TP77椭圆偏振光测厚仪功能的拓展研究

成功地将TP77椭圆偏振光测厚仪改装成以卤钨灯或氙灯为光源的广谱椭偏仪 .改装后的椭偏仪不含λ/4波长片 ,而配有一型号为WDG5 0 0 1A的单色仪和一个X Y函数记录仪 ,它可用来测量固体薄膜和片状材料的折射指数n(λ)和消光指数k(λ) .

Dynamic Variation and Simulation of Extinction Coefficient of Corn Population

[Objective] The aim was to study the dynamic variation of extinction coefficient of corn population, so as to improve the accuracy of assessment on net primary productivity （NPP） or yield. [Method] Based on the data of photosynthetic active radiation and leaf area index during corn growing season （from May to September） in 2006, observed in Jinzhou observation station of corn farmland ecosystem, China Meteorological Administration, the dynamic variation of extinction coefficient of corn population was analyzed. [Result] There was a great daily variation in the extinction coefficient of corn population during growing season, and the maximum value appeared from 7：00 to 9：00 and from 15：00 to 17：00, while the minimum could be found around 12：00, but the amplitude of variation decreased in tasseling stage. On a large time scale （5 d）, there was a parabolic relationship between extinction coefficient （K） and leaf area index （LAI）, with determination coefficient R2 of 0.960 7. The simulation equation of extinction coefficient, based on the sun elevation angle or leaf area index, had poor accuracy at various time during growing season, so a new dynamic model of extinction coefficient was established, namely K=λ（0.784 8-0.001 6θ）（0.154 8LAI2-0.558 6LAI＋0.654）. [Conclusion] The effect of sun elevation angle and leaf area index on extinction coefficient during corn growing season was considered in the new dynamic model of extinction coefficient, and its simulated result was superior to that of single-factor model.

Satellite-based Estimates of Canopy Photosynthetic Parameters for an Alpine Meadow in Northern Tibet

Plant photosynthesis is the fundamental driver of all the biospheric functions. Alpine meadow on the Tibetan Plateau is sensitive to rapid climate change, and thus can be considered an indicator for the response of terrestrial ecosystems to climate change. However, seasonal variations in photosynthetic parameters, including the fraction of photosynthetically active radiation by canopy(FPAR), the light extinction coefficient(k) through canopy, and the leaf area index(LAI) of plant communities, are not known for alpine meadows on the Tibetan Plateau. In this study, we used field measurements of radiation components and canopy structure from 2009 to 2011 at a typical alpine meadow on the northern Tibetan Plateau to calculate these three photosynthetic parameters. We developed a satellite-based(NDVI and EVI) method derived from the Beer-Lambert law to estimate the seasonal dynamics of FPAR, k,and LAI, and we compared these estimates with the Moderate Resolution Imaging Spectroradiometer(MODIS) FPAR(FPAR_MOD) and LAI product(LAI_MOD). The results showed that the average daily FPAR was 0.33, 0.37 and 0.35, respectively, from 2009 to 2011, and that the temporal variations could be explained by all four satellite-based FPAR estimations, including FPAR_MOD, an FPAR estimation derived from the Beer-Lambert law with a constant k(FPAR_LAI), and two FPAR estimations from the nonlinear functions between the ground measurements of FPAR(FAPRg) and NDVI/EVI(FPAR_NDVI and FPAR_EVI). We found that FPAR_MOD seriously undervalued FPARg by over 40%. Tower-based FPAR_LAI also significantly underestimated FPARg by approximately 20% due to the constant k(0.5) throughout the whole growing seasons. This indicated that using FPAR_LAI to validate the FPAR_MOD was not an appropriate method in this alpine meadow because the seasonal variation of k ranged from 0.19 to 2.95 in this alpine meadow. Thus, if the seasonal variation of k was taken into consideration, both FPAR_NDVI and FPAR_EVI provided better descriptions, with negligible overestimates of less than 5% of FAPRg(RMSE=0.05), in FPARg estimations than FPAR_MOD and FPAR_LAI. Combining the satellite-based(NDVI and EVI) estimations of seasonal FPAR and k, LAI_NDVI and LAI_EVI derived from the Beer-Lambert law also provided better LAIg estimations than LAI_MOD(less than 30% of LAIg). Therefore, this study concluded that satellite-based models derived from the Beer-Lambert law were a simple and efficient method for estimating the seasonal dynamics of FPAR, k and LAI in this alpine meadow.