Leaf biochemical properties indicate the growing status of natural vegetation and crops and are the main input variables of many ecological models. Remote study of leaf biochemical properties by measuring reflectance from various platforms has become an important tool for understanding the functioning of terrestrial ecosystems. Two main approaches are generally used to measure leaf biochemical properties with hyperspectral remote sensing: model inversion and indices. Although both approaches have been applied in various ecosystems, neither approach has been used to estimate leaf biochemical properties in arid ecosystems based on hyperspectral data.
Populus euphratica is an important tree species in arid lands. It is one of the oldest species of the original desert riparian ecosystem and is important for conserving and improving the ecology and environment in arid areas. Unlike other tree species, P. euphratica produces polymorphic leaves, i.e. leaf shape varies with growth stage and height in the canopy.
In order to evaluate the applicability of the inversed PROSPECT model in arid ecosystems, which has been widely applied to non-arid ecosystems, and determine hyperspectral indices for leaf biochemical properties of plants in arid ecosystems, leaf biochemical properties were estimated using both model inversion and hyperspectral indices for the polymorphic leaves of P. euphratica in arid lands. Reflectance spectra and biophysical/biochemical properties along the vertical axis of P. euphratica canopies were measured at Aragan region in the lower reaches of the Tarim River.
The results showed that both the shapes and biochemical properties of P. euphratica leaves were found to change with the heights from ground surface. The results indicated that the model inversion calibrated for each leaf shape performed much better than the model calibrated for all leaf shapes, and also better than hyperspectral indices. Similar results were obtained for estimations of equivalent water thickness (EWT) and leaf mass per area (LMA). Hyperspectral indices identified in this study for estimating these leaf properties had root mean square error (RMSE) and R2 values between those obtained with the two calibration strategies using the inversed PROSPECT model. Hence, the inversed PROSPECT model can be applied to estimate leaf biochemical properties in arid ecosystems, but the calibration to the model requires special attention.
The study was supported by the West Light Talents Cultivation Program of Chinese Academy of Sciences (XBBS 200801), the National Natural Science Foundation of China (40801146), and the JSPS Project (21403001).
The main finding has been published on Journal of Arid Land, 2012, 4(1): 52-62. The paper is also archived at http://jal.xjegi.com/EN/abstract/abstract124.shtml
