QUANTIFYING AND MONITORING NUTRIENT CYCLING, CARBON DYNAMICS AND SOIL PRODUCTIVITY AT FIELD, WATERSHED AND REGIONAL SCALES
Location: Hydrology and Remote Sensing Laboratory
Title: Spectral Bio-indicator simulations for tracking photosynthetic activities in a corn field
| Cheng, Yen-Ben - |
| Middleton, Elizabeth - |
| Huemmrich, K - |
| Zhang, Qingyuan - |
| Corp, Lawrence - |
| Campbell, Petya - |
Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: April 20, 2011
Publication Date: August 21, 2011
Citation: Cheng, Y., Middleton, E.M., Huemmrich, K.F., Zhang, Q., Corp, L., Campbell, P., Kustas, W.P. 2011. Spectral bio-indicator simulations for tracking photosynthetic activities in a corn field [abstract]. SPIE Remote Sensing and Modeling of Ecosystems for Sustainability VIII Conference. 2011 CDROM.
Accurate assessment of vegetation canopy optical properties plays a critical role in monitoring natural and managed ecosystems under environmental changes. In this context, radiative transfer (RT) models simulating vegetation canopy reflectance have been demonstrated to be a powerful tool for understanding and estimating spectral bio-indicators. In this study, two narrow band spectroradiometers were utilized to acquire observations over corn canopies for two summers. These in situ spectral data were then used to validate a two-layer Markov chain based canopy reflectance model for simulating the Photochemical Reflectance Index (PRI), which has been widely used in recent vegetation photosynthesis and light use efficiency (LUE) studies. The PRI derived from in situ narrow band hyperspectral reflectance exhibited clear response to 1) viewing geometry corresponding to the light environment and 2) seasonal variation corresponding to the growth stage. The RT model utilized (ACRM; Kuusk, 2001) successfully simulated the response to the viewing geometry. The best simulations were obtained when the model was set to run in the two layer mode using the sunlit leaves as the upper layer and shaded leaves as the lower layer. Simulated PRI values yield much better correlations with in situ observations during the early growth, vegetative and reproductive stage (r=0.78 to 0.86) than in the senescence stage (r=0.65). Further sensitivity analysis was conducted to show the importance of leaf area index (LAI) and the sunlit/shaded ratio for the PRI simulations.