Recent Developments and Prospects for Innovative Remote Sensing of High-Temperature Events and Vegetation Fire Impacts by D. Oertel, E. Lorenz, B. Zhukov German Aerospace Center, (DLR-OS) Berlin Adlershof UN-ISDR Wildland Fire Advisory Group Meeting, GFMC, Freiburg, 3-4 December 2004 1
Overview of Presentation: # Vegetation fire emissions an example of application # Comparison of fire recognition capabilities of available satellite sensors # Examples of semi-operational MODIS applications # Bi-spectral IR Detection (BIRD) mission a pioneering experience # Comparison of MODIS and BIRD # Prospective operational fire detection and monitoring sensors of ESA 2
Peat Fires are a major climate threat ATSR-2 0.87 µm band 3.7 µm band In 1997 (during the El Nino) South East Asian peat fires calculated to have released carbon equivalent to 13-40% of global annual carbon emissions from fossil fuel burning. Drainage and logging suspected to have made peat fires more frequent and severe in recent decades and in the future, too. Severe smoke is extreme harmful to human health and it disturbs traffic. 3
Peat Fires in Indonesia If we can t prevent fires in Indonesia, such international efforts (e.g. Kyoto Protocol) to limit the effects of climate change could be in vain. Nature Vol. 432 Issue No 7014, 11 November 2004 50 km 3D model of peat volume Courtesy: F. Siegert, RSS GmbH 4
Space-borne active fire recognition - currently conducted by: A) Meteorological and environmental satellite systems mostly not dedicated to active fire detection and monitoring, possessing a 4 µm channel, such as: Sensors on Low Earth Orbits (LEO): # Advanced Very High Resolution Radiometer (AVHRR) on NOAA POES satellites, # Advanced Along Track Scanning Radiometer (AATSR) on ERS and ENVISAT # Moderate resolution Imaging Spectro-radiometer (MODIS) on EOS Terra and Aqua # Visible and InfraRed Scanner (VIRS) on the Tropical Rainfall Measuring Mission (TRMM) satellite Geostationary sensors: # Visible Infrared Spin Scan Radiometer Atmospheric Sounder (VAS) on the GOES satellites the GOES Imager B) Experimental satellite on Bi-spectral InfraRed Detection (BIRD) 5
SENSOR Min. Detectable 800 K HTE (12/6 K above Bkg) DAY TIME Saturation Size of 800 K HTE Min. Detectable 800 K HTE (12/6 K above Bkg) NIGHT TIME Saturation Size of 800 K HTE AVHRR (NOAA) 500 / 225 m 2 670 m 2 170 / 75 m 2 1300 m 2 VIIRS (TRMM) 1350 / 850 m 2 1880 m 2 650 / 285 m 2 3760 m 2 MODIS (EOS) 430 / 230 m 2 66400 m 2 190 / 85 m 2 66800 m 2 BIRD (DLR) 50 / 30 m 2 32100 m 2 23 / 10 m 2 42700 m 2 SEVIRI (MSG) 10300 / 4650 m 2 40500 m 2 4360 / 1910 m 2 51600 m 2 GOES 4000 / 2100 m 2 11000 m 2 1570 / 690 m 2 16200 m 2 6
MODIS Fire Map daily global coverage: 1-km pixel size Overpasses Pink 02:30 am/pm - Aqua Red 10:30 am/pm - Terra http://firemaps.geog.umd.edu Courtesy: C. Justice, Univ. Md / US 7
Wildfires in California MODIS active fire detections - MOD 14 product on Web - superimposed with US Forest Service park boundaries, hydrology, roads User can query for fire detection attribute information Courtesy: Justice & Davies et al. Univ.Md / US 8
BIRD: Bi-spectral InfraRed Detection mission BIRD launch on 22 October 2001 with an Indian PSLV-C3 launcher BIRD Objectives: Test of new small satellite technologies Test of a new generation of infrared array sensors with an adaptive radiometric dynamic range Detection and quantitative characterisation of hightemperature events: vegetation-, peat- and coal seam fires and of volcanic activity 9
BIRD Micro-Satellite and Sensor Technology The Payload Segment Satellite: 94 kg, 620 x 620 x 550 mm 3, 200 W peak power The Electronics Segment The Service Segment Spacecraft bus with variable payload platform 10
Comparison of MODIS and BIRD sensors Spectral channels for fire detection MIR channel saturation Spatial resolution Swath width Revisit time MODIS on EOS -Terra / Aqua MIR: 3.9-4.0 µm TIR: 10.8-11.3 µm RED: 0.62-0.67 µm NIR: 0.84-0.88 µm 450 K 1 km 2330 km 4 times a day HSRS* / WAOSS-B** on BIRD MIR: 3.4-4.2 µm TIR: 8.5-9.3 µm NIR: 0.84-0.90 µm 600 K 370 m / 185 m 190 km Experimental imaging of selected areas * HSRS: Hot Spot Recognition System, ** WAOSS-B: Wide-Angle Optoelectronic Stereo Scanner BIRD modification 11
