Radiative Transfer Modelling for the characterisation of natural burnt surfaces AO/1-5526/07/NL/HE Recommendations #2c P. LEWIS 1, T. QUAIFE 5, J. GOMEZ-DANS 1,2, M. DISNEY 1, M. WOOSTER 2, D. ROY 3, B. PINTY 4 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 , USA 4. INSTITUTE FOR ENVIRONMENT AND SUSTAINABILITY (IES), EC JOINT RESEARCH CENTRE, VIA E. FERMI 1, TP 440, ISPRA (VA), ITALY 5. NCEO/DEPT. GEOGRAPHY, EXETER UNIVERSITY,

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

Fcc in detection algorithms  Optical detection algorithms: – ‘sensitive measure’ e.g. NDVI/NBR – And set of rules (thresholds etc.)  If view fcc as the sensitive measure, should be able to integrate into detection algorithms in same way  Can use fcc in probabilistic framework – Then obviate need for ‘rules’ beyond probability threshold – Particularly hopeful of this given stability in burn signals observed

Probability of step change

The add spatial probability constraints

And segment into ‘fires’ at same time as detection

Particularly attractive for C/climate models

Post fire analysis  NIR/MIR signal increases over week/weeks in savannas – If model operates as intended, expect:  Fcc remain constant over time  a0/a1 parameters vary (char dissipation)

Post fire analysis  Such analysis quite complex – Need to do careful BRDF modelling post fire  But would suggest that fcc measure should have some tolerance to post-fire observation timing – Since a0/a1 quite stable, expect to observe some consistent dynamics in feature space as fn of time after fire

Post fire analysis  Also, vegetation regrowth post fire should have poor fit to spectral model – so should spot this

recommendations  fcc approach should be investigated for detecting fire- affected areas from optical data  extend to spatio-temporal modeling of fires as part of detection algorithms and concepts for multi-sensor merging. – Target variables should move beyond estimation of a pixel count of fire-affected areas, to measures including fcc, fire size, and rates of spread.  temporal dynamics of the fcc signal should receive some attention.