Remote sensing of vegetation water content
Microwave remote sensing signals over land depend on both soil moisture and vegetation water content. Because more biomass implies more vegetation mass that is partially composed of water, vegetation water content datasets derived from microwave remote sensing have mostly been used as indicators of biomass change. However, this neglects the fact that the relative water content of the biomass can also change depending on xylem and leaf water potential and thus, on meteorological conditions and plant water stress. Our group is interested in all aspects of enabling microwave remote sensing proxies of vegetation water content to be used for better understanding plant water stress and its many interactions with the rest of the earth system. This includes building new datasets from both radar and radiometry, calibration and validation of those datasets, better understanding the sensitivity of related datasets to changes in water stress and its manifestations in the soil-plant-atmosphere-continuum, and using datasets that either we or others have developed (e.g. the LPDR dataset produced at the University of Montana, the SMAP MTDCA VOD originally developed by Alex and now maintained by Andrew Feldman at NASA Goddard) for a variety of ecohydrological aplications (e.g. water and carbon flux dynamics, trait mapping, wildfire risk, drought-driven tree mortality, etc...)
Detecting forest response to droughts with global observations of vegetation water content
Konings A.G., S.S. Saatchi, C. Frankenberg, M. Keller, V. Leshyk, W.R.L. Anderegg, V. Humphrey, A.M. Matheny, A. Trugman, L. Sack, E. Agee, M.L. Barnes, O. Binks, ..., and P.A. Zuidema (2021). Global Change Biology, 27: 6005-6024
L-band vegetation optical depth as an indicator of plant water potential in a temperate deciduous forest stand
N. Holtzman, L.D.L Anderegg, S. Kraatz, A. Mavrovic, O. Sonnentag, C. Pappas, M.H. Cosh, A. Langlois, T. Lakhankar, D. Tesser, N. Steiner, A. Colliander, A. Roy, and A.G. Konings (2021). Biogeosciences, 18:739-753.
Interannual variations of vegetation optical depth due to both water stress and biomass changes
Konings, A.G., N.M. Holtzman, K. Rao, L. Xu, and S. Saatchi (2021). Geophysical Research Letters, 48, e2021GL095267
Leaf surface water, not plant water stress, drives diurnal variation in tropical forest canopy water content
Xu, X., A.G. Konings, M. Longo, A. Feldman, L. Xu, S. Saatchi, D. Wu, J. Wu, and P. Moorcroft (2021). New Phytologist, 231: 122-136.
SAR-enhanced mapping of live fuel moisture content
Rao, K., A.P. Williams, J. Fortin Flefil, and A.G. Konings (2020). Remote Sensing of Environment, 245: 111797.
Satellite-based vegetation optical depth as an indicator of drought-driven tree mortality
Rao, K., W.R.L. Anderegg, A. Sala, J. Martinez-Vilalta, and A.G. Konings (2019). Remote Sensing of Environment, 227: 125–36.
Macro to micro: microwave remote sensing of plant water content for physiology and ecology
Konings, A.G., K. Rao, and S.C. Steele-Dunne (2019). New Phytologist, 223: 1166-1172.
Interacting effects of leaf water potential and biomass on vegetation optical depth
Momen, M., J.D. Wood, K.A. Novick, R. Pangle, W.T. Pockman, N.G. McDowell, and A.G. Konings (2017). Journal of Geophysical Research - Biogeosciences, 122:3031-3046.
L-band vegetation optical depth and scattering albedo estimation from SMAP
Konings, A. G., M. Piles, N.N. Das, and D. Entekhabi (2017). Remote Sensing of Environment, 198: 460-470.
The Effect of Variable Soil Moisture Profiles on P-Band Backscatter
Konings, A. G., D. Entekhabi, M. Moghaddam, and S.S. Saatchi (2014). IEEE Transactions on Geoscience and Remote Sensing, 52(10): 6315-6325.