Next Article in Journal
A Compressive Sensing-Based Approach to Reconstructing Regolith Structure from Lunar Penetrating Radar Data at the Chang’E-3 Landing Site
Next Article in Special Issue
A Comparison of Hybrid Machine Learning Algorithms for the Retrieval of Wheat Biophysical Variables from Sentinel-2
Previous Article in Journal
Rockfall Simulation Based on UAV Photogrammetry Data Obtained during an Emergency Declaration: Application at a Cultural Heritage Site
Open AccessArticle

Physically-Based Retrieval of Canopy Equivalent Water Thickness Using Hyperspectral Data

Department of Geography, Ludwig-Maximilians-University Munich, Luisenstraße 37, 80333 Munich, Germany
*
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(12), 1924; https://doi.org/10.3390/rs10121924
Received: 19 October 2018 / Revised: 26 November 2018 / Accepted: 27 November 2018 / Published: 30 November 2018
(This article belongs to the Special Issue Remote Sensing of Biophysical Parameters)
Quantitative equivalent water thickness on canopy level (EWTcanopy) is an important land surface variable and retrieving EWTcanopy from remote sensing has been targeted by many studies. However, the effect of radiative penetration into the canopy has not been fully understood. Therefore, in this study the Beer-Lambert law is applied to inversely determine water content information in the 930 to 1060 nm range of canopy reflectance from measured winter wheat and corn spectra collected in 2015, 2017, and 2018. The spectral model was calibrated using a look-up-table (LUT) of 50,000 PROSPECT spectra. Internal model validation was performed using two leaf optical properties datasets (LOPEX93 and ANGERS). Destructive in-situ measurements of water content were collected separately for leaves, stalks, and fruits. Correlation between measured and modelled water content was most promising for leaves and ears in case of wheat, reaching coefficients of determination (R2) up to 0.72 and relative RMSE (rRMSE) of 26% and in case of corn for the leaf fraction only (R2 = 0.86, rRMSE = 23%). These findings indicate that, depending on the crop type and its structure, different parts of the canopy are observed by optical sensors. The results from the Munich-North-Isar test sites indicated that plant compartment specific EWTcanopy allows us to deduce more information about the physical meaning of model results than from equivalent water thickness on leaf level (EWT) which is upscaled to canopy water content (CWC) by multiplication of the leaf area index (LAI). Therefore, it is suggested to collect EWTcanopy data and corresponding reflectance for different crop types over the entire growing cycle. Nevertheless, the calibrated model proved to be transferable in time and space and thus can be applied for fast and effective retrieval of EWTcanopy in the scope of future hyperspectral satellite missions. View Full-Text
Keywords: hyperspectral; spectroscopy; equivalent water thickness; canopy water content; agriculture; EnMAP hyperspectral; spectroscopy; equivalent water thickness; canopy water content; agriculture; EnMAP
Show Figures

Graphical abstract

MDPI and ACS Style

Wocher, M.; Berger, K.; Danner, M.; Mauser, W.; Hank, T. Physically-Based Retrieval of Canopy Equivalent Water Thickness Using Hyperspectral Data. Remote Sens. 2018, 10, 1924. https://doi.org/10.3390/rs10121924

AMA Style

Wocher M, Berger K, Danner M, Mauser W, Hank T. Physically-Based Retrieval of Canopy Equivalent Water Thickness Using Hyperspectral Data. Remote Sensing. 2018; 10(12):1924. https://doi.org/10.3390/rs10121924

Chicago/Turabian Style

Wocher, Matthias; Berger, Katja; Danner, Martin; Mauser, Wolfram; Hank, Tobias. 2018. "Physically-Based Retrieval of Canopy Equivalent Water Thickness Using Hyperspectral Data" Remote Sens. 10, no. 12: 1924. https://doi.org/10.3390/rs10121924

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop