Radiative Transfer Modelling for the characterisation of natural burnt surfaces AO/1-5526/07/NL/HE Recommendations

1. Radiative Transfer Modelling for the characterisation of natural burnt surfacesAO/1-5526/07/NL/HERecommendations P. LEWIS1, T. QUAIFE5, J. GOMEZ-DANS1,2, M. DISNEY1, M. WOOSTER2 , D. ROY3, B. PINTY4 1. NCEO/DEPT. GEOGRAPHY, UNIVERSITY COLLEGE LONDON, GOWER ST., LONDON WC1E 6BT, UK 2. NCEO/DEPT. GEOGRAPHY, KING'S COLLEGE LONDON, STRAND, LONDON WC2R 2LS, UK 3. GEOGRAPHIC INFORMATION SCIENCE CENTER OF EXCELLENCE, SOUTH DAKOTA STATE UNIVERSITY, WECOTA HALL, BOX 506B, BROOKINGS, SD 57007-3510, USA 4. INSTITUTE FOR ENVIRONMENT AND SUSTAINABILITY (IES), EC JOINT RESEARCH CENTRE, VIA E. FERMI 1, TP 440, 21020 ISPRA (VA), ITALY 5. NCEO/DEPT. GEOGRAPHY, EXETER UNIVERSITY,

2. Overview • EO technology overview (talk 1) • Wildfire detection and quantification • Brief summary of relevant results • ESA and related missions • Modelling fire impacts (talk 2) • Semi-analytical • 3D • Thermal • Linear modelling

3. EO technology overview: wildfire • Technologies: • Surface: • Optical (main focus here) • Thermal (secondary focus) • Microwave • Atmosphere • Not considered here • All technologies rely on spatial and temporal localisation of fire

4. Thermal: detection • Detect anomalous high T • Polar orbiting • Don’t view all fires • Orbital convergence • Some methods night only (lower fire activity) • Some methods rely on T saturation • Geostationary • Lower spatial, higher temporal resolution • Low resolution at high latitudes • All impacted by cloud

5. Optical: detection • Sometimes feasible from single image: classification • Mostly use time series • Mostly use SWIR (also NIR) • NBR/NDVI • Compounded by BRDF effects • Mostly considered noise, but can be treated • Worse cloud/smoke problems that thermal • Esp. if shorter wavelengths used • Moderate resolution: global • Polar orbiting (mainly), also geostationary • Higher resolution: • Low revisit • used for specific study areas • Or use longer time between

6. Active microwave: detection • Essentially classification mostly • Time series, generally • Issue of attribution of signal change to fire • Complexity from moisture variations • Not such an issue if materials dry? • Complexity from dry materials • Huge advantage in areas of high cloud cover • Tropics

7. Fire impact • optical fire severity measures • fire radiative energy • integral over time of fire radiative power • ‘direct’ measurements of pre-post biomass • active microwave • lidar measurements • vegetation indices • area affected by fire from spectral unmixing • atmospheric measurement of gasses and particles released by fire

8. Fire detection and impact • Best strategy, combine information • Multiple moderate resolution optical • Constellations of higher resolution • Combined optical and thermal • Combine all sources • Need appropriate theoretical background, models, and algorithms

9. Contributions of this study • Model to estimate fcc • bottom-up approach to C release estimate • Needs fuel load • Compare with FRE • Fcc model generic to all optical sensors • Should be able to combine information • Burn signal results suggest use as constraint • Measure is linear • Simple spatial scaling

10. The relevance of the algorithm to the exploitation of data from ESA and related sensors and missions • ENVISAT • Earth Explorers • Sentinels • Meteorological missions • Others

11. ENVISAT: MERIS • 300m, VIS/NIR, many channels • Issues: • No SWIR sampling • Geolocation (?) • BRDF effects not too great • Main route to exploitation: • Detect fire from other sensors • Apply fcc algorithm • Noting issues wrt burn materials/dead vegetation confusion • Would be aided by easy to use gridded surface reflectance product

