Nimrod Carmon

Biographical Sketch

Dr. Nimrod Carmon is a data scientist at the Jet Propulsion Laboratory, having completed his Ph.D. at Tel-Aviv University. He joined JPL initially as a postdoctoral scholar before transitioning into a full-time data scientist role. Dr. Carmon serves as the principal investigator (PI) for projects within the NASA Land Cover and Land Use Change (LCLUC) program and the Early Career Investigator Program in Earth Science (ECIP-ES).

His research is concentrated on advancing retrieval sciences in imaging spectroscopy, particularly hyperspectral and multispectral VSWIR and TIR remote sensing. By integrating rigorous physical formulations and efficient parameterizations, his work aims to enhance the interpretative value of these measurements, minimizing uncertainties and boosting their applicability.

Dr. Carmon's current projects include fire risk assessment through the analysis of plant functional traits in fire-prone areas. His approach utilizes the PROSAIL leaf and canopy reflectance model in conjunction with the MODTRAN atmospheric radiative transfer model. By employing advanced linear algebra techniques, dimensionality reduction, and optimization algorithms, he refines these models to achieve precise, physically-meaningful estimates of surface conditions. His modeling philosophy emphasizes simplifying complex forward models into computationally efficient forms without compromising their accuracy or physical relevance.

Projects

• Imaging spectroscopy, geological surface composition, radiative transfer

Selected Publications

Thompson, David R., Carmon, N., and others (2024). “On-orbit calibration and performance of the EMIT imaging spectrometer,” Remote Sensing of Environment, 303, p. 113986. Document (link to DOI).

Carmon, N. and others (2023). “Shape from Spectra,” Remote Sensing of Environment. Document (link to DOI).

Dozier, J., Carmon, N., and others (2022). “Error and Uncertainty Degrade Topographic Corrections of Remotely Sensed Data,” JGR Biogeosciences. Document (link to DOI).

Thompson, D., Carmon, N., and others (2022). “Atmospheric Lengthscales for Global VSWIR Imaging Spectroscopy,” JGR Biogeosciences. Document (link to DOI).

Carmon, N., Berk, A., Bohn, N., Brodrick, P., Kalashnikova, O. and others (2022). “Unified Topographic and Atmospheric Correction for Remote Imaging Spectrometers,” Frontiers in Remote Sensing. Document (link to DOI).

Bohn, N., Thompson, D. R., Carmon, N., Susiluoto, J., Turmon, M. and others (2022). “Glacier Ice surface properties in South-West Greenland Ice Sheets: First Estimates from PRISMA Imaging Spectroscopy Data,” Remote Sensing of Environment. Document (link to DOI).

Nelson, P.R., Carmon, N., and others (2022). “Remote Sensing of Tundra Ecosystems using High Spectral Resolution Reflectance: Opportunities and Challenges,” JGR Biogeosciences. Document (link to DOI).

Brodrick, P., Thompson, D. R., Fahlen, J. E., Eastwood, M. L., Sarture, C. M. and others including Carmon, N. (2021). “Generalized Radiative Transfer Emulation for Imaging Spectroscopy Reflectance Retrievals,” Remote Sensing of Environment. Document (link to DOI).

Bohn, N., Thompson, D. R., Carmon, N., Susiluoto, J., Turmon, M. and others (2020). “Optimal Estimation of Snow and Ice Surface Parameters from Spaceborne Imaging Spectroscopy Measurements,” Remote Sensing of Environment. Document (link to DOI).

Thompson, D. R., Braverman, A., Bohn, N., Brodrick, P., Carmon, N., and others (2020). “Scene Invariants for Quantifying Radiative Transfer Uncertainty,” Remote Sensing of Environment. Document (link to DOI).

Connelly, D. S., Thompson, D. R., Mahowald, N., Li, L., Carmon, N. and others (2020). “The EMIT Mission Information Yield for Mineral Dust Radiative Forcing,” Remote Sensing of Environment. Document (link to DOI).

Cawse-Nicholson, K., Townsend, P. A., Schimel, D., Carmon, N., and others (2020). “NASA’s Surface Biology and Geology Designated Observable: A Perspective on Surface Imaging Algorithms,” Remote Sensing of Environment. Document (link to DOI).

Carmon, N., Thompson, D. R., Susilouto, J., Bohn, N., Connelly, D. S. and others (2020). “Uncertainty Quantification for a Global Imaging Spectroscopy Surface Composition Investigation,” Remote Sensing of Environment. Document (link to DOI).

Thompson, D. R., Braverman, A., Candela, A., Carmon, N., Clark, R. N. and others (2020). “Quantifying Uncertainty for Remote Spectroscopy of Surface Composition,” Remote Sensing of Environment. Document (link to DOI).

Carmon, N., Lenart, C., and Ben-Dor, E. (2019). “Investigation of Spectral Assignments from Airborne HRS Sensor to model Friction Deterioration in Asphaltic Roads,” Proceedings of IEEE-WHISPERS. Document (link to DOI).

Carmon, N. and Ben-Dor, E. (2018). “A Spectral Assignment-Oriented Approach to Improve Interpretability and Accuracy of Proxy Spectral-Based Models,” IEEE Transactions on Geoscience and Remote Sensing. Document (link to DOI).

Gholizadeh, A., Saberioon, M., Carmon, N., Boruvka, L., and Ben-Dor, E. (2018). “Examining the Performance of PARACUDA-II Data-Mining Engine versus Selected Techniques to Model Soil Carbon from Reflectance Spectra,” Remote Sensing, 10(8), p. 1172. Document (link to DOI).

Carmon, N. and Ben-Dor, E. (2018). “Mapping Asphaltic Roads’ Skid Resistance Using Imaging Spectroscopy,” Remote Sensing, 10(3), p. 430. Document (link to DOI).

Gholizadeh, A., Carmon, N., Klement, A., Ben-Dor, E., and Borůvka, L. (2017). “Agricultural Soil Spectral Response and Properties Assessment: Effects of Measurement Protocol and Data Mining Technique,” Remote Sensing, 9(10), p. 1078. Document (link to DOI).

Kopačková, V., Ben-Dor, E., Carmon, N., and Notesco, G. (2017). “Modelling Diverse Soil Attributes with Visible to Longwave Infrared Spectroscopy using PLSR Employed by an Automatic Modelling Engine,” Remote Sensing, 9(2), p. 134. Document (link to DOI).

Carmon, Nimrod and Ben-Dor, Eyal (2016). “Rapid assessment of dynamic friction coefficient of asphalt pavement using reflectance spectroscopy,” IEEE Geoscience and Remote Sensing Letters, 13(5), pp. 721–724, IEEE. Document (link to DOI).