According to client interactive operation in agricultural macroscopic decision-making eystem WebGIS publish, Ajax asynchronous communication technology and GWT-Ext were integrated into WebGIS. The Ajax technique used in the browser made the user getting part of the webpage information through the server possible. GWT-Ext is a Web interface element based on GWT (Google Web Toolkit) and Extjs development. GWT-Ext use Object Orient language Java and Ext component to develop Ajax applications, it is more efficient, shorten the development cycle. Based on the method in this paper the speed of server response and the interactivity can be improved.
Proc. SPIE. 8762, PIAGENG 2013: Intelligent Information, Control, and Communication Technology for Agricultural Engineering
KEYWORDS: Environmental monitoring, Visualization, Databases, Geographic information systems, Data acquisition, Telecommunications, Data centers, Wireless communications, Data communications, General packet radio service
To solve the problem on remote data real-time transmission and the analysis and management of the data in the agricultural environment monitoring, we had a detailed study of the principle of wireless communication SMS/GPRS and the technology of seamless integration with GIS. The system achieved the wireless real-time transmission of remote monitoring data by the SMS/GPRS technology and used the GIS visualization technology to display monitoring data visually. With the aid of the function of GIS spatial analysis the system analyzed the geographic area. The software system structure and key technologies had been solved. The system is suitable for departments of agriculture to acquire and communicate the environmental monitoring data, to manage the GIS, and to analyze the decision.
Based on remote sensing images, the panoramic views of land coverage distribution across a large geographic area can be accessed conveniently. In order to improve the accuracy of monitoring land use changes, the Chaos Genetic Algorithm was proposed. Chaos Immune Algorithm has capability of self-organizing, self-learning, self-recognition and self-memory, hence through the input samples the global optimization clustering center was found. And then the clustering center was employed to classify the view picture of remote sensing image. In this process, the ergodic property of chaos phenomenon was used to optimize the initial antibody population, so it could accelerate the convergence of Immune Algorithm. Through the clone selection operator, mutation operator and recruited antibody, local optimums were avoid. Chaos Immune Algorithm was applied to classify land use in Huainan –based on TM image. Based on confusion matrix, the classification of the Parallelepiped and Maximum likelihood methods were contrasted with Chaos Immune Algorithm. It is demonstrated that Chaos Immune Algorithm is superior to the two traditional algorithms, and its overall accuracy and Kappa coefficient reach 88.26% and 0.853respectively.