12. ENVISAT: AATSR • Thermal • Detection (night time saturation or near saturation) (WFA) • Can’t use for FRE • Optical • Relevant wavelengths • Only 4 wavebands • Issues with 3 parameter model • Unless use burn signal constraint • Dual view possibly interesting for fcc directional effects • Same argument for MISR, CHRIS-PROBA

13. Earth Explorers • Earthcare: atmsophere (out of scope) • MSI worth considering? • Wind from ADM-Aeolus relevant (out of scope) • SMOS soil moisture relevant (fire risk) (out of scope) • PREMIER: atmosphere (out of scope) • BIOMASS

14. BIOMASS • P band SAR • Real potential for pre-post fire woody biomass estimates • Would need to demonstrate acceptable precision in change signal • Unlikely viable for dry grass fires • But distinguishing these of interest

15. Sentinels • Sentinel 1 • C band SAR • Arguments above, re detection • but saturation at higher biomass • So biomass change issues if pre-fire biomass high • Sentinels 4,5 • Atmosphere (out of scope)

16. Sentinel 2 • 13 bands across SW • Varying spatial resolution 60m+ • Satellite pair • Increased viewing opportunity • 5 day (cloud free) • ‘extended viewing capability’ • BRDF issues would need treatment • Fcc product at 60m, or implement multi-scale for further localisation • Need detection algorithms • Very intersting platform to develop fcc-based detection algorithm

17. Sentinel 3 • OLCI and SLSTR similar to MERIS/AATSR • SLSTR: dedicated low-dynamic range ‘fire’ channels • So FRP & day/night detections • Optical, similar to MERIS/AATSR uses and issues • BUT very interesting combination of platforms (Sentinel-2,-3) for multi-scale strategy (possibly also then Sentinel-1/BIOMASS)

18. Meteo • MetOp • AVHRR instrument • Optical (includes SWIR) • BRDF effects (can be treated: MODIS algorithm prototyped with AVHRR) • direct value if constrained burn signal used for fcc • Indirect, of value to moderate resolution constellation approach • thermal (fire saturation) • MSG/MTG • Operational FRE • Optical burned area/fcc difficult • Low signal/noise for any by largest fires • BUT tracking fcc post fire would be of interest • Need constraint to burn signal, but probably can get from active fire detections

19. Others • Medium resolution (sub 1m to 10s m) • VIS/NIR • SPOT Pléiades, DMC, SEOSAT-INGENIO, RapidEye, EROS • Revisit period for individual may not be high enough, but have constellation missions • Also CEOS LSI-concept – all as virtual constellation • Probably most useful for localisation of information if fire known (e.g. thermal) • Fcc could be applied if constrained burn signal • And atmospheric correction • EnMAP • Very relevant for characterisation of fcc • BRDF effects for off-nadir pointing • Don’t need full hyperspectral for this though • So maybe target more subtle information

20. Discussion • 3 parameter fcc model • Best used with >> 3 bands • Or strong constraint to burn signal • 2 single most interesting sensors • Sentinel-2 / EnMAP • Both aim at high repeat coverage high resolution

21. Discussion • A major limitation to monitoring / characterisation is often viewing opportunity • So should develop multi-sensor concepts • Including multi-resolution • Issues: • different spectral sampling • different spatial resolutions • potentially different viewing and illumination angles • Fcc approach can at least partially deal with all of these (BRDF modelling for latter) • Longer term, may consider full DA system (e.g. ESA EOLDAS) • But technology needs development

22. Key Recommendations • Fcc should be developed into operational algorithms to quantify fire impact • Method should be generic • needs testing ESA sensors and Sentinel prototypes • Investigate constraint for application to sensors with not >>3 wavebands • Issues in study in comparison of fcc-FRE • Need further investigation • Most application here to S. Africa • Wider application / testing • Develop method for multiple data streams • Including multiple resolutions