|Russ, Andrew - Andy|
|Kustas, William - Bill|
Submitted to: Ecological Informatics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/10/2010
Publication Date: 9/17/2010
Publication URL: http://handle.nal.usda.gov/10113/53861
Citation: Cheng, Y., Middleton, E.M., Huemmrich, K.F., Zhang, Q., Campbell, P., Corp, L.A., Russ, A.L., Kustas, W.P. 2010. Utilizing in situ directional hyperpectral measurements to validate bio-indicator simulations for a corn crop canopy. Ecological Informatics. 5:330-338. Interpretive Summary: A remote sensing field study and plant radiative transfer modeling experiments were conducted to understand the relation between leaf optical properties and a remotely sensed vegetation index called the Photochemical Reflectance Index (PRI). Good agreement between modeled and remotely-sensed PRI was observed, particularly when including shaded leaves in the lower part of the canopy. Other remotely sensed vegetation indices were also evaluated and shown to be insensitive to incorporating shaded leaves in the radiative transfer modeling. This result indicates that PRI is strongly influenced by plant physiological dynamics and vegetation structure. Thus the PRI has the potential for being used to monitor plant vigor and physiological status, very useful information for monitoring crop conditions. Further observations and modeling studies are planned to understand the effects of plant canopy structure parameters on the PRI.
Technical Abstract: Two radiative transfer canopy models, SAIL and the Markov-Chain Canopy Reflectance Model (MRCM), were coupled with in situ leaf optical properties to simulate canopy-level spectral band ratio vegetation indices with the focus on the Photochemical Reflectance Index (PRI) in a cornfield. In situ hyperspectral (FWHM~3 nm) measurements were made at both leaf and canopy levels. Leaf optical properties were obtained from both sunlit and shaded leaves. Canopy reflectance was acquired for eight different relative azimuth angles at three different view zenith angles, and later used to validate model outputs. Field observations of PRI for sunlit leaves exhibited lower values than shaded leaves, indicating higher light stress. Canopy PRI expressed obvious sensitivity to viewing geometry, both in view and azimuth angles. Overall, simulations from MCRM exhibited better agreements with in situ values than SAIL. When using only sunlit leaves as input, MRCM-simulated PRI values showed satisfactory correlation (r = 0.71) and RMSE (0.019) compared to in situ values. However, the performance of the MRCM model was significantly improved (r=0.86, RMSE=0.004) after defining shaded leaves as the lower canopy layer beneath a sunlit leaf layer. Four other widely used band ratio vegetation indices were also studied and compared with the PRI results. MCRM simulations were able to generate satisfactory simulations for these other four indices when using only sunlit leaves as input; unlike PRI, adding shaded leaves did not improve the performance of MCRM. These results support the hypothesis that the PRI is sensitive to physiological dynamics while the others detect static factors related to canopy structure. Sensitivity analysis was performed on MCRM in order to better understand the effects of structure related parameters on the PRI simulations. LAI showed the most significant impact on MCRM-simulated PRI among the parameters studied.