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GIS - based urban meteorological monitoring element interpolation analysis

Author: ZhaoHaiBo
Tutor: YangDeHong
School: Kunming University of Science and Technology
Course: Cartography and Geographic Information Systems
Keywords: Meteorological monitoring Analysis of spatial interpolation Cross-validation Geographic Information Systems
CLC: P412
Type: Master's thesis
Year: 2010
Downloads: 220
Quote: 0
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Abstract


Urban precipitation, temperature and other meteorological elements are closely related to people's daily life, but also affect the planning and construction of urban flood control, drainage works, so the city of Meteorological Elements accurate and comprehensive understanding of the current city attaches great importance to the problem. The limited the city meteorological monitoring points collected monitoring data do not meet the social needs of meteorological data products. Limited monitoring data collected, the use of spatial interpolation techniques of interpolation, has become the first choice of meteorological products cover the entire area being monitored. Speaking from a theoretical point of view, there are many studies on the spatial interpolation method, but the urban meteorological elements which interpolation method is more suitable for interpolation analysis became the subject of research, this study main content. GIS-based urban meteorological monitoring element interpolation analysis study the Kunming meteorological monitoring data, for example, study the suitability of the GIS spatial interpolation analysis for the city of Meteorological Elements interpolation analysis. This article is based on detailed research and analysis commonly used in the analysis of spatial interpolation interpolation method, using the secondary development of the ArcGIS platform the components ArcEngine developed for the city of Meteorological Elements interpolation analysis applications. The system not only to complete the interpolation analysis commonly used in meteorological elements, but also by several commonly used interpolation method in ArcGIS platform for cross-validation of meteorological monitoring records and statistics of the average error, mean absolute error, standard deviation, etc. error statistics storage into the system database. In order to facilitate interpolation analysis the research special designed and implemented based on these errors statistical analysis of the statistical records, the use of these features can be easily cross-validation results of the interpolation method meteorological elements for statistical analysis, assessment of the interpolation method parameters meteorological elements suitability. The study found: inverse distance weighted interpolation, Kriging interpolation is more appropriate for the city of Meteorological Elements interpolation analysis. Inverse distance weighted interpolation on the urban temperature interpolation analysis of the effect of significantly better than other methods, urban precipitation, continuous precipitation interpolation results are better; the interpolation analysis error of Kriging rainstorms in urban precipitation overall than other interpolation methods better, but the results grid is not smooth, the range beyond the original range of the phenomenon is more serious than the spline function; spline function interpolation results range phenomenon is more serious than monitoring records range function properties of grid very smooth, but the error statistics in general and Kriging interpolation, triangular linear interpolation, natural neighbor interpolation poor. Overall, GIS-based urban meteorological monitoring element interpolation analysis interpolation analysis module to the space of the GIS platform based on the use of software engineering ideas developed interpolation method suitable for the city of Meteorological Elements interpolation analysis system for research results analysis and discussion, visual display to provide convenient and efficient means. This paper has made a useful exploration of the GIS spatial interpolation of meteorological data products produced suitability.

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CLC: > Astronomy,Earth Sciences > Atmospheric science (meteorology ) > Atmospheric sounding ( meteorological observations ) > Detection techniques and methods
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