Daniel Jensen
Postdoc
About
Bio
Daniel is a postdoctoral fellow at JPL with the NASA Postdoctoral Program under the supervision of Marc Simard and David Thompson. He completed his PhD at UCLA with Kyle Cavanaugh and Marc Simard, where he used airborne imaging spectrometer data to study coastal wetland ecosystems in Louisiana.
Education
BA in Geography, UC Berkeley; MA in Geography, CSU Long Beach; PhD in Geography, UCLA
Research Interests
Imaging spectroscopy, Environmental remote sensing, Data integration, Wetland ecology
Experience
Professional Experience
- NASA Postdoctoral Program Fellow, JPL (2020-present)
- Teaching Assistant, UCLA (2015-2019)
- Intern, JPL (2016)
- Participant, Geoinformatics Fellow, and Assistant Center Lead, DEVELOP National Program at JPL (2014-2015)
- Participant, DEVELOP National Program at Langley Research Center (2014)
Achievements
Awards & Recognitions
- Professional Society and External Organization Awards | UCLA | Graduate Research Mentorship Award (?)
Publications
- Jensen, D., Cavanaugh, K.C., Simard, M., Okin, G.S., Castañeda-Moya, E., McCall, A., & Twilley, R.R. (2019). Integrating Imaging Spectrometer and Synthetic Aperture Radar Data for Estimating Wetland Vegetation Aboveground Biomass in Coastal Louisiana. Remote Sensing, 11(21), 2533. DOI: 10.3390/rs11212533
- Jensen, D., Simard, M., Cavanaugh, K., Sheng, Y., Fichot, C.G., Pavelsky, T., & Twilley, R. (2019). Improving the Transferability of Suspended Solid Estimation in Wetland and Deltaic Waters with an Empirical Hyperspectral Approach. Remote Sensing, 11(13), 1629. DOI: 10.3390/rs11131629
- Jensen, D., Reager, J.T., Zajic, B., Rousseau, N., Rodell, M., & Hinkley, E. (2018). The sensitivity of US wildfire occurrence to pre-season soil moisture conditions across ecosystems. Environmental Research Letters, 13(1). DOI: 10.1088/1748-9326/aa9853
- Jensen, D.J., Simard, M., Cavanaugh, K.C., & Thompson, D.R. (2017). Imaging Spectroscopy BRDF Correction for Mapping Louisiana’s Coastal Ecosystems. IEEE Transactions on Geoscience and Remote Sensing, 56(3), 1739–1748. DOI: 10.1109/TGRS.2017.2767607