基于ArcPy的克里金法自动插值技术研究
首发时间:2022-07-26
摘要:随着地理信息科学理论和方法的日臻完善,以及计算机软件技术的不断丰富和发展,地理信息行业软件迅速发展壮大,在地理信息、遥感领域的研究中得到了广泛应用,扩展了地理信息产业的服务能力和范围,但同时也暴露出一些问题。例如在生产实践和研究中,基于GIS软件的数据处理工作步骤繁杂,容易出错,主要表现在容差内的尺度匹配和精度匹配问题,多源与异步数据的融合校验;空间数据库的入库工作浪费了大量人力物力;大数据场景下对于自动化技术存在性能优化的迫切需求;使用地理信息行业软件制作特定用途的专题图存在制作成本较高、专业性强、工作强度高、制图格式不一致等问题;重复作业,效率不高;人工编辑序号耗时较长,易出现错误、标准不统一等问题。本文针对空间插值效率低下问题,选取北京市城六区房产价格数据作为示例数据,基于ArcPy站点包和ArcToolbox工具箱,研究自动插值的技术实现。结果表明,基于二手房价交易数据的克里金插值在考虑4种克里金法、11种半变异函数、21种步长时,相比传统ArcGIS手动插值,插值时间缩短约4倍,有望在克里金插值研究中推广使用,同时为基于ArcPy包的同类开发补充了案例验证。
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Research on Automatic Interpolation Techniques of Kriging Method Based on ArcPy
Abstract:With the improvement of the theories and methods of Geographic Information Science and the continuous enrichment and development of computer software technology, the software of geographic information industry has developed rapidly, and has been widely used in the research of geographic information and remote sensing, which has expanded the service capacity and scope of geographic information industry, but also exposed some problems. For example, in production practice and research, data processing based on GIS software is complicated and error prone, which is mainly manifested in the problems of scale matching and accuracy matching within tolerance, and the fusion and verification of multi-source and asynchronous data; The storage of spatial database wastes a lot of manpower and material resources; There is an urgent need for performance optimization of automation technology in the big data scenario; There are some problems in using geographic information industry software to make thematic maps for specific purposes, such as high production cost, strong professionalism, high work intensity, inconsistent mapping format, etc; Repeated operation, low efficiency; It takes a long time to edit the serial number manually, which is prone to errors, inconsistent standards and other problems. Aiming at the low efficiency of spatial interpolation, this paper selects the real estate price data of six districts in Beijing as an example data, and studies the technical implementation of automatic interpolation based on arcpy site package and arctoolbox toolbox. The results show that Kriging interpolation based on second-hand house price transaction data can shorten the interpolation time by about 4 times compared with traditional ArcGIS manual interpolation when considering 4 Kriging methods, 11 semivariograms and 21 steps, which is expected to be popularized and used in Kriging interpolation research. At the same time, it supplements case verification for similar development based on arcpy package.
Keywords: Automatic interpolation ArcPy Kriging method
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