Date of Image(s):

January 11, 2025

Summary:

This product shows the char/ash fraction of each pixel based on airborne imaging spectroscopy measurements from NASA JPL AVIRIS-3. The surface reflectance was first estimated using ISOFIT, after which a Spectral Unmixing algorithm was used to determine the amount of char and ash within each pixel, based on the MESMA approach. See credits for citations and more information on ISOFIT, Spectral Unmixing, and the MESMA approach.

The char/ash fractional cover value is displayed as a single band pseudocolor grayscale, with thresholds at minimum detectable bounds of 50% and 80% char/ash fractional cover for Palisades and Eaton Fires, respectively.

Suggested Use:

The product describes the relative amount of char and ash (0-1) within each pixel. In order to deliver a product with low latency, the endmember library used was constrained to that common to a Southern California urban environment, and manual masking was also used. Locations that are heavily shaded may have errant solutions. The product also only indicates the char/ash fraction of the exposed surface - not what lies underneath. Areas covered by ash, for example, may express as having a fraction despite having only a thin coating of ash on top.

This is a research grade product with known false positives and false negatives. Improvements to product accuracy are ongoing and linear spectral mixture model was used to approximate char/ash fractional cover; however, due to multiple scattering effects of complex surfaces, actual the relationship between observed char/ash reflectance and actual char/ash abundance may be non-linear.

Resolution:

The product ground spatial resolution is approximately 2.8 m, and flights occurred between 19:40 and 21:00 UTC on Jan 11th 2025. Raw data are available for download here: https://popo.jpl.nasa.gov/pub/LA_Fires/working/eaton_1.tif

Point of Contact:

Philip G. Brodrick (JPL) and David R. Thompson (JPL)

Credits:

AVIRIS-3 Radiance Data:

Eckert, R., D.R. Thompson, A.M. Chlus, J.W. Chapman, M. Eastwood, M. Bernas, S. Geier, M. Helmlinger, D. Keymeulen, E. Liggett, S. Nadgauda, L.M. Rios, L.A. Shaw, W. Olson-Duvall, P.G. Brodrick, and R.O. Green. 2024. AVIRIS-3 L1B Calibrated Radiance, Facility Instrument Collection. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/2356

AVIRIS-3 Reflectance Data:

Brodrick, P.G., A.M. Chlus, U.N. Bohn, E. Greenberg, J. Montgomery, J.W. Chapman, M. Eastwood, S.R. Lundeen, R. Eckert, W. Olson-Duvall, D.R. Thompson, and R.O. Green. 2025. AVIRIS-3 L2A Orthocorrected Surface Reflectance, Facility Instrument Collection. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/2357

ISOFIT:

Thompson, D.R., Natraj, V., Green, R.O., Helmlinger, M.C., Gao, B.C. and Eastwood, M.L., 2018. Optimal estimation for imaging spectrometer atmospheric correction. Remote sensing of environment, 216, pp.355-373.

Philip G Brodrick, David R Thompson, Niklas Bohn, Nimrod Carmon, Regina Eckert, James Montgomery, Kevin Wurster, & Nicholas Vaughn. (2024). isofit (v3.2.2). Zenodo. https://doi.org/10.5281/zenodo.14135462

Spectral Unmixing: https://github.com/emit-sds/SpectralUnmixing

MESMA Approach:

Quintano, C., Fernández-Manso, A. and Roberts, D.A., 2013. Multiple Endmember Spectral Mixture Analysis (MESMA) to map burn severity levels from Landsat images in Mediterranean countries. Remote Sensing of Environment, 136, pp.76-88.

Date of Image(s):

January 11, 2025

Summary:

This product shows the char/ash fraction of each pixel based on airborne imaging spectroscopy measurements from NASA JPL AVIRIS-3. The surface reflectance was first estimated using ISOFIT, after which a Spectral Unmixing algorithm was used to determine the amount of char and ash within each pixel, based on the MESMA approach. See credits for citations and more information on ISOFIT, Spectral Unmixing, and the MESMA approach.

The char/ash fractional cover value is displayed as a single band pseudocolor grayscale, with thresholds at minimum detectable bounds of 50% and 80% char/ash fractional cover for Palisades and Eaton Fires, respectively.

Suggested Use:

The product describes the relative amount of char and ash (0-1) within each pixel. In order to deliver a product with low latency, the endmember library used was constrained to that common to a Southern California urban environment, and manual masking was also used. Locations that are heavily shaded may have errant solutions. The product also only indicates the char/ash fraction of the exposed surface - not what lies underneath. Areas covered by ash, for example, may express as having a fraction despite having only a thin coating of ash on top.

This is a research grade product with known false positives and false negatives. Improvements to product accuracy are ongoing and linear spectral mixture model was used to approximate char/ash fractional cover; however, due to multiple scattering effects of complex surfaces, actual the relationship between observed char/ash reflectance and actual char/ash abundance may be non-linear.

Resolution:

The product ground spatial resolution is approximately 2.8 m, and flights occurred between 19:40 and 21:00 UTC on Jan 11th 2025. Raw data are available for download here: https://popo.jpl.nasa.gov/pub/LA_Fires/working/eaton_1.tif

Point of Contact:

Philip G. Brodrick (JPL) and David R. Thompson (JPL)

Credits:

AVIRIS-3 Radiance Data:

Eckert, R., D.R. Thompson, A.M. Chlus, J.W. Chapman, M. Eastwood, M. Bernas, S. Geier, M. Helmlinger, D. Keymeulen, E. Liggett, S. Nadgauda, L.M. Rios, L.A. Shaw, W. Olson-Duvall, P.G. Brodrick, and R.O. Green. 2024. AVIRIS-3 L1B Calibrated Radiance, Facility Instrument Collection. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/2356

AVIRIS-3 Reflectance Data:

Brodrick, P.G., A.M. Chlus, U.N. Bohn, E. Greenberg, J. Montgomery, J.W. Chapman, M. Eastwood, S.R. Lundeen, R. Eckert, W. Olson-Duvall, D.R. Thompson, and R.O. Green. 2025. AVIRIS-3 L2A Orthocorrected Surface Reflectance, Facility Instrument Collection. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/2357

ISOFIT:

Thompson, D.R., Natraj, V., Green, R.O., Helmlinger, M.C., Gao, B.C. and Eastwood, M.L., 2018. Optimal estimation for imaging spectrometer atmospheric correction. Remote sensing of environment, 216, pp.355-373.

Philip G Brodrick, David R Thompson, Niklas Bohn, Nimrod Carmon, Regina Eckert, James Montgomery, Kevin Wurster, & Nicholas Vaughn. (2024). isofit (v3.2.2). Zenodo. https://doi.org/10.5281/zenodo.14135462

Spectral Unmixing: https://github.com/emit-sds/SpectralUnmixing

MESMA Approach:

Quintano, C., Fernández-Manso, A. and Roberts, D.A., 2013. Multiple Endmember Spectral Mixture Analysis (MESMA) to map burn severity levels from Landsat images in Mediterranean countries. Remote Sensing of Environment, 136, pp.76-88.