1. Differential Leveling Conversion and Analysis Toolset Lisa Berry University of Redlands, MS GIS Program

2. Project Overview Masters of Science in GIS Partnered with: Image: www.dot.ca.gov

3. Problem Inability to spatially and temporally pinpoint height changes over time along transportation infrastructure in southern California Images: www.examiner.com and www.flickr.com

4. How to Measure this Change Elevation changes along the transportation infrastructure using differential leveling survey methods Image: http://www.theeagle.com

5. Differential Leveling Survey Methods Differences in height rather than actual elevation - Helps determine geodetic elevation Image from: www.facebook.com

6. What is Differential Leveling? Measured between Benchmarks Difference in height between these benchmarks Images from: gallery.usgs.govImages from: gallery.usgs.gov, onlinemanuals.txdot.gov onlinemanuals.txdot.gov Differential Leveling Observation Run

7. Benchmark and Run Visualization Runs store differential height value Benchmarks (Points) Runs (Lines)

8. Spatial and Temporal Problem Finding regions of significant change

9. Blue Book Format National Geodetic Survey (NGS) Vertical Observation text files - Collects and validates geodetic leveling data

10. Blue Book Format 1 Survey per file - Line records store raw observations

11. Goals of Project Build a geodatabase to manage datasets for efficient analysis Tool to automate conversion into ArcGIS Tool to perform analysis between surveys Image: esri.com

12. What Needs to be in the Geodatabase? Types of survey information within file: Basic information about survey Latitude/Longitude of Benchmarks Differential height between benchmarks Date/Time of measurements Temperatures and instrument specifications

13. Methods ArcGIS 10.1 - Geodatabase schema Python and ArcPy methods - Conversion and analysis

14. Conversion Process Step 1: Creation of Geodatabase Schema

15. Conversion Process Step 2: Python Script Tool - Handling different line records

16. Python Script Line Record “key”

17. Conversion Process Step 3: Field type conversion within Python - Integer and date fields to match geodatabase schema +=

18. Writing to the Geodatabase Insert Cursor method Sparse/Convert Line Data Python List Insert Row to Table

19. Conversion Tool Interface Batch process surveys Pre-made Geodatabase schema (location)

20. Conversion Output

21. Pilot Dataset Results 9 Surveys 2700 Benchmarks and 4200 Runs Filling 2 Feature Classes and 2 additional tables 15 seconds

22. Analysis Tool Searches Feature Class for: - Same start and end benchmark - Significant difference in the differential leveling value Search Cursor Method - Comparing the table to itself

23. Analysis Tool Interface

24. Analysis Tool Result Join with Runs Feature Class - Spatial visualization of the runs with significant change

25. Overall Solution BeforeAfter

26. The Big Picture Image: aaroads.cahighways.org and www.noaa.govaaroads.cahighways.org

27. Conclusions Creation of geodatabase Automating the conversion process Creating a tool for analysis Allowing further analysis of datasets Runs Benchmarks Equipment Differences

28. Thank you Lisa Berry lisa_berry@spatial.redlands.edu