UC Davis Soil Resource Laboratory

The UC Davis Soil Resource Laboratory is a western US center of research into soil science. The researchers at the laboratory are experts in the field, yet even they are occasionally dismayed at the technical complexity involved in accessing regional soil survey data.

Soil data summary view

In order to improve accessibility to the soil survey data, the staff at the laboratory began a program in 2004 to make the data accessible to the public. The raw data is provided by the US Department of Agriculture, in a number of scales. At the 1:24K scale, the soil survey for California, Nevada and Arizona comprise almost over half a million polygons, with a large number of associated attribute tables.

Initially, the researchers settled on a system using UMN Mapserver and MySQL which provided an interactive map interface to the data. MySQL was used to store the attribute tables, and the spatial data was stored separately in Shape files — one for each "survey area". The Mapserver/MySQL system provided basic map access well, but there were a number of drawbacks:

  • The map view of soil data was only available on a per survey area basis and users browsing past survey area boundaries would perceive that the data available ended at the survey boundaries.
  • Managing the data in 120 separate survey areas was inconvenient.
  • With TIGER data added for context, data management became even more complex, as the number of input files grew.
  • Making non-spatial queries and joining the results to spatial information required complicated scripting.

In the spring of 2006, the team decided to migrate all the data into a single instance of PostGIS/PostgreSQL. The ogr2ogr tool was used to load the data into PostGIS, and the Mapserver application was altered to read the spatial data directly out of PostGIS.

Soil data summary view

With the new spatial database architecture, the team capitalized on a number of improvements right away:

  • A single seamless table was used to store information from each of the 120 survey areas, making it possible to view and query all the data simultaneously.
  • The PostGIS "simplify()" function was used to create reduced-precision versions of some of the spatial layers, substantially improving the mapping performance of the application at smaller geographic scales.
  • The TIGER layers were also added as seamless tables, and the "simplify()" function used to create faster mapping layers.

The move to PostGIS has freed the team from working on data management problems and allowed them to work on functionality. "The largest improvements in the last six months are closely tied to the move to PostGIS", says Dylan Beaudette, a developer and researcher at the lab.

Now that their data is consolidated with standard SQL access across all survey areas, new analytical possibilities are available to the researchers. "Using the SQL approach to GIS, we can do multi-survey analysis inside PostGIS that would otherwise be too demanding to carry out with shapefiles and ArcGIS", says Dylan.

The data published by the lab is now being used for outreach to farm advisors and by independent environmental consultants — a valuable resource for scientists throughout the south-west.

For more information:

Dylan Beaudette
UC Davis Soil Resource Laboratory

Published August 2006

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