Journal article
Quantitative Assessment of Satellite L-Band Vegetation Optical Depth in the U.S. Corn Belt
IEEE geoscience and remote sensing letters, Vol.19, pp.1-5
11/06/2020
DOI: 10.1109/LGRS.2020.3034174
Abstract
Satellite L-band vegetation optical depth (L-VOD) contains new information about terrestrial ecosystems. However, it has not been evaluated against the geophysical variable that it represents, plant water, the mass of liquid water contained within vegetation tissue per ground area. We quantitatively assess the seasonal variation of three L-VOD products at the South Fork Core Validation Site in the Corn Belt state of Iowa where L-VOD is directly proportional to crop plant water. We use three satellite-scale crop plant water estimates: in situ measurements; a normalized difference water index (NDWI) calibrated with in situ measurements; and a crop model. We find that overall the L-VOD satellite products are 0.02-0.09 Np (0.4-1.7 kg · m⁻²) lower than the three estimates. We show that overestimation of L-VOD can be attributed to dynamic soil surface roughness, and hypothesize that crop plant water observations will require the incorporation of this effect into retrieval algorithms.
Details
- Title: Subtitle
- Quantitative Assessment of Satellite L-Band Vegetation Optical Depth in the U.S. Corn Belt
- Creators
- Kaitlin Togliatti - Department of Agronomy, Iowa State University of Science and Technology, Ames, IA 50011 USAColin Lewis-Beck - Department of Statistics and Actuarial Science, University of Iowa, Iowa City, IA 52242 USAVictoria A Walker - Numerical Terradynamic Simulation Group, University of Montana, Missoula, MT 59812 USATheodore Hartman - Department of Agronomy, Iowa State University of Science and Technology, Ames, IA 50011 USAAndy VanLoocke - Department of Agronomy, Iowa State University of Science and Technology, Ames, IA 50011 USAMichael H Cosh - Hydrology and Remote Sensing Laboratory, USDA ARS, Beltsville, MD 20705 USABrian K Hornbuckle - Department of Agronomy, Iowa State University of Science and Technology, Ames, IA 50011 USA (e-mail: bkh@iastate.edu)
- Resource Type
- Journal article
- Publication Details
- IEEE geoscience and remote sensing letters, Vol.19, pp.1-5
- Publisher
- IEEE
- DOI
- 10.1109/LGRS.2020.3034174
- ISSN
- 1545-598X
- eISSN
- 1558-0571
- Grant note
- IOW05566 / Iowa Agriculture and Home Economics Experiment Station NNX16AN24G; NNX16AO71H / NASA
- Language
- English
- Date published
- 11/06/2020
- Academic Unit
- Statistics and Actuarial Science; Economics
- Record Identifier
- 9984066105202771
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