[Study on multi-angular polarized spectrum characteristics of leaf based on some indoor experimental data].

In the present study, we acquired multi-angular polarized spectrum of three kinds of leaves with different surface structures, and calculated the multi-angular spectral degree of polarization DOP based on Stokes parameters to explore its variation tendency with wavelength and the relationship between the leaf polarized reflectance and its physiological parameters and the relative observational geometric condition. The results show that although the spectral degree of polarization of the 3 kinds of leaves has obvious differences in value because of the leaf surface structures, the general trend of the DOP curve keeps consistent, and this trend could be explained by analyzing the properties of both specular and diffuse components of the leaf reflectance. The peak value of the DOP appears in the specular direction of the principal plane, and grows with the increase in the incident zenith angle. The analysis of the data demonstrates that compared to the other two experimental bands, the near infrared band shows a better discrimination in showing the relationship between DOP and the observational geometric configuration for all the three kinds of leaves, but the value of the DOP is smaller. Considering the effect of variation in chlorophyll content, DOP of the red band has more stable value than the near infrared band, whereas the water content has barely influence in both of the bands.

[Retrieval of spectral characteristics of hyperspectral sensor and retrieval of reflectance spectra].

On-orbit spectral calibration of hyperspectral imaging data is a key step for quantitatively analyzing them. Like the atmospheric correction, accurate spectral calibration is very necessary for improved studies of land or ocean surface properties. Based on the previous literatures, a new method which coupled an optimization algorithm was developed to simultaneously retrieve the central wavelength and the full width at half maximum (FWHM) of the hyperspectral sensor without needing the in situ reflectance spectra. Firstly, the Hyperion data set simulated using MODTRAN4 with the Hyperion spectral specification was used to test the new method, and the results indicated that the maximum error was less than 0.1 and 0.7 nm for central wavelength and FWHM respectively when the spectral shift is 5 nm. Then the algorithm was applied to the Hyperion data acquired on May 20, 2008 over Heihe River Basin and it was iteratively performed for each detector of the two spectrometers of Hyperion. The results showed that the VNIR of Hyperion had a pronounced smile effect, and the shift in on-orbit calibration with respect to the laboratory was from -2 to +2 nm, while the SWIR has essentially no smile effect, the wavelength correction was relatively flat over all sample with an approximately constant value of 3 nm. The FWHM in VNIR could range from -0.2 to 0.5 nm as a function of sample number of the spectrometer, and in SWIR it ranged from -2 to -3 nm. So for both the VNIR and SWIR, the original spectral calibration should be updated. These results showed good agreement with previous research findings, and which also proved the feasibility of the new method. Finally, with the updated spectral calibration characteristics, the sample reflectances of desert and vegetation target in our study site were reconstructed by applying a further atmospheric correction, and as expected, the strong spikes around the typical atmospheric absorption were almost disappeared.

[Winter wheat growth spatial variation study based on temporal airborne high-spectrum images].

Precision agriculture technology is defined as an information-and technology-based agriculture management system to identify, analyze and manage crop spatial and temporal variation within fields for optimum profitability, sustainability and protection of the environment. In the present study, push-broom hyperspectral image sensor (PHI) image was used to investigate the spatial variance of winter wheat growth. The variable-rate fertilization contrast experiment was carried out on the National Experimental Station for Precision Agriculture of China during 2001-2002. Three airborne PHI images were acquired during the wheat growth season of 2002. Then contrast analysis about the wheat growth spatial variation was applied to the variable-rate fertilization area and uniformity fertilization area. The results showed that the spectral reflectance standard deviation increased significantly in red edge and short infrared wave band for all images. The wheat milky stage spectral reflectance has the maximum standard deviation in short infrared wave band, then the wheat jointing stage and wheat filling stage. Then six spectrum parameters that sensitive to wheat growth variation were defined and analyzed. The results indicate that parameters spatial variation coefficient for variable-rate experiment area was higher than that of contrast area in jointing stage. However, it decreased after the variable-rate fertilization application. The parameters spatial variation coefficient for variable-rate area was lower than that of contrast area in filling and milking stages. In addition, the yield spatial variation coefficient for variable-rate area was lower than that of contrast area. However, the yield mean value for variable-rate area was lower than that of contrast area. The study showed that the crop growth spatial variance information can be acquired through airborne remote sensing images timely and exactly. Remote sensing technology has provided powerful analytical tools for precision agriculture variable-rate management.

[Optical methods for in situ measuring leaf area index of forest canopy: a review].

Leaf area index (LAI) is an important parameter of canopy structure, because it relates to many biophysical and physiological processes of canopy, including photosynthesis, respiration, transpiration, carbon cycling, precipitation interception, and energy exchange, etc. This paper introduced the theoretical bases and mathematical models of optical methods for forest canopy LAI determination, introduced the principles, merits, and drawbacks of currently used optical methods, and summed up the main sources of the errors in LAI optical measurement, including clumping effect, non-photosynthesis components, measurement conditions, and terrain effect. The developing status of quantitatively evaluating clumping effect, non-photosynthesis components, and terrain effect was analyzed, and the promising development directions of optical methods for measuring forest canopy LAI were discussed.