Steven Pestana (Former Employee)
Science and Products
Streamflow and surface-water presence data availability across the conterminous United States: A review for headwater systems Streamflow and surface-water presence data availability across the conterminous United States: A review for headwater systems
Water is essential for life on Earth, supporting ecosystems, human health, and economic activities. Hydrology relies on observational data, and this paper discusses regional and national datasets for the conterminous United States (CONUS) publicly available as of 2023, focusing on headwaters, defined as first- and second-order streams at 1:24000 scale. It identifies 72 primary and...
Authors
Roy Sando, Kristin Jaeger, Christa Kelleher, John C. Hammond, Jay R. Christensen, Catalina Segura, Heather E. Golden, Frederick Y. Cheng, Admin Husic, C. Nathan Jones, Charles R. Lane, Li Li, D. Tyler Mahoney, Hillary McMillan, Adam N. Price, Erin C. Seybold, Adam Ward, Margaret Zimmer, Steven James Pestana
Non-USGS Publications**
Pestana, S. J., Chickadel, C. C., & Lundquist, J. D. (2024). Thermal infrared shadow-hiding in GOES-R ABI imagery: snow and forest temperature observations from the SnowEx 2020 Grand Mesa field campaign. The Cryosphere, 18(5), 2257-2276. https://doi.org/10.5194/tc-18-2257-2024
Pestana, S., Bair, E. H., Dozier, J., & Lundquist, J. D. (2023). Observations of Diurnal Midwave Infrared Anisotropy over Snow and Forests with GOES-R ABI. In IGARSS 2023-2023 IEEE International Geoscience and Remote Sensing Symposium (pp. 5-8). IEEE. https://doi.org/10.1109/IGARSS52108.2023.10282266
Pestana, S., & Lundquist, J. D. (2022). Evaluating GOES-16 ABI surface brightness temperature observation biases over the central Sierra Nevada of California. Remote Sensing of Environment, 281, 113221. https://doi.org/10.1016/j.rse.2022.113221
Pestana, S., Chickadel, C. C., Harpold, A., Kostadinov, T. S., Pai, H., Tyler, S., Webster, C., & Lundquist, J. D. (2019). Bias correction of airborne thermal infrared observations over forests using melting snow. Water Resources Research, 55(12), 11331-11343. https://doi.org/10.1029/2019WR025699
**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.
Science and Products
Streamflow and surface-water presence data availability across the conterminous United States: A review for headwater systems Streamflow and surface-water presence data availability across the conterminous United States: A review for headwater systems
Water is essential for life on Earth, supporting ecosystems, human health, and economic activities. Hydrology relies on observational data, and this paper discusses regional and national datasets for the conterminous United States (CONUS) publicly available as of 2023, focusing on headwaters, defined as first- and second-order streams at 1:24000 scale. It identifies 72 primary and...
Authors
Roy Sando, Kristin Jaeger, Christa Kelleher, John C. Hammond, Jay R. Christensen, Catalina Segura, Heather E. Golden, Frederick Y. Cheng, Admin Husic, C. Nathan Jones, Charles R. Lane, Li Li, D. Tyler Mahoney, Hillary McMillan, Adam N. Price, Erin C. Seybold, Adam Ward, Margaret Zimmer, Steven James Pestana
Non-USGS Publications**
Pestana, S. J., Chickadel, C. C., & Lundquist, J. D. (2024). Thermal infrared shadow-hiding in GOES-R ABI imagery: snow and forest temperature observations from the SnowEx 2020 Grand Mesa field campaign. The Cryosphere, 18(5), 2257-2276. https://doi.org/10.5194/tc-18-2257-2024
Pestana, S., Bair, E. H., Dozier, J., & Lundquist, J. D. (2023). Observations of Diurnal Midwave Infrared Anisotropy over Snow and Forests with GOES-R ABI. In IGARSS 2023-2023 IEEE International Geoscience and Remote Sensing Symposium (pp. 5-8). IEEE. https://doi.org/10.1109/IGARSS52108.2023.10282266
Pestana, S., & Lundquist, J. D. (2022). Evaluating GOES-16 ABI surface brightness temperature observation biases over the central Sierra Nevada of California. Remote Sensing of Environment, 281, 113221. https://doi.org/10.1016/j.rse.2022.113221
Pestana, S., Chickadel, C. C., Harpold, A., Kostadinov, T. S., Pai, H., Tyler, S., Webster, C., & Lundquist, J. D. (2019). Bias correction of airborne thermal infrared observations over forests using melting snow. Water Resources Research, 55(12), 11331-11343. https://doi.org/10.1029/2019WR025699
**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.