Research On Data Processing For Agro-meteorological Disaster Monitoring And Forecasting Of Fruits

The frequent occurrences of agro-meteorological disasters seriously affect the rapid and healthy development of China’s agricultural production. How to establish the disaster assessing and defending systems is the focal point of researches on agro-meteorological disasters. Though the development of Geographic Information System (GIS) provides advanced methods for the monitoring and analyzing of the spatial and temporal distribution of agro-meteorological disasters, the high price of traditional stand-alone GIS system limits the popularization of them. The rapid development of Internet technology makes WEBGIS be a new platform for GIS and makes it possible to extend the restricted GIS functionalities from the relatively limited network to a broader space. In recent years, researches on agro-meteorological disaster prevention in China are mainly focused on the combination of efficiently active defense technology using agro-climatic resources and passive defense technology of disaster prevention and preparation. So far, it achieved good results in the defense of agricultural drought and cold damage.Based on previous studies, this paper carries out researches in combination with the project, agro-meteorological disaster monitoring and forecasting system, for fruits, supported by public service sectors (WMO) funding. To provide a new platform agro-meteorological disaster monitoring and forecasting system, this paper takes out a lot of spatial analysis (such as overlay analysis and spatial interpolation analysis etc.) to study the association among weather phenomena. The main research work of this paper includes:(1) Spatial data query. This paper introduced spatial data management and query optimization techniques, mainly focused on spatial indexing mechanisms of R-tree indexing series and Quad tree indexing series, which lays the foundation for further study.(2) Quality assurance of spatial data. To ensure data accuracy, consistency and reliability, this paper carries out researches on data preprocessing, normalized operation, rule-based Digital Line Graphic (DLG), etc. For DLG, template matching method and user-defined rules are used to ensure the data quality; and for meteorological data detected by automatic weather stations, we studied spatial distribution of the data and the normalization operations, which provide the standards-compliant data for the spatial analysis.(3) Spatial analysis. This paper conducts a series of spatial analyses, including spatial data processing, overlay analysis and spatial interpolation. In addition, this paper takes comparative studies of the mixed interpolation method and geostatistical spatial interpolation methods. Besides, downsizing interpolation method is proposed, which is verified to be an effective interpolation method.(4) Implementation of agro-meteorological disaster monitoring and forecasting system for fruits. The system contains many useful functions, such as the common GIS functions, data query and output functions, spatial interpolation, as well as special statistics. It provides an avenue for agro-meteorological monitoring and forecasting.