Visual Sample Plan (VSP)

Review by Jason Karl
Basic Information
Name: Visual Sample Plan
Acronym: VSP
Author/Owner/Steward: Pacific Northwest National Laboratory
Type: Tool
Platform: Standalone Windows application

Description from Website

VSP is a software tool that supports the development of a defensible sampling plan based on statistical sampling theory and the statistical analysis of sample results to support confident decision making. VSP couples site, building, and sample location visualization capabilities with optimal sampling design and statistical analysis strategies. VSP is currently focused on design and analysis for the following applications:

  • Environmental Characterization and Remediation
  • Environmental Monitoring and Stewardship
  • Response and Recovery of Chemical/Biological/Radiation Terrorist Event
  • Footprint Reduction and Remediation of Unexploded Ordnance (UXO) Sites
  • Sampling of Soils, Buildings, Groundwater, Sediment, Surface Water, Subsurface Layers.

VSP is a tool that helps ensure that the right type, quality, and quantity of data are gathered to support confident decisions and provides statistical evaluations of the data with decision recommendations. Developed with support from DOE, EPA, DoD, the Department of Homeland Security (DHS), the Centers for Disease Control (CDC), and the United Kingdom, VSP has more than 5000 users. VSP has many sampling design and statistical analysis modules focused on soils, sediments, surface water, streams, groundwater, buildings, and unexploded ordnance sites. Many statistical sampling designs are available including random, systematic, sequential, adaptive cluster, collaborative, stratified, transect, multi-increment, combined judgment/probabilistic, and rank set sampling. VSP is being recommended by many regulators for defensible sampling design and statistical analysis.

The underlying methodology employs statistically defensible approaches and has strong Data Quality Objectives (DQO) Process underpinnings. The objective is to ensure that the right type, quality, and quantity of data are gathered to support confident decisions.

It allows real-time evaluation of the tradeoffs between increased confidence in decisions and costs or number of samples required. VSP answers the questions of how many samples are required and where samples should be obtained. Designed for the non-statistician, VSP is organized around the possible data uses. Before developing a data-gathering plan, each user must determine what they will do with the data to support their decision-making process.

Tool Evaluation

This review is based on working through the tutorials that come with VSP and some limited experimenting with other datasets.

Quick Assessment

VSP is a powerful program for designing samples that has a lot of different functions for designing statistically-rigorous sampling schemes. It was originally developed for measuring and monitoring things like environmental pollutants, site contamination, and unexploded ordinance, but it could have uses for rangeland applications – especially for smaller, well defined areas like pastures or even allotments.


  • VSP’s Expert Mentor is a nice feature which guides users through a number of questions to ascertain which of VSP’s many sample selection algorithms are appropriate. The expert mentor covers things like what is the sampling objective, are the data likely to be normally distributed, and what are the precision requirements. This feature can be bypassed, but is a good starting point for this complex software.
  • VSP is a stand-alone application, but has mapping capabilities. Study area boundaries and pre-defined strata can be loaded into VSP and samples selected within these areas
  • By default, VSP includes estimation of the number of samples required to meet sampling objectives. This forces the user to think about variability in the system being measured, precision of their measurements, and their sampling objectives, rather than guessing at the number of samples that should be taken. The cost of each sample can also be factored in.
  • VSP can automatically generate a report for each sample design that lists the assumptions that were made in generating the sampling locations (e.g., data are normally distributed, expected variability in observations)
  • VSP can also do adaptive fill sampling. This is useful if, for instance, there have already been some samples taken from an area, but the existing sampling needs to be supplemented with more observations. Adaptive fill sampling considers a set of existing locations and then selects additional locations.


  • The biggest weakness of VSP for rangeland applications is that is was not designed for ecological assessment and monitoring. As such, much of the language in the VSP program and its documentation is US EPA or military jargon, and there are software options related to regulations governing sampling for contaminants that do not apply to rangeland situations. That said, VSP still has potential to be of value for rangeland assessment and monitoring.
  • The mapping capabilities in VSP are rather limited. The program can import shapefiles, but not other vector formats, GPS data, background images, or other raster datasets.
  • The spatial sampling tools in VSP are limited to point selection, and there is no ability to select area units (i.e., polygons representing ground features like pastures, watersheds, etc.) for sampling.
  • The export of sample locations is rudimentary. Getting sample locations loaded into a GPS unit would require either copying or exporting the coordinates out of VSP, reformatting them using a spreadsheet program or text editor and then uploading them into the GPS unit.
  • VSP cannot handle unequal selection probabilities or sampling with probability proportional to a covariate. This would be useful in cases where some information is known beforehand about the distribution or variability of the feature being measured (or something it’s related to) and would allow for density of samples to vary accordingly.


  • Matzke BD, NL Hassig, JE Wilson, RO Gilbert, BA Pulsipher, LL Nuffer, ST Dowson, J Hathaway, CJ Murray, and LH Sego. 2007. Visual Sample Plan Version 5.0 User’s Guide(PDF). PNNL-16939, Pacific Northwest National Laboratory, Richland, Washington.

Contact Information

Contact Name: Brent Pulsipher
Contact Email:

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