PAMAP is the base map of the Commonwealth of Pennsylvania and primarily consists of color orthophotography and LiDAR elevation data. The seamless, consistent, high-resolution set of digital geospatial data provides vital components of the state’s spatial data infrastructure for use by citizens, state and federal agencies, county and municipal government, institutions, business entities and community organizations. The initiative was launched in 2001 and is managed as a partnership between the Pennsylvania Department of Conservation and Natural Resources (DCNR) and the Office of Administration – Office for Information Technology (OIT). On behalf of the Commonwealth, The Pennsylvania State University oversees PAMAP production and coordinates long-term program design and implementation.
An equal distribution of checkpoints across the data collection area was a key project requirement. For the orthophotography checkpoints, the HRG team selected photo-identifiable ground features in the office prior to the survey. Using the PAMAP orthophotography in Esri ArcMap software, survey technicians “heads up” digitized each checkpoint over existing surface features visible on the imagery before field visits. These points were then imported into Panasonic Toughbooks with Delorme Street Atlas software so that they could be easily navigated to while in the field. The use of this GPS navigation software was essential as field personnel moved through unfamiliar terrain and greatly increased efficiency.
The LiDAR points proved more challenging since they essentially had to be chosen “on the fly” in the field. The HRG team had to select points that fit the criteria for the five land cover classes and were also distributed well spatially while also meeting criteria set by Dewberry.
The criteria were based on the 1998 National Standard for Spatial Data Accuracy (NSSDA) and specified that horizontal accuracy would be tested by comparing the planimetric coordinates of well-defined points in the dataset with coordinates of the same points from an independent source of higher accuracy. Vertical accuracy would be tested by comparing the elevations in the dataset with elevations of the same points as determined from an independent source of higher accuracy. Since the NSSDA was developed before widespread use of LiDAR, the project team also relied on supplemental guidelines issued by the American Society for Photogrammetry and Remote Sensing (ASPRS), the National Digital Elevation Program (NDEP) and FEMA for vertical accuracy testing of LiDAR data. These guidelines recommend surveying 100 vertical checkpoints for each LiDAR collection block, which equated to 20 checkpoints each for the five land cover types specified in the project (bare ground, high grass, brush, woods and urban).
Time constraints and a high volume of checkpoints over an expansive, statewide project area ruled out the use of static GPS due to the lengthy observation times required. The other drawback to this method was that there was no way to verify the quality of the data being collected until it was downloaded and processed in the office. This was of particular concern in relation to the checkpoints in the “woods” land cover class. To survey these points, an inter-visible pair of control points had to be set and observed with GPS. The control points were then occupied with an electronic total station, and the checkpoint was measured under tree cover where GPS is ineffective.
RTK GPS was impractical due to the large geographic area of the project; most broadcast radio signals are limited to a range of two to five miles. Rapidly and cost-effectively collecting a high volume of checkpoints over an expansive area that had highly accurate horizontal and vertical positions required a different approach.
Cellular modems were being successfully employed by other industries to provide real-time data for communication and remote monitoring. The sending and receiving of data with this method was not limited by distance and was possible anywhere wireless data service could be obtained. The use of this technology for GPS surveying at the beginning of the project was in its infancy. Still, the HRG team believed that applying this technology to the RTK survey method could provide substantial improvements in efficiency while achieving the required accuracy.
HRG personnel determined that Airlink cellular modems via a nine-pin serial port could be readily interfaced with the Trimble R8 and 5800 GPS receivers used for field surveys. Once the modems were configured properly, real-time data could be transmitted by one modem at the base receiver to its “mate” connected to a rover receiver realizing a modem “pair.” After establishing the connection through a wireless network, a high-quality “fixed” RTK solution was achieved, which gave the field surveyors real-time positions on any given checkpoint or survey control point used to conventionally locate LiDAR checkpoints in the “wooded” land cover classification.
The next challenge was to find a way to obtain redundant observations on each of the PAMAP checkpoints to ensure the quality of the survey data. Two accepted methods to achieve this redundancy are to observe each point twice at different times and/or from different base locations. However, the large project area and the distances traveled made observing the checkpoints at different times impractical. Instead, the team developed a method for observing each point from two base locations in a single visit. The two field members working on the collection each carried two Airlink modems along with their GPS rover. Two Trimble R8 base stations were then set up at different locations with a single Airlink modem, and each of the base modems was configured to transmit to both of the field members simultaneously. This enabled each of them to observe each checkpoint twice, without having to revisit the point.
The combination of cellular modems and the creative approach to redundancy greatly increased the efficiency of the workflow and accuracy of the final dataset while allowing the crews to set survey control pairs “on the fly” for observing wooded LiDAR checkpoints.
HRG completed its portion of the project on time and on budget in 2010, establishing nearly 1,400 3D QA/QC checkpoints for Dewberry’s contract to perform independent QA/QC of statewide digital orthophotos and LiDAR for the PAMAP Program. “The HRG surveyors deployed to every county in Pennsylvania and provided QA/QC checkpoints that were always accurate and well documented the first time, never having to return to the field for re-surveys,” says Dewberry’s Project Manager David F. Maune, PhD, PS, GS, PSM, CP, CFM. “I credit this to HRG’s innovative use of technology and their excellent technical and project management.”
For the HRG surveyors, this project was another chance to demonstrate the value of the profession. We’re proud of our role in the accuracy assessment of this data and the value and usability that it provides to both the public and private sectors.