Research On The Interpolation Algorithm For The Geological Space Visualization

Along with the construction of "digital Earth" and "the digital China", the development of the earth information science and the earth space information science is extraordinary rapid. Under the pressure of the increases sharply in the population, the crowded life space, the deficiency of natural resource and the natural environment worsening, the underground spatial three dimensional visualization research had already become the hot question in geology, geographic information system and computer science. The base of the visualization of the geological space is the geological investigation and reconnaissance data, but as a result of the questions like the condition of the working area and limitation of the fund, in the certain research region only limited drill hole and the geophysics reconnaissance data can be obtained, and these data is very difficult to satisfy the request of the construction of the three-dimensional space data field. This requests to use interpolation technology, selects the appropriate interpolation algorithm to density the data in the study area, uses the information contained in the data sufficiently, which is the essential step to realize the visualization of the geological space.The main research works are as follows:(1) Contrasts inverse distance weighting algorithm with Kriging Interpolation algorithm. Takes peaks surface as the known surface, contrasts and analyses the interpolation result of the inverse distance weighting algorithm and Kriging Interpolation algorithm which select different semi-variation function by two dimensional contour and three dimensional surface.(2) Gathers and analyses the primitive drill hole data of the interpolation algorithm. Chooses 146 drill holes data from 400 drill holes data in the Zhejiang-Jinhua to make up of the primary data, examines whether does the distribution of the stratum elevation data obey the normal distribution, discovers the global trend and the aeolotropism existing in the data, and according the result, using the tool to transform the data to normal distribution, simulate the global trend and rejects the data aeolotropism, thus increases the interpolation precision.(3) Obtains the interpolation result. According to the result of exploring data analysis, appoints a number of parameters step by step, deals the data with the structural interpolation processing, then obtains the interpolation result.(4) Determines the quality of the interpolation result. Uses the Cross-validation to determine...