TY - JOUR
T1 - Hyperspectral narrowband and multispectral broadband indices for remote sensing of crop evapotranspiration and its components (transpiration and soil evaporation)
AU - Marshall, Michael
AU - Thenkabail, Prasad
AU - Biggs, Trent
AU - Post, Kirk
N1 - Funding Information:
The project was funded primarily through support from the United States Geological Survey (USGS) Mendenhall Research Fellowship Program under the direction of the Geographic Analysis and Monitoring and Land Remote Sensing programs. Field assistants (Tony Chang, Jeff Peters, and Bobbijean Freeman) who worked long and strenuous hours to collect spectroradiometric and ancillary biophysical data were funded with support from a USGS and National Association of Geoscience Teachers cooperative agreement. The micrometeorological stations were maintained through support from the California Energy Commission , USGS Federal Matching Funds program, U.S. Department of Energy's Office of Science Ameriflux program, California Department of Water Resources (CADWR) , National Aeronautics and Space Administration (NASA) , and the University of California (UC) at Berkeley and Davis. The authors are especially grateful to the following individuals, and their respective organizations, for outstanding contributions to the project: Diganta Adhikari, Christopher Lund, Forrest Melton, Dennis Baldocchi, Laura Koteen, Sara Knox, Cayle Little, and Richard Snyder for their assistance with deployment of field instrumentation, micrometeorological station ET data analysis and partial funding. We would also like to thank The Nature Conservancy for site access and logistical support for two of the micrometeorological stations. Finally, we would like to thank Deborah Soltesz, Miguel Velasco, Larry Gaffney, and Lois Hales who managed day-to-day logistics while personnel were in the field.
Publisher Copyright:
© 2015 The Authors.
PY - 2016/3/15
Y1 - 2016/3/15
N2 - Evapotranspiration (ET) is an important component of micro- and macro-scale climatic processes. In agriculture, estimates of ET are frequently used to monitor droughts, schedule irrigation, and assess crop water productivity over large areas. Currently, in situ measurements of ET are difficult to scale up for regional applications, so remote sensing technology has been increasingly used to estimate crop ET. Ratio-based vegetation indices retrieved from optical remote sensing, like the Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index, and Enhanced Vegetation Index are critical components of these models, particularly for the partitioning of ET into transpiration and soil evaporation. These indices have their limitations, however, and can induce large model bias and error. In this study, micrometeorological and spectroradiometric data collected over two growing seasons in cotton, maize, and rice fields in the Central Valley of California were used to identify spectral wavelengths from 428 to 2295nm that produced the highest correlation to and lowest error with ET, transpiration, and soil evaporation. The analysis was performed with hyperspectral narrowbands (HNBs) at 10nm intervals and multispectral broadbands (MSBBs) commonly retrieved by Earth observation platforms. The study revealed that (1) HNB indices consistently explained more variability in ET (δR2=0.12), transpiration (δR2=0.17), and soil evaporation (δR2=0.14) than MSBB indices; (2) the relationship between transpiration using the ratio-based index most commonly used for ET modeling, NDVI, was strong (R2=0.51), but the hyperspectral equivalent was superior (R2=0.68); and (3) soil evaporation was not estimated well using ratio-based indices from the literature (highest R2=0.37), but could be after further evaluation, using ratio-based indices centered on 743 and 953nm (R2=0.72) or 428 and 1518nm (R2=0.69).
AB - Evapotranspiration (ET) is an important component of micro- and macro-scale climatic processes. In agriculture, estimates of ET are frequently used to monitor droughts, schedule irrigation, and assess crop water productivity over large areas. Currently, in situ measurements of ET are difficult to scale up for regional applications, so remote sensing technology has been increasingly used to estimate crop ET. Ratio-based vegetation indices retrieved from optical remote sensing, like the Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index, and Enhanced Vegetation Index are critical components of these models, particularly for the partitioning of ET into transpiration and soil evaporation. These indices have their limitations, however, and can induce large model bias and error. In this study, micrometeorological and spectroradiometric data collected over two growing seasons in cotton, maize, and rice fields in the Central Valley of California were used to identify spectral wavelengths from 428 to 2295nm that produced the highest correlation to and lowest error with ET, transpiration, and soil evaporation. The analysis was performed with hyperspectral narrowbands (HNBs) at 10nm intervals and multispectral broadbands (MSBBs) commonly retrieved by Earth observation platforms. The study revealed that (1) HNB indices consistently explained more variability in ET (δR2=0.12), transpiration (δR2=0.17), and soil evaporation (δR2=0.14) than MSBB indices; (2) the relationship between transpiration using the ratio-based index most commonly used for ET modeling, NDVI, was strong (R2=0.51), but the hyperspectral equivalent was superior (R2=0.68); and (3) soil evaporation was not estimated well using ratio-based indices from the literature (highest R2=0.37), but could be after further evaluation, using ratio-based indices centered on 743 and 953nm (R2=0.72) or 428 and 1518nm (R2=0.69).
KW - ITC-ISI-JOURNAL-ARTICLE
KW - ITC-HYBRID
KW - Spectroscopy
KW - Micrometeorology
KW - Latent heat
KW - Energy balance
KW - HyspIRI
UR - https://ezproxy2.utwente.nl/login?url=https://webapps.itc.utwente.nl/library/2016/isi/marshall_hyp.pdf
UR - https://www.scopus.com/pages/publications/84951820768
U2 - 10.1016/j.agrformet.2015.12.025
DO - 10.1016/j.agrformet.2015.12.025
M3 - Article
SN - 0168-1923
VL - 218-219
SP - 122
EP - 134
JO - Agricultural and forest meteorology
JF - Agricultural and forest meteorology
ER -
