Journal article
Comparison of Methods for Modeling Fractional Cover Using Simulated Satellite Hyperspectral Imager Spectra
Remote sensing (Basel, Switzerland), Vol.11(18), p.2072
09/01/2019
DOI: 10.3390/rs11182072
Abstract
Remotely sensed data can be used to model the fractional cover of green vegetation (GV), non-photosynthetic vegetation (NPV), and soil in natural and agricultural ecosystems. NPV and soil cover are difficult to estimate accurately since absorption by lignin, cellulose, and other organic molecules cannot be resolved by broadband multispectral data. A new generation of satellite hyperspectral imagers will provide contiguous narrowband coverage, enabling new, more accurate, and potentially global fractional cover products. We used six field spectroscopy datasets collected in prior experiments from sites with partial crop, grass, shrub, and low-stature resprouting tree cover to simulate satellite hyperspectral data, including sensor noise and atmospheric correction artifacts. The combined dataset was used to compare hyperspectral index-based and spectroscopic methods for estimating GV, NPV, and soil fractional cover. GV fractional cover was estimated most accurately. NPV and soil fractions were more difficult to estimate, with spectroscopic methods like partial least squares (PLS) regression, spectral feature analysis (SFA), and multiple endmember spectral mixture analysis (MESMA) typically outperforming hyperspectral indices. Using an independent validation dataset, the lowest root mean squared error (RMSE) values were 0.115 for GV using either normalized difference vegetation index (NDVI) or SFA, 0.164 for NPV using PLS, and 0.126 for soil using PLS. PLS also had the lowest RMSE averaged across all three cover types. This work highlights the need for more extensive and diverse fine spatial scale measurements of fractional cover, to improve methodologies for estimating cover in preparation for future hyperspectral global monitoring missions.
Details
- Title: Subtitle
- Comparison of Methods for Modeling Fractional Cover Using Simulated Satellite Hyperspectral Imager Spectra
- Creators
- Philip E. Dennison - University of UtahYi Qi - Univ Nebraska, Sch Nat Resources, Lincoln, NE 68583 USASusan K. Meerdink - Univ Florida, Engn Sch Sustainable Infrastruct & Environm, Gainesville, FL 32611 USARaymond F. Kokaly - United States Geological SurveyDavid R. Thompson - CALTECH, Jet Prop Lab, 4800 Oak Grove Dr, Pasadena, CA 91109 USACraig S. T. Daughtry - USDA ARS, Hydrol & Remote Sensing Lab, Beltsville, MD 20705 USAMiguel Quemada - Univ Politecn Madrid, Sch Agr Engn, CEIGRAM, E-28040 Madrid, SpainDar A. Roberts - Univ Calif Santa Barbara, Dept Geog, Santa Barbara, CA 93106 USAPaul D. Gader - Univ Florida, Engn Sch Sustainable Infrastruct & Environm, Gainesville, FL 32611 USAErin B. Wetherley - Univ Calif Santa Barbara, Dept Geog, Santa Barbara, CA 93106 USAIzaya Numata - South Dakota State UniversityKeely L. Roth - Climate Corp, Sci, San Francisco, CA 94103 USA
- Resource Type
- Journal article
- Publication Details
- Remote sensing (Basel, Switzerland), Vol.11(18), p.2072
- DOI
- 10.3390/rs11182072
- ISSN
- 2072-4292
- eISSN
- 2072-4292
- Publisher
- Mdpi
- Number of pages
- 23
- Grant note
- 80NSSC17K0575 / National Aeronautics and Space Administration (NASA); National Aeronautics & Space Administration (NASA)
- Language
- English
- Date published
- 09/01/2019
- Academic Unit
- Geographical and Sustainability Sciences
- Record Identifier
- 9984259385802771
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