Research On Data Acquisition And Management Technology For Crop Information Monitoring

Agricultural information (AI) is an effective technology support to ensure national commissariat safety, promote adjustment of agricultural structure, exploit agricultural resources, protect agricultural resources and environment, expand agricultural market, prevent and reduce agricultural disaster, and achieve sustainable agricultural development and so on. And agricultural Information Monitoring (AIM) must be of pith and moment and a long-term operational task. AIM requires not only facile and accurate information, data, knowledge related to the agricultural production processing, as well as efficient management of them. So, this paper aims to study farming field data acquisition, integrated data management, and preprecessing.It is the premise and key for agricultural condition monitoring to obtain farmland data timely and accurately and learn the spatio-tempora dynamic change information. Systemic study has been done about the status and problems of obtaining technology for farmland parameter. At first, this paper focuses on the agricultural information acquisition technology to solve the problem of data sources. Then, this paper studies data transmission and communication techniques, resolve key problems of data transmission stream and acquisition stream. At last, in principle of feasibility, economy and stability, this paper establishes system of field parameter acquisition, and structures two acquisition systems on the basis of existing platform, which realized data warehousing automatically by WSN technique, and online data acquiring and updating in mobile mode through sharing platform and mobile terminal.AIM-related data has the characteristics of immense amount, multiple sources with diverse structures and in various temporal and spatial scales. Though, it’s challenging applications of multivariate and multi-service. It is fundamentally to overcome difficulties of low security in single-file-managing mode and slowness of queries, then to construct a secure, efficient, and standard DBMS dealing with immense amount of agricultural data.Using key technologies such as user-role-permission, data encryption, data backup, space vector and image data organization model, metadata, data dictionary, etc, I constructed national agricultural information monitoring database which is a complex of image, grid, vector, attribute, and multimedia data, set up by Oracle lOg, ArcGIS9.2, and programming utilities, etc.To extend the comprehensive utilization ability of farmland field monitoring data, to research preprocessing of them, on the basis of researching spatial expression technique, we proposed a spatial interpolation method of farmland soil moisture/temperature data based on results of image classification. Meanwhile, I conducted study on spatial grid data confusion technology based on spatial products of agricultural information and spatial and temporal resolution difference of images. Finally, I did system integration, to complete the operational data preprocessing required.Through above studies and system integration, the outcome provided available data support for AIM, and also certain acquired technique innovation.1. WSN(Wireless Sensor Network)-based and WebGIS-based online acquiring and updating farmland field parameters.Depending on Research Group’s WSN acquiring system of farmland field parameter, we developed platform for data accepting and data warehousing data correction automatically, realizing online acquiring fixed point farmland field parameter. However, it is not realistic to massively use wireless network to acquire data at present, so I take advantage of network technology, WebGIS technology to develop update online platform to realize farmland field parameter mobile acquisition. Systematic platform provide update online service for spatial data, including farmland field survey GPS points, vector spatial data recording, editing and version saving, etc.2. The characteristic Metadata and data dictionary is created in the stage of agricultural information database establishmentFirst, spatial-temporal models such as space vector, image grid are completely adopted to realize effective organization of the immense amounts of multiple source data by upgrading data compression and storage efficiency. In order to promote efficiency of data inquiry and searching, metadata and data dictionary is proposed based on the characteristic of agricultural information monitoring and data functional demand for monitoring. Moreover, I designed efficient data structure such as management attribute, vector, grid, original image, image products, etc. Data redundancy, filling the information is effectively overcome by these methods, thus, data connection is increased, meanwhile, detailed data dictionary, data relation, data type, data security level is formulated to ensure data update and data security.3. Spatial interpolation flow of farmland soil moisture observation data is improvedThis paper proposed spatial interpolation flow based on classification results of remote sensing data as a media. Under the classification result controlled conditions, the classification was carried out. The idea overcomes the blindness of traditional spatial interpolation, monitoring, and the accuracy of the interpolation is improved.