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Spatial Variability Mapping of pH in Oregon Organic Farms using Geographic Information Systems (GIS) Geospatial Interpolation Models

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  • This internship project (Dr. Dawn Wright—Department of Geoscience) was a synthesis of several aspects of the research process. The documentation of methods consisted of: primary data collection of soil samples, geographical coordinates, georeferencing, basemap creation, laboratory machine operation, laboratory methods, laboratory quality control planning, statistical analysis, and geo-statistical analysis using geospatial interpolation tools. Quantitative information must derive from measurement, and we cannot measure the soil everywhere; we can at best measure the soil with planned samples. So accurate information for any region is available only at isolated points or for small bodies of soil. Whatever we state for intermediate positions or larger blocks of land involves some kind of interpolation or estimation from the measurements. That in turn carries with it uncertainty, and so we want some measure of that uncertainty too. This research focus is more of a tutorial on how to think about measurement, interpolation, variability of pH and nutrients in soil while using this data in a GIS.
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file details Soils_Geostatpaper.pdf 2017-07-21 公开 下载