Construction and implementation of an automatic algorithm for generating information of geological disaster floor risk warning products based on GIS and GDAL

Since 2003, mainland China has carried out regional geological disaster early warning work during the flood season and formed early warning products to be released to the public, which plays an important role in geological disaster prevention and control. The geological disaster warning description information is an important component of the geological disaster warning product, including the warning range, grade, time period, and text description. In order to quickly form authoritative, scientific, and accurate information, this paper studies a technical algorithm that can efficiently and automatically analyze and form preliminary early warning product description information and conducts verification analysis on the algorithm. The algorithm uses the administrative division map and early warning division map of the study area as data sources.Based on the designed three-level warning level as the main key of the set concept model of the warning level, Using GIS technology, through the use of spatial information superposition and discrimination, the calculation of the distribution area ratio of the warning level, the description of the distribution range of the warning level, and the calculation of the unit distribution orientation of the warning level as key methods, the information on the map can be quickly Converted to an intuitive text description, the automatic acquisition of early warning product description information can be realized.In the verification process, 11 virtual townships are designed as the warning range. The warning zoning layer takes 3×3KM as the warning level unit. The total number of warning units is 5194, and the file is in Shapefile format. The verification process is based on the GDAL library (Geospatial Data Abstraction Library)and the C++ language. A software tool is designed for the algorithm, and the experimental data is used for verification and analysis. The results show that the early warning description information formed by the algorithm is completely consistent with the spatial presentation results of the early warning zoning layer, and the calculation process is efficient and fast, which can significantly improve the precision of early warning. It is fully suitable for promotion and use in practical work.