Excess heavy metal, for example, copper, in vegetation will depress the normal plant growth, and the yield of such plant will be harmful if they are loaded into the food chain. Spectroscopy is thought as an efficient noncontact method on detecting the heavy metal in vegetation. This paper is aimed at retrieving the copper ion content in copper-stressed tobacco leaves from hyperspectral data by inverting a modified radiative transfer (RT) model. The dataset regarding the reflectance spectra, biochemical components, and copper ion contamination of copper-treated leaves was obtained from a laboratory experiment on spectral data from copper-treated tobacco. A simultaneous inversion on multiple parameters was conducted to explore the difficulties in estimating copper ion concentrations without considering the correlation between input parameters. This simultaneous inversion produced an unsatisfactory result, with the correlation coefficient (R) and root-mean-squared error (RMSE) being 0.12 and 0.021, respectively. Then, the sensitivity of the input parameters of the RT model was analyzed. Based on the sensitivity bands and the RT model, a concrete procedure for a multiobjective and multistage decision-making method was defined to perform the inversion of the copper ion content. The accuracy of the inversion results was improved significantly, and the values of the R and RMSE were 0.60 and 0.015, respectively. The proposed method fully considers the correlativity among the model parameters. Additionally, the method promises to provide a theoretical basis and technical support for heavy metal monitoring using the spectroscopy method.

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Intelligent Transportation System (ITS) is a valid utility to solve the problem of heavy traffic and ensuring safety of traffic and transportation, especially in large city, e.g. Beijing. A WebGIS system functioning to provide real-time road condition information was developed in this paper. In order to ensure the logic and reliability of data management, a uniform GeoDatabase space database was established based on these three factors as below: the difference of travel volume in different time and road, real time dynamic updating traffic database, and the traffic space dataset in Beijing. In this GeoDatabase the right connectivity of multi-layer data was investigated. In the shortest road search routine, some parameters, such as traffic flow and the length of cond path, which may be concerned by many users, were used as weights to determinate an optimal road. The dynamic updating data could be stored in the database in the format of GeoDatabase, the quantitive research to determine the optimal weight coefficient of travel carrying capacity could be available through proper traffic model and real time dynamic updating data. Besides, the final traffic model would be formed considering the length of optimal path. This intelligent transportation WebGIS inquiry system is developed on base of Visual Studio.NET and Arcgis Server platform. The system would publish data through Web server and supply clients with the service to inquire the real time optimal travel path in Beijing.

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