• Skip to main content
itrc_logo

Geospatial Analysis for Optimization at Environmental Sites

Navigating this Website
Overview
Fact Sheets
Fact Sheets Overview
Fact Sheet 1: Do You Need Geospatial Analysis?
Fact Sheet 2: Are Conditions Suitable for Geospatial Analysis?
Fact Sheet 3: How is Geospatial Analysis Applied?
Fact Sheet 4: What Software is Available to Help?
PM's Tool Box
PM's Tool Box Overview
Review Checklist
Choosing Methods
Common Misapplications
Optimization Questions
Geospatial Analysis Support for Optimization Questions in the Project Life Cycle
Data Requirements
General Considerations
Methods for Optimization
Geospatial Methods for Optimization Questions in the Project Life Cycle Stages
Release Detection
Site Characterization
Remediation
Monitoring
Closure
Documenting Results
Fundamental Concepts
Fundamental Concepts for Geospatial Analysis
Basic Data Concepts for Geospatial Analysis
Interpolation Methods and Model Prediction
Uncertainty in Geospatial Analyses
Characteristics of Interpolation Methods
Work Flow
Work Flow for Conducting Geospatial Analysis
Geospatial Analysis Work Flow Overview
Perform Exploratory Data Analysis
Select Geospatial Method
Build Geospatial Model
Evaluate Geospatial Method Accuracy
Generate Geospatial Analysis Results
Using Results
Using Analysis Results for Optimization
Plume Intensity and Extent
Trend Maps
Estimating Quantities
Hot Spot Detection
Sample Spacing
Estimating Concentrations Based on Proxy Data
Background Estimation
Quantifying Uncertainty
Remedial Action Optimization
Monitoring Program Optimization
Examples
Examples Overview
Example 1
Example 2
Example 3
Example 4
Methods
Methods Overview
Simple Geospatial Methods
More Complex Geospatial Methods
Advanced Methods
Index of Methods
Software
Software Overview
Software Comparison Tables
Software Descriptions
Workshops and Short Courses
Case Studies
Case Studies Overview
Superfund Site Monitoring Optimization (MAROS)
PAH Contamination in Sediments—Uncertainty Analysis (Isatis)
Optimization of Long-Term Monitoring at Former Nebraska Ordnance Plant (GTS; Summit Envirosolutions)
Optimization of Lead-Contaminated Soil Remediation at a Former Lead Smelter (EVS/MVS)
Extent of Radiological Contamination in Soil at Four Sites near the Fukushima Daiichi Power Plant, Japan (ArcGIS)
Optimization of Groundwater Monitoring at a Research Facility in New Jersey (GWSDAT)
Optimization of Sediment Sampling at a Tidally Influenced Site (ArcGIS)
Stringfellow Superfund Site Monitoring Optimization (MAROS)
Lead Contamination in Soil (ArcGIS)
Stakeholder Perspectives
Additional Information
Project Life Cycle Stages
History of Remedial Process Optimization
Additional Resources
Acronyms
Glossary
Index of Methods
Acknowledgments
Team Contacts
Document Feedback

 

Geospatial Analysis for Optimization at Environmental Sites
HOME

Sample Spacing

Geospatial analysis can be used to guide the selection of sample spacing or sampling plan design. The first step is to conduct an evaluation of the spatial correlation of existing data using one of the following EDA methods: (1) plot the empirical variogram, covariance function, or correlation function; or (2) plot the h-scatterplot. Consider whether the spatial trend should be subtracted from the data before constructing the plot. From the plot, determine the approximate correlation range of the data, which is the maximum distance over which the data are correlated. Ideally, a sampling plan defines a sample spacing less than the correlation distance between measured values of the quantity of interest. As a conservative rule of thumb, the sample spacing should be half the range of spatial correlation identified with EDA.

Understanding the Results: ▼Read more

The spatial distance or temporal frequency over which a property exhibits autocorrelation is not always straightforward or generic at project sites. Thus, sampling designs can sometimes over- or under-sample the area of interest. The sampling interval can be best determined using preliminary data sets (if available) and other site-specific information (for example, soil maps, geologic maps, or digital elevation models). The sampling interval in geospatial analyses can help in determining a defensibly adequate number of samples for a sampling program and can be determined using variography.

The sampling design should reflect the natural heterogeneity of the data and how the data are related to precision and representativeness of the locations being sampled. The environments that are sampled can be highly heterogeneous in time or space. Therefore, one discrete sample may not represent a particular location or point in time. This heterogeneity can also make it difficult to characterize the variation of a property or process between sampling locations (autocorrelation) or within a single sampling location (for example, laboratory precision). This difficulty can be addressed by using composite sampling, as described in EPA QA/G-5S (USEPA 2002a), or by calculating the average of multiple samples representative of a single sampling location. If economically feasible, the latter better quantifies the precision of the sampling support to determine whether the it is adequate.

Because the potential extent of contamination is rarely known at the outset of an environmental project, the sampling extent is often determined by the sampling program results and is not necessarily evident at the start of sampling. Therefore, a sampling program might propose a sampling extent based on a CSM or other site specific information and optimize this extent upon further data generation and evaluation.

Several geostatistical methods (for example, variograms) guidance documents and free software packages (for example, VSP) are available to help estimate the spatial distribution and number of samples needed to build a defensible and representative sampling program. Be aware that software packages and guidance documents that do not take into account autocorrelation often incorrectly estimate the number of samples needed.

image_pdfPrint this page/section



GRO

web document
glossaryGRO Glossary
referencesGRO References
acronymsGRO Acronyms
ITRC
Contact Us
About ITRC
Visit ITRC
social media iconsClick here to visit ITRC on FacebookClick here to visit ITRC on TwitterClick here to visit ITRC on LinkedInITRC on Social Media
about_itrc
Permission is granted to refer to or quote from this publication with the customary acknowledgment of the source (see suggested citation and disclaimer). This web site is owned by ITRC • 1250 H Street, NW • Suite 850 • Washington, DC 20005 • (202) 266-4933 • Email: [email protected] • Terms of Service, Privacy Policy, and Usage Policy ITRC is sponsored by the Environmental Council of the States.