[Scale invariance analysis of the ten-day sunshine duration in Henan Province, China].

Using the ten-day sunshine duration data of 107 meteorological stations in Henan Province from 1961 to 2012, spatial-temporal variation characteristics of ten-day sunshine duration were analyzed, and the scale invariance analysis of ten-day sunshine duration was studied by using the method of detrended fluctuation analysis. The results showed that the means of ten-day sunshine duration and its standardized error among stations were 57.90 and 9.18 h, respectively, and their probability distributions were not subject to normal distribution. The cumulative abnormal of sunshine duration had a distinct linear increasing trend, however, its square deviation among the stations was of phase characteristics. The scale index of ten-day sunshine of each station was above 0.5, indicated that time series of scale index was of permanence. Variation of scale index among stations was small, which obeyed the normal distribution.

[Comparison of methods for estimating soybean leaf area index].

Leaf area index (LAI) is an important biophysical parameter, and is the critical variable in many ecology models, productivity models and carbon circulation study. Based on the field experiment data, an evaluation of soybean LAI retrieval methods was conducted using NDVI (normalized difference vegetation index) and RVI (ratio vegetation index), principle component analysis (PCA) and neural network (NN) methods, and the estimate effects of three methods were compared. The results showed that the three methods have an ideal effect on the LAI estimation. R2 of validated model of vegetation indices, PCA, NN were 0.753 (NDVI), 0.758 (RVI), 0.883, 0.899. PCA and NN methods were better with higher precision, and PCA method was the best, as its RMSE (0.202) was slower than the two vegetation indices (RMSEs of NDVI and RVI were 0.594 and 0.616) and NN (RMSE was 0.413) method. While the LAI was small, vegetation indices were obvious for removing the noise from soil and atmospheric effect and obtained the good evaluation result. PCA showed better effect for all LAI. LAI affected the estimating result of NN method moderately. As for the NN method, modeled LAI value and measured LAI regression formula slope was the nearest to 1 with R2 of 0.949, which showed a great potential for LAI estimating. As a whole, PCA and NN methods were the prior selection for LAI estimation, which should be attributed to the application of hyperspectral information of many bands.

[Bio-optical model of total suspended matter based on reflectance in the near infrared wave band for case-II waters].

From August to October, 2006, reflectance spectra were measured in a turbid Case-Il waters condition with an ASD FieldSpec spectrometer for a total of 58 samples. Based on the observation of reflectance curves, spectral analysis was carried out over 400-1200 nm. Showing the typical character of Case-II waters, the reflectance values were generally higher than those in other similar studies. Strong backscattering of high concentration total suspended matter (TSM) contributed considerably to the total reflectance spectra in water. Two obvious TSM reflectance peaks were observed in the near infrared wave bands, i.e., 808 and 1067 nm, especially the latter one that was never reported before. The highest correlation coefficient between reflectance and concentrations of TSM existed at 873 nm. Based on the simplification of water inherent optical parameters in the near-infrared wave band, including absorption of TSM, Chlorophyll-a (Chl-a) and chromophoric dissolved organic matter (CDOM), and backscattering of pure water, Chl-a and CDOM, three empirical equations of the bio-optical model using reflectance at 808, 873 and 1067 nm respectively were established to estimate the concentrations of TSM. Compared with linear and exponential models, the bio-optical model showed fairly good performance with comparatively high determination coefficient (r2) and low root mean squared error (RMSE), which confirmed the applicability of the bio-optical model to retrieve concentrations of TSM effectively in turbid Case-II waters.