MODIS BIRD Bush fires in Australia imaged by MODIS and BIRD on 5 January 2002 Colour coded Fire Radiative Power (in MW) of hot spots is projected on the NIR band MODIS: Detected 34 hot clusters, accumulated Fire Radiative Power release: FRP = 2.9 (2.6-3.0) GW BIRD: Detected 227 hot clusters, accumulated FRP = 5.2 (5.1-5.3) GW 20 10 km km 1 10 100 1000 MW 12
MODIS: 1 km IR pixel size BIRD: 370 m IR pixel size 1 2 3 5 4 10 km 6 Fragments of bush fire images in Australia obtained by MODIS and BIRD on 5 January 2002. Colour coded Fire Radiative Power (in MW) of hot spots is projected on the 0.9 µm NIR band images. 1 10 100 1000 MW 13
Typical characteristics of fire fronts (BIRD, Australia, 5 January 2002) No Eff. fire temp., K Eff. fire area, Ha Front length, km Energy release, MW Front strength, kw/m 1 815 0.48 4 130 30 2 715 2.3 7.5 310 40 3 893 0.59 3 210 70 4 >670 <0.78 5 79 15 5 852 0.92 10 300 30 6 957 1.0 9 530 60 7 >690 <0.51 4 62 15 8 796 0.39 3 96 30 14
MODIS BIRD 1 2 3 4 5 6 7 10 km 1 100 10000 MW Fragments of forest fire images at Baikal obtained by MODIS and BIRD on 16 July 2003. Colour coded Fire Radiative Power (in MW) of hot spots is projected on the 3.9 µm MIR band. The white arrows in the left image fragment indicate possible false alarms 15
Conclusions on comparative MODIS / BIRD fire data analysis (1) The Fire Radiative Power (FRP)* of more than a half of the hot clusters, which were detected by BIRD, is below the detection limit of MODIS, (2) MODIS, nevertheless, may only slightly underestimate the cumulative FRP in ecosystems where large fires take place, and (3) Though MODIS is hardly suitable for early small fire detection, it is an adequate instrument for cumulative FRP estimation of large wildfires. *FRP is a parameter proportional to the rate of biomass combustion, i.e. to the fire intensity 16
ESA Earth Observation: Vision on Thermal Sensors Provision of services for all phases of thermal disaster management 4 Pre- and post-fire, 4 Monitoring, in preference, including propagation modelling 4 Detection, as build-up capability Using guaranteed operational assets: 4 Operational meteorological satellites: Polar and geostationary visible infrared imagers 4 GMES satellites, Land Cover Sentinel Deploying new dedicated elements, BIRD-like, in a gradual manner 4 as dedicated micro-sats and/or guest payloads on operational host carriers, 4 in an incremental Thermal Disaster Management Confederation, 4 based on an open agreed deployment plan Extended to other thermal disasters (e.g. volcanoes) and applications of thermal monitoring 17
Prospective of Innovative Fire Recognition Satellite Systems in Global Monitoring of Environment and Security (GMES): GMES Earth Observation Component, Proposal of Preparatory Activities (Document: ESA/PB-EO[2004]48 rev.2): 4 Space Segment: Finally, a fire-detecting and monitoring IR sensor will be studied for eventual deployment as an auxiliary payload on several GMES satellites. 4 Sentinel 2 (Land Super Spectral) and Sentinel 3 (Ocean): The activities also will include definition studies for the IR sensor for fire detection which is considered for inclusion in the payload for several Sentinel satellites. 18
From the demonstrator BIRD to prospective operational GMES IR Sensors and an international Thermal Disaster Management Confederation DLR s BIRD know how will back up and accelerate the development of new Fire detection and monitoring IR sensors providing on-board: # Hot spot detection # Hot spot parameter estimation # Geo-referencing of hot spot data # Broadcast of tables with hot spot information to mobile GPS-type receivers using automated and time effective on-board signal processing chain elements. These Fire detection and monitoring IR sensors shall be flown as payload passengers and micro-satellite main payloads -with an estimated mass of a ~20 kg, and an expected power consumption less than 100 W. 19
How to contact us at DLR - Berlin: www.dlr.de/os/forschung/projekte/bird Eckehard.Lorenz@dlr.de Dieter.Oertel@dlr.de 20