objective is to investigate the efficiency and reliability of Artificial Intelligence (AI) based image processing algorithms and data compression for space a pplications. This is of particular importance given the high volumes and rates of data. The application of such algorithms requires a reliable and resource-efficient On -Board Co mputer (O BC) th at ca n wi thstand th e ha rsh sp ace environment. The approach outlined in this paper envisions a dedicated OBC to manage the AI-based experiments of the satellite, called the Artificial Intelligence capable On-Board Computer ( AI-OBC). The AI-OBC includes multiple hardware-based AI accelerators to meet the computational requirements and ensure real-time processing for object detection and tracking. This paper describes the structure of the data processing pipeline and includes the AI-OBC architecture with its connections to both the cameras and the platform's OBC. Further, the study discusses the training and validation steps of the intended use-cases.

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“…The possibility to calculate the FRE over the fire diurnal cycles may significantly improve, for instance, the estimation accuracy of Dry Matter Burned (DMB), an important input parameter for the Global Fire Assimilation System (GFAS) [ 11 , 13 ].…”

Section: Capability Of Firebird Class Data For Validation Of the Fire...mentioning

confidence: 99%

The Capabilities of Dedicated Small Satellite Infrared Missions for the Quantitative Characterization of Wildfires

et al. 2022

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The main objective of this paper was to demonstrate the capability of dedicated small satellite infrared sensors with cooled quantum detectors, such as those successfully utilized three times in Germany’s pioneering BIRD and FireBIRD small satellite infrared missions, in the quantitative characterization of high-temperature events such as wildfires. The Bi-spectral Infrared Detection (BIRD) mission was launched in October 2001. The space segment of FireBIRD consists of the small satellites Technologie Erprobungs-Träger (TET-1), launched in July 2012, and Bi-spectral InfraRed Optical System (BIROS), launched in June 2016. These missions also significantly improved the scientific understanding of space-borne fire monitoring with regard to climate change. The selected examples compare the evaluation of quantitative characteristics using data from BIRD or FireBIRD and from the operational polar orbiting IR sensor systems MODIS, SLSTR and VIIRS. Data from the geostationary satellite “Himawari-8” were compared with FireBIRD data, obtained simultaneously. The geostationary Meteosat Third Generation-Imager (MTG-I) is foreseen to be launched at the end of 2022. In its application to fire, the MTG-I’s Flexible Combined Imager (FCI) will provide related spectral bands at ground sampling distances (GSD) of 3.8 µm and 10.5 µm at the sub-satellite point (SSP) of 1 km or 2 km, depending on the used FCI imaging mode. BIRD wildfire data, obtained over Africa and Portugal, were used to simulate the fire detection and monitoring capability of MTG-I/FCI. A new quality of fire monitoring is predicted, if the 1 km resolution wildfire data from MTG-1/FCI are used together with the co-located fire data acquired by the polar orbiting Visible Infrared Imaging Radiometer Suite (VIIRS), and possibly prospective FireBIRD-type compact IR sensors flying on several small satellites in various low Earth orbits (LEOs).

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The DLR FireBIRD Small Satellite Mission: Evaluation of Infrared Data for Wildfire Assessment

Cited by 9 publications

References 23 publications

Orthorectification of Helicopter-Borne High Resolution Experimental Burn Observation from Infra Red Handheld Imagers

Orthorectification of Helicopter-Borne High Resolution Experimental Burn Observation from Infra Red Handheld Imagers

Data pipeline of a multi-spectral satellite experiment for object detection and artificial intelligence-based processing

The Capabilities of Dedicated Small Satellite Infrared Missions for the Quantitative Characterization of Wildfires

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