Daniel Sousa


Daniel SouzaAssistant Professor of Geography
Storm Hall 304C | [email protected]

Dan Sousa and his students work at the intersection of geophysical data analysis, surface hydrology, and conservation ecology. Dan’s research addresses the question of how multiple types of observations, in particular observations at multiple scales, can be better used together to understand the Earth surface. This work involves both emerging sensing technologies like imaging spectroscopy, as well as novel analysis techniques like manifold learning and spatial network analysis.

Dan’s research has primarily used optical and thermal satellite image time series in conjunction with robust field measurements to better understand spatiotemporal landscape patterns. Past work has focused on mapping and monitoring of oak landscapes in California Rangelands; chemical weathering severity in geologic outcrops; conservation and land use/land cover change in ecologically sensitive areas in Oman and Bangladesh; the application of spectral mixture analysis to the remote sensing of evapotranspiration; microscale physics of evaporation from porous media; intercomparison of information content in coincident multispectral and hyperspectral observations; and global standardization of Landsat and MODIS spectral mixture models.

Dan grew up working as a manual laborer and crew supervisor on construction sites in and around Davis, CA. He has a BS from UC Davis and an MA and PhD from Columbia University. Previously, he has worked at research labs including NASA’s Jet Propulsion Lab (JPL) and Ames Research Center, the U.S. Naval Research Lab (NRL), and the National Center for Ecological Analysis and Synthesis (NCEAS). Dan also served one year as a NOAA Knauss Fellow in a California Congressional office on Capitol Hill. He has done fieldwork in over 10 countries and spent 6 weeks at sea on a geophysical research cruise in the waters offshore Hawai’i. He has also done freelance consulting work for small and large for-profit and non-profit clients.

Dan welcomes new graduate or undergraduate students interested in topics including imaging spectroscopy, spatiotemporal analysis, spectral and temporal mixture modeling, spatial networks, and multisensor fusion. If any of the above sounds interesting to you, please get in touch!

  • Ph.D., Columbia University
  • M.A., Columbia University
  • B.S., University of California, Davis
  • GEOG 592: Intermediate Remote Sensing of Environment
  • Understanding spatiotemporal landscape patterns using multi-scale imagery
  • Imaging spectroscopy, manifold learning, and spatial network analysis