This document discusses how geographic information systems (GIS) can be used to support site remediation projects (SRP). It describes a three step iterative process for GIS analysis: 1) data assembly, 2) data analysis, and 3) data presentation. For data assembly, GIS is used to organize disparate data sources by relating data to geographic coordinates. For data analysis, GIS enables simple observations and modeling to build an understanding of site conditions. For data presentation, GIS creates maps, graphs and other visualizations to communicate spatial relationships and trends in the data. The document provides examples of how GIS can be applied throughout the different phases of an SRP.

1. GIS ANALYSIS AND WORK-
PRODUCTS SUPPORTING SRP
The Application of Geographic Information Systems (GIS) to
the Site Remediation Program – An Introduction
Joe Luchette:
jluchette@geosyntec.com

2. Using GIS in SRP Projects
• From Preliminary Assessment or Phase I to
• Site Investigation,
• Conceptual Site Modeling (CSM),
• Remedial Investigations,
• Remedial Designs,
• Remedial Actions…

3. • A task-driven, iterative process:
1. Data Assembly
2. Data Analysis
3. Data Presentation
Using GIS in SRP Projects

4. • A task-driven, iterative process:
1. Data Assembly
2. Data Analysis
3. Data Presentation
Analytical data and disparate
base map data sources
Simple data observations,
statistics, graphs, contouring,
modeling, mass estimation,
etc.
Using GIS in SRP Projects

5. Data Assembly
• Everything that has position (and in some cases, dimension) is
related by coordinates in one or more coordinate systems
Air Photo
Base Map
Utilities
Wells
Geology
Hydrology
Easting
• Any Sample (bottle of stuff) is associated
with a LOCATION that has Coordinates in a
related table
• Locations, spatial features and
georeferenced imagery are related using
Geographical Information Systems (GIS)
• GIS is a specialized form of the RDBMS in
which all records have spatial information
1. Data Assembly
2. Data Analysis
3. Data Presentation

6. Data Assembly: Organization
• A GeoDatabase can help organize site
data.
• Maintain consistent location for all
data.
1. Base_Layers: Background and
regional data layers.
2. Contours
3. Project_Data: GPS, survey,
digitized data, scanned data. Site
features, sample locations, etc.

7. Data Assembly: Preliminary Assessment
• GIS can assist in the early stages
– Ownership information (tax parcels)
– Aerial Imagery
• NJDEP
• www.HistoricAerials.com
• EDR
• USG
– Nearby sites
– Historic Fill
– Wetlands
– Site plans (if available)

8. • Conversion is not necessarily transitive:
cannot always reproduce the original CAD
data after converting to GIS due to inherent
differences in CAD/GIS data models
• Tips for requesting DWGs:
– Use model space
– Explode blocks,
– Don’t use mtext,
– Don’t use hatching,
– Organize layers well
Data Assembly: Working with AutoCAD Drawings
Traditionally Doesn’t interface well with GIS.

9. Data Assembly: Working with AutoCAD Drawings
• Bi-directional conversions between CAD
and GIS data
– Use ArcToolbox to convert CAD to GIS
& GIS to CAD
• ArcToolbox > Conversion Tools>To
Geodatabase > Import from CAD
• ArcToolbox > Conversion Tools>To
CAD>Export to CAD

10. Data Assembly: GeoReferencing
• GeoReferencing
– Digitizing
– Raster to Vector Conversion (ArcScan)
Vectorization of contours
using ArcScan
GeoReferencing a drawing
onto an aerial

11. Data Assembly: GPS
• GPS sampling locations
– Trimble and Pathfinder Office
• Ad-Hoc methods
– Smartphone Apps

12. Data Analysis
• Simple observation/overlays
• Statistics
• Modeling
• Building and continually refining your Conceptual Site Model (CSM):
1. Data Assembly
2. Data Analysis
3. Data Presentation
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13. Data Analysis: Overlay
• Data Observation:
– Historic imagery overlays
– Topographic overlays
– Site plan overlays- historic use

