Gas flaring is a disposal process widely used in the oil extraction and processing industry. It consists in the burning of unwanted gas at the tip of a stack and due to its thermal characteristic and the thermal emission it is possible to observe and to quantify it from space. Spaceborne observations allows us to collect information across regions and hence to provide a base for estimation of emissions on global scale. We have successfully adapted the Visible Infrared Imaging Radiometer Suite (VIIRS) Nightfire algorithm for the detection and characterisation of persistent hot spots, including gas flares, to the Sea and Land Surface Temperature Radiometer (SLSTR) observations on-board the Sentinel-3 satellites. A hot event at temperatures typical of a gas flare will produce a local maximum in the night-time readings of the shortwave and mid-infrared (SWIR and MIR) channels of SLSTR. The SWIR band centered at 1.61 $\mathsf{\mu }$m is closest to the expected spectral radiance maximum and serves as the primary detection band. The hot source is characterised in terms of temperature and area by fitting the sum of two Planck curves, one for the hot source and another for the background, to the radiances from all the available SWIR, MIR and thermal infra-red channels of SLSTR. The flaring radiative power is calculated from the gas flare temperature and area. Our algorithm differs from the original VIIRS Nightfire algorithm in three key aspects: (1) It uses a granule-based contextual thresholding to detect hot pixels, being independent of the number of hot sources present and their intensity. (2) It analyses entire clusters of hot source detections instead of individual pixels. This is arguably a more comprehensive use of the available information. (3) The co-registration errors between hot source clusters in the different spectral bands are calculated and corrected. This also contributes to the SLSTR instrument validation. Cross-comparisons of the new gas flare characterisation with temporally close observations by the higher resolution German FireBIRD TET-1 small satellite and with the Nightfire product based on VIIRS on-board the Suomi-NPP satellite show general agreement for an individual flaring site in Siberia and for several flaring regions around the world. Small systematic differences to VIIRS Nightfire are nevertheless apparent. Based on the hot spot characterisation, gas flares can be identified and flared gas volumes and pollutant emissions can be calculated with previously published methods.

Space-borne infrared remote sensing specifically for the detection and characterization of fires has a long history in the DLR Institute of Optical Sensor Systems. In the year 2001, the first DLR experimental satellite, Bi-spectral Infrared Detection (BIRD), was launched after an intensive test period with cooled IR sensor systems on airborne systems. The main basis for the development of the FireBIRD mission with the two satellites, Technology Erprobungsträger No 1 (TET-1) and Bi-spectral-Infrared Optical System (BIROS), was the already space-proven sensor and satellite technology with successfully tested algorithms for fire detection and quantification in the form of the so-called fire radiation power (FRP). This paper summarizes the development principles for the IR sensor system of FireBIRD and the most critical design elements of the TET-1 and BIROS satellites, especially concerning the attitude control system—all very essential tools for high-resolution infrared fire monitoring. Key innovative tools necessary to increase the agility of small IR satellites are discussed.

More than 10 years after the launch of DLR’s first small satellite BIRD, a follow on project called FireBird was started. Based on the success of the BIRD mission, the main scientific goal- the investigation of high temperature events and their impact on the climatic processes- will be continued but in consideration to the advantages given by the operation of a constellation of two small satellites. The first of these satellites- TET-1- was launched on June 22nd 2012. The launch of the second satellite- BIROS- is scheduled for spring 2016. Both satellites are mainly dedicated to the observation and analysis of high temperature events such as wildfires and volcanoes. The outstanding feature of the FireBird Infrared Instruments is their higher ground sample resolution and dynamic range compared to systems such as MODIS. This enables the detection of smaller fire events and improves the quality of the quantitative analysis. The analysis of the high temperature events is based on the Bi- Spectral Method, which requires also an excellent characterization of the background temperatures. With this the FireBird Infrared Instruments are also suitable to study phenomena with lower temperatures. Following the experience of BIRD, the design of the camera system in the visible bands was changed and with this altering the characteristics of the Bi- Spectral Method. These changes were validated in several experiments and the results will be discussed in this paper. To overcome some restrictions of the small satellite technology, advanced on board processing will be implemented on the FireBird satellites. By implementing the Bi- Spectral Method on board, it is possible to reduce the data stream to a dedicated list of detected high temperature events containing the parameter analyzed. This allows more efficient management of the on board memory and of the downlink capabilities considering also the demand to download selected image data.

