As so far, studies based on remote sensing to explore ozone column concentration keep a watchful eye on the stratosphere or troposphere, while few focus on the near-surface, though it directly correlative to human health. In this paper, the regional near-surface total column ozone was inversed based on the moderate-resolution imaging spectroradiometer (MODIS) for its extraordinary spatial resolution. First, the statistical synthetic regression algorithm was utilized to retrieve the first guess. A nonlinear physical iterative method was then employed to acquire final ozone profiles. Finally, after creating a unique database, the ozone column concentration was obtained by using the multivariable linear regression model. Compared with the measurements of ground monitoring sites, the retrieval results were over 95% accurate and its distribution consists with the actual situation. The method proposed in this paper can be applied to monitor air pollution.
Untreated and annealed PVDF films in same crystalline phase were fabricated via different processes, and the effects of annealing treatment on the dielectric properties of PVDF films were studied. It has been found that the annealing treatment eliminates the micro pores in the PVDF films. As a result, the annealing treatment shows to exert strong influence on the relative permittivity and leakage current of PVDF films. Compared with common untreated PVDF film, the annealed PVDF film presents a higher relative permittivity about 8.7 in a 1 kHz electric field and a lower leakage current around 3.04 μA under a 1000 kV/cm electric field. However, the annealing treatment has little effect on the dissipation factor.
This article presents an analysis of the scattering measurements for an entire wheat growth cycle by ground-based scatterometers at a frequency of 5.3 GHz. Since wheat ears are related to wheat growth and yield, the radar backscatter of wheat was analyzed at two different periods, i.e., with and without wheat ears. Simultaneously, parameters such as wheat and soil characteristics as well as volume scattering and soil scattering were analyzed for the two periods during the entire growth cycle. Wheat ears have been demonstrated to have a great influence on radar backscatter; therefore, a modified version of water-cloud model used for retrieving biomass should consider the effect of wheat ears. This work presents two retrieval models based on the water-cloud model and adopts the advanced integral equation model to simulate the soil backscatter before the heading stage and the backscatter from the layer under wheat ears after the heading stage. The research results showed that the biomass retrieved from the advanced synthetic aperture radar (ASAR) images to agree well with the data measured in situ after setting the modified water-cloud model for the growth stages with ears. Furthermore, it was concluded that wheat ears should form an essential component of theoretical modeling as they influence the final yield.
A biomass inversion algorithm based on a semi-empirical scattering model has been developed by using the simultaneous observation data, which are obtained by ground-based and space-based scatterometers during the rice-growing season. Three steps are applied to build the algorithm: (1) the backscattering coefficients are collected in eight acquisitions at different growth periods. Meanwhile, the ground-truth data are measured, such as rice biomass, leaf-area index, and canopy height and related ecophysiological canopy variables. Moreover, three scenes of advanced synthetic aperture radar (ASAR) AP images covering the study area are acquired. (2) The inversion models are built based on a semi-empirical rice water-cloudy model with the data measured in field. The rice backscattering coefficients of HH and VV polarizations are the input parameters. (3) By processing the ASAR images, the backscattering coefficients are extracted and input to the inversion model, and then the rice biomass maps are outputted at three different periods’ images. By comparing the rice biomass measured with the inverse values from the scattering data and SAR images, it shows that the inversion values are considerably consistent with the true measured values. The inversion results show that the multitemporal SAR images at the C-band can be used to monitor the growth of rice by using the semi-empirical inversion model.
A microwave backscattering model of winter wheat based on the vector radiative transfer theory has been established. The model focused on the distribution of wheat ears that are directly related to the yield. In addition, characteristics of the wheat growth have been adequately considered. Compared to the measured values, the model effectively simulated the microwave backscattering characteristics of winter wheat. Intercomparison of the winter wheat model and modified Michigan Microwave Canopy Scattering (MIMICS) model using experimental data shows that the winter wheat model had better cross-polarized simulation results than the modified MIMICS model did. This improvement was attributed to the special attention paid to the cross-polarization after the booting stage. After booting, wheat ear started to appear and grow in size. Wheat ear contributed greatly to cross-polarized backscatter. The inclusion of the ear as one of the model components was significant in modeling the observed cross-polarized backscattering.
A neural network (NN) algorithm to invert biomass of rice plants using quad-polarization radar datasets of ground-based scatterometer and spaceborne RADARSAT-2 has been studied. The NN is trained with pairs of multipolarization radar backscattering and biomass data. The backscattering data are simulated from a Monte Carlo backscatter model that uses the outputs from a growth model of the rice plant. The growth model is developed from the plant data collected in growing cycles of several years. In addition to producing parameters needed by the backscatter model, the growth model outputs the biomass value of the plant. Multipolarization data collected by a ground-based scatterometer at eight stages during the 2012 growing cycle are input to the NN to invert biomass. Satisfactory results are obtained due to a small root mean squared error (RMSE) of 0.477 kg/m 2 and a high correlation coefficient of 0.989 when the inverted and measured biomass values are compared. Finally, RADARSAT-2 synthetic aperture radar images acquired on four different dates during the 2012 growth period are analyzed to delineate rice paddies within the study area and to invert biomass using the NN. Inversion results from the delineated rice paddies are encouraging because the RMSE is 0.582 kg/m 2 and correlation coefficient is 0.983.
After over twenty years since the demonstration of the first QKD systems in 1989 there have been two categories of
QKD systems, namely fiber QKD systems and wireless QKD systems. The security of a practical QKD system over
wireless optical paths is degraded due to imperfectness of devices and channel loss. Very simple attacks, such as beamsplitting
attacks (BS), could jeopardize the security of polarization coding QKD systems. Among all the attacks photon
number splitting (PNS) is the most threatening one against the security of polarization coding QKD systems. The upper
bound for secure transmission length of free-space QKD systems based on polarization coding under PNS attacks is
provided here as well as the secure transmission criterion. The theoretic results predicted in this paper accord with
experimental results of Manderbach's work.
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