14. Data Analysis: Data Modeling
• Interpolation/extrapolation,
– What concentrations are expected in between or beyond existing data?
• Groundwater elevations
• Isoconcentration (analytical data)
• Geology
TCE isoconcentration contours
with color fill
Interpolation of hydraulic gradient
from groundwater elevations

15. Data Analysis: Data Modeling
• Predictive modeling
– GW modeling, particle tracking, etc.
Extraction well capture modeling
at various pumping rates

16. Data Analysis: Virtual Remediation
• Compliance Averaging using Spatially Weighted Average
(area weighted mean)

17. Data Analysis: Virtual Remediation
• Compliance Averaging using Spatially Weighted Average
(area weighted mean)
– Step 1: Create Thiessen/Voronoi polygons from points dataset.
– Step 2: Add a field & calculate area for polygons
– Step 3: Add a field & calculate percent area ((area of each polygon ÷
total functional area)*100)
– Step 4: Add a field & calculate weighted result for a compound
– Step 5: Get statistics on the final field and get mean
• If this is less than the applicable standard, you are done!
• If this is still above the standard, take out the polygon with the
highest result, and start over at step 2.
– Iterate until complete.

18. Data Presentation
• You are telling a story through narratives, tables, charts, maps and
other visualizations
• Maps are fundamental to environmental data to communicate spatial
component
• Yes, every picture tells a story (in fact, most pictures tell several
stories), but the key is finding THE picture…
1. Data Assembly
2. Data Analysis
3. Data Presentation
“There’s no such thing as an objective map”
--Michael Goodchild

19. Data Presentation: Thematic Mapping
• Graduated color and graduated symbol sizes
Graduated symbols showing
magnitude of Total VOC
concentrations in a treatment area.
Graduated color map, with class
break at regulatory limit

20. Data Presentation: Thematic Mapping
• Pie Charts and Graph maps
Time-series concentration data
suggest transport of vinyl chloride is
to the west, off-site.
Pie charts showing compound ratios
in Total VOC summations.

21. Data Presentation: Data Posting
• Advanced Labeling (aka “Spider Maps” or “Data Box Maps”)
– Show multiple samples (depth, dates)
– Highlight results above standards
– Use in combination with symbology

22. Data Presentation: Leaving Plan View
• GIS provides a quick start to your Cross Sections
– Use the X or Y coordinate as the X axis, and use the elevation or depth
measurements and use at as the Y axis to start constructing your
scaled graphic.
– Add your labels
– Draw in your contacts

23. Data Presentation: Leaving Plan View
• Psuedo 3-D
– Showing Depth using planar maps
Juxtaposition Stacking

24. Data Presentation: 3-D Visualization
• ArcGIS extensions: 3D Analyst + Spatial Analyst
– Plot boreholes, well screens, block geology (planar interpolations and
extrusions)
• EVS/MVS, Rockworks or GMS
– Plume Mapping - Volumetric Kriging (real 3d) + Geology
– Slices and Fence Diagrams
• EnterVol – ArcGIS Extension

25. Data Presentation: The Fourth Dimension
• Temporal Data Visualization using Animation
– Stream Flow animation with corresponding graph: Link
Modeling Nutrient Delivery in a
Bioremediation Curtain
Population Growth
www.egr.msu.edu

26. Helpful Links
• State of NJ – Tax List Search: http://njgin.state.nj.us/oit/gis/NJ_TaxListSearch
• NJDEP Compliance Averaging Guidance:
www.nj.gov/dep/srp/guidance/srra/attainment_compliance.pdf
• Golden Software - Surfer: http://www.goldensoftware.com/products/surfer
• ArcGIS – 3D Analyst Extension:
http://www.esri.com/software/arcgis/extensions/3danalyst
• ArcGIS – Spatial Analyst Extension:
http://www.esri.com/software/arcgis/extensions/spatialanalyst
• Ctech – EVS/MVS Suite: http://www.ctech.com/mvsevs-product-suite-new/
• EnterVol – EVS ArcGIS extension: http://entervol.com/
• Visualizing Temporal data in ArcGIS:
http://resources.arcgis.com/en/help/main/10.1/index.html#/About_visualizing_t
emporal_data/005z0000000n000000/

27. QUESTION AND ANSWER
GIS analysis and work-products supporting SRP