Based on the DLR satellite system BIRD, launched and operated in the early 2000, the TET-1 satellite has been launched in 2012 as part of the FireBird satellite constellation. The constellation will consist of two satellites, the second one to be launched in the first half of 2016. Acquired imagery is processed and archived by DLR and will be publicly available. For this purpose, a processing chain has been implemented converting raw data (level 0 product) to geo-annotated at-sensor radiance (level 1b). Further data products can be derived, e.g. information on brightness temperature, fire radiative power, and surface emissivity. Other processing levels, such as atmospherically corrected reflectance, could also be produced. The sensitivity of a Thermal Infrared (TIR) sensor system depends on its spectral characteristics and its spatial resolution. Various methods for high temperature event (HTE) detection and quantification have been developed, which can be categorized into single- and multi-band algorithms. While single band methods rely on the robust demarcation of background pixels and higher temperature pixels, considered as being anomalous, the TET-1 system facilitates the application of the widely used bi-spectral algorithm approach introduced by Dozier (1981), using the mid-infrared and longwave-infrared channel. This approach takes advantage of the non-linear nature of the Planck’s curves to calculate temperatures and the HTE area on a sub-pixel basis. TIR remote sensing can make a significant contribution to the detection and, partly, the monitoring of land surface temperature (LST), HTE and of parameters describing the surface energy balance for specific areas.

Gas flaring is a disposal process widely used in the oil extraction and processing industry. It consists in the burning of unwanted gas at the tip of a stack and due to its thermal characteristic and the thermal emission it is possible to observe and to quantify it from space. Spaceborne observations allows us to collect information across regions and hence to provide a base for estimation of emissions on global scale. We have successfully adapted the Visible Infrared Imaging Radiometer Suite (VIIRS) Nightfire algorithm for the detection and characterisation of persistent hot spots, including gas flares, to the Sea and Land Surface Temperature Radiometer (SLSTR) observations on-board the Sentinel- satellites. A hot event at temperatures typical of a gas flare will produce a local maximum in the night-time readings of the shortwave and mid-infrared (SWIR and MIR) channels of SLSTR. The SWIR band centered at 1.61 mmis closest to the expected spectral radiancemaximumand serves as the primary detection band. The hot source is characterised in terms of temperature and area by fitting the sum of two Planck curves, one for the hot source and another for the background, to the radiances from all the available SWIR, MIR and thermal infra-red channels of SLSTR. The flaring radiative power is calculated from the gas flare temperature and area. Our algorithm differs from the original VIIRS Nightfire algorithm in three key aspects: (1) It uses a granule-based contextual thresholding to detect hot pixels, being independent of the number of hot sources present and their intensity. (2) It analyses entire clusters of hot source detections instead of individual pixels. This is arguably a more comprehensive use of the available information. (3) The co-registration errors between hot source clusters in the different spectral bands are calculated and corrected. This also contributes to the SLSTR instrument validation. Cross-comparisons of the new gas flare characterisation with temporally close observations by the higher resolution German FireBIRD TET-1 small satellite and with the Nightfire product based on VIIRS on-board the Suomi-NPP satellite show general agreement for an individual flaring site in Siberia and for several flaring regions around the world. Small systematic differences to VIIRS Nightfire are nevertheless apparent. Based on the hot spot characterisation, gas flares can be identified and flared gas volumes and pollutant emissions can be calculated with previously published methods.

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.