Winfried Halle

Detection and characterization of low temperature peat fires during the 2015 fire catastrophe in indonesia using a new high-sensitivity fire monitoring satellite sensor (FireBird)

Vast and disastrous fires occurred on Borneo during the 2015 dry season, pushing Indonesia into the top five carbon emitting countries. The region was affected by a very strong El Niño-Southern Oscillation (ENSO) climate phenomenon, on par with the last severe event in 1997/98. Fire dynamics in Central Kalimantan were investigated using an innovative sensor offering higher sensitivity to a wider range of fire intensities at a finer spatial resolution (160 m) than heretofore available. The sensor is onboard the TET-1 satellite, part of the German Aerospace Center (DLR) FireBird mission. TET-1 images (acquired every 2–3 days) from the middle infrared were used to detect fires continuously burning for almost three weeks in the protected peatlands of Sebangau National Park as well as surrounding areas with active logging and oil palm concessions. TET-1 detection capabilities were compared with MODIS active fire detection and Landsat burned area algorithms. Fire dynamics, including fire front propagation speed and area burned, were investigated. We show that TET-1 has improved detection capabilities over MODIS in monitoring low-intensity peatland fire fronts through thick smoke and haze. Analysis of fire dynamics revealed that the largest burned areas resulted from fire front lines started from multiple locations, and the highest propagation speeds were in excess of 500 m/day (all over peat > 2m deep). Fires were found to occur most often in concessions that contained drainage infrastructure but were not cleared prior to the fire season. Benefits of implementing this sensor system to improve current fire management techniques are discussed. Near real-time fire detection together with enhanced fire behavior monitoring capabilities would not only improve firefighting efforts, but also benefit analysis of fire impact on tropical peatlands, greenhouse gas emission estimations as well as mitigation measures to reduce severe fire events in the future.

A system on a chip concept for the Mercury Thermal Imaging Spectrometer MERTIS

A very advanced Mercury Thermal Infrared Spectrometer (MERTIS) was proposed by the German Aerospace Center (DLR) fulfilling the extreme resource restrictions of the ESA deep space mission BepiColombo to the inner planet Mercury. The design drivers for the MERTIS instruments are the limited mass and the harsh radiation environment. Derived from these main constrains are power-, volume- and thermal restrictions. This paper presents some key technologies applied to keep the BepiColombo mission limits. It will touch the extreme light weight and compact optic design but focuses on the system on a chip application of the MERTIS instrument digital electronics and its influence to the system structure and reliability concept. It will further show some techniques making the operation of the MERTIS instrument more robust in this radiation exposed environment. One example is the integration of a digital thermal controller for a thermo electrical cooler with less than 10 mK accuracy. It is synthesized into the MERTIS system on a chip instrument controller based on a field programmable gate array (FPGA)

Upcoming and prospective fire monitoring missions based on the heritage of the BIRD (bi-spectral infrared detection) satellite

Observation of active fires enables the estimation of trace gas and aerosol emissions, and can support fire management, air pollution monitoring and forecasting, and reporting efforts under international conventions. Here we present a mission concept for a dedicated Fire Monitoring Constellation (FMC) of small satellites based on experience from the BIRD mission (2001 - 2004), as well as the upcoming FireBIRD mini-constellation to start operating in 2014. An operational FMC should provide near daily observations during afternoon hours, improve characterisation and monitoring of fires in the low latitudes, and provide high spatial resolution to characterize fire fronts and predominant combustion regime.

Texture segmentation with a neural network

A neural method for gray value segmentation now is applied to texture segmentation. The parallel-sequential algorithm is based on recursive nonlinear feature smoothing in a 4- neighborhood. The smoothed feature values then can be segmented using an adaptive adjacency criterion which defines a special graph structure, called the Feature Similarity Graph. The segments are the connected components of that graph. The combination of results from the different image features is done in a hierarchical process starting, like in the human visual system with gray value segmentation. Besides segments with homogeneous gray value this process also provides texture elements which are the basis for the calculation of new image features. Then, first, the modulus of the gray value gradient is used as a new feature of the original image. The following segmentation basing on that feature provides regions which are homogeneous with respect to the mean gray value gradient. Furthermore, texel directions are calculated. That feature contains information on texture orientation of textured image regions. With these features the same neural segmentation method is able to separate not only regions with different mean gray values but also those with different textures.

Objectives and results of the BIRD mission

The DLR small satellite BIRD (Bi- spectral Infrared Detection) is successfully operating in space since October 2001. The main payload is dedicated to the observation of high temperature events and consists mainly of a Bi-Spectral Infrared Push Broom Scanner (3.4-4.2μm and 8.5-9.3μm), a Push Broom Imager for the Visible and Near Infrared and a neural network classification signal processor. The BIRD mission answers topical technological and scientific questions related to the operation of a compact infra-red push-broom sensor on board of a micro satellite. A powerful Payload Data Handling System (PDH) is responsible for all payload real time operation, control and on-board science data handling. The IR cameras are equipped with an advanced real time data processing allowing an autonomously adaptation of the dynamic range to different scenarios. The BIRD mission control, the data reception and the data processing is conducted by the DLR ground stations in Weilheim and Neustrelitz (Germany) and is experimentally performed by a low cost ground station implemented at DLR Berlin-Adlershof. The BIRD on ground data processing chain delivers radiometric and geometric corrected data products, which will be also described in this paper. The BIRD mission is an exemplary demonstrator for small satellite projects dedicated to the hazard detection and monitoring.

Thematic data processing on board the satellite BIRD

The general trend in remote sensing is on one hand to increase the number of spectral bands and the geometric resolution of the imaging sensors which leads to higher data rates and data volumes. On the other hand the user is often only interested in special information of the received sensor data and not in the whole data mass. Concerning these two tendencies a main part of the signal pre-processing can already be done for special users and tasks on-board a satellite. For the BIRD (Bispectral InfraRed Detection) mission a new approach of an on-board data processing is made. The main goal of the BIRD mission is the fire recognition and the detection of hot spots. This paper describes the technical solution, of an on-board image data processing system based on the sensor system on two new IR-Sensors and the stereo line scanner WAOSS (Wide-Angle-Optoelectronic-Scanner). The aim of this data processing system is to reduce the data stream from the satellite due to generations of geo-coded thematic maps. This reduction will be made by a multispectral classification. For this classification a special hardware based on the neutral network processor NI1000 was designed. This hardware is integrated in the payload data handling system of the satellite.

High Temperature Fire Experiment for TET-1 and Landsat 8 in Test Site DEMMIN (Germany)

In 2012, the German Aerospace Center (DLR) launched the small satellite TET-1 (Experimental Technology Carrier) as a test platform for new satellite technologies and as a carrier for the Multi-Spectral Camera System (MSC) with five spectral bands (Green, Red, Near Infrared, Middle Infrared, and Thermal Infrared). The MSC has been designed to provide quantitative parameters (e.g. fire radiative power, burned area) observing high-temperature events. The detection of such events provides information for operational support to fire brigades, to change detection of hotspots, to assess CO2 emissions of burning vegetation, and, finally, contributes to the monitoring programs that support climate models. In order to investigate the sensitivity and accuracy of the MSC system, a calibration and validation fire campaign was developed and executed, to derive characteristic signal changes of corresponding pixels in the MWIR and LWIR bands. The planning and execution of the validation campaign and the results are presented.