Location: Hydrology and Remote Sensing Laboratory
Title: The photochemical reflectance index from directional cornfield reflectances: Observations and simulations Authors
Submitted to: Remote Sensing of Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: May 30, 2012
Publication Date: July 4, 2012
Citation: Cheng, Y., Middleton, E.M., Zhang, Q., Corp, L.A., Dandois, J., Kustas, W.P. 2012. The photochemical reflectance index from directional cornfield reflectances: Observations and simulations. Remote Sensing of Environment. 124:444-453. Interpretive Summary: Remotely sensed spectral bio-indicators have the potential to play a critical role in monitoring and modeling plant processes, including the exchange of carbon, in time and space for agro-ecosystems. This is because uncertainties exist in how agro-ecosystems will function and what feedbacks to expect, especially under disturbances induced by the changing climate. One of the widely used concepts to model carbon uptake by plants is the light use efficiency (LUE) model. Previous studies have shown that LUE can vary based on vegetation type, environmental conditions, and temporal resolution of the observations. A remotely sensed bio-indicator, the Photochemical Reflectance Index (PRI) is closely related to LUE. However, PRI is affected by canopy structure associated with variable fraction of sunlit/shaded leaves. The capability of the two-layer Analytical Canopy Reflectance Model for PRI simulations in a cornfield at different growth stages is evaluated. The performance of the model is greatly improved when the crop is dominated by green foliage during the vegetative and mature reproductive stages. The least satisfactory results were found when the corn crop reached the senescent stage. The significance of taking both sunlit and shaded leaf segments into account for canopy PRI studies is documented. The analysis suggests that canopy structure information might be needed to improve simulations or to interpret PRI observations. These findings also imply that canopy PRI observations and model simulations need to be investigated for more crop types.
Technical Abstract: The two-layer Markov chain Analytical Canopy Reflectance Model (ACRM) was linked with in situ hyperspectral leaf optical properties to simulate the Photochemical Reflectance Index (PRI) for a corn crop canopy at three different growth stages. This is an extended study after a successful demonstration of PRI simulations for a cornfield previously conducted at an early vegetative growth stage. Consistent with previous in situ studies, sunlit leaves exhibited lower PRI values than shaded leaves. Since sunlit (shaded) foliage dominates the canopy in the reflectance hotspot (coldspot), the canopy PRI derived from field hyperspectral observations displayed sensitivity to both view zenith angle and relative azimuth angle at all growth stages. Consequently, sunlit and shaded canopy sectors were most differentiated when viewed along the azimuth matching the solar principal plane. These directional PRI responses associated with sunlit/shaded foliage were successfully reproduced by the ACRM. As before, the simulated PRI values from the current study were closer to in situ values when both sunlit and shaded leaves were utilized as model input data in a two-layer mode, instead of a one-layer mode with sunlit leaves only. Model performance as judged by correlation (r) and root mean square error (RMSE) between in situ and simulated values was strongest for the mature corn crop (r = 0.87, RMSE = 0.0048), followed by the early vegetative stage (r = 0.78; RMSE = 0.0051) and the early senescent stage (r = 0.65; RMSE = 0.0104). Since the benefit of including shaded leaves in the scheme varied across different growth stages, a further analysis was conducted to investigate how variable fractions of sunlit/shaded leaves affect the canopy PRI values expected for a cornfield, with implications for remote sensing monitoring options. Simulations of the sunlit to shaded canopy ratio near 50/50 +/- 10 (e.g., 60/40) matching field observations at all growth stages were examined.