PAMAP Lidar Elevation Data

Merriam-Webster defines lidar as a device that emits pulses of laser light. Such a device can be used to detect, identify, and locate objects—making it a lidar sensor. The word “lidar” is an acronym for Light Detection and Ranging. You may also see the word “lidar” as “LiDAR” or “LIDAR,” although the all-caps version is not common.

From 2006 through 2008, the PAMAP Program used lidar to collect 3-D measurements of Pennsylvania’s surface. Data collection was done for a group of counties each year. Airborne lidar sensors fired laser beams to the ground at a rate of hundreds of thousands of pulses per second. Whenever a pulse hit an object (e.g., a building, a tree, or a rock), some of the light would be reflected back to the plane. In most areas, multiple returns were recorded for each pulse of light, and the intensity of the reflected energy was noted. By knowing the absolute position and orientation of the sensor (a feat that involves a global-positioning-system receiver and an inertial measurement unit), and considering such factors as the angle, speed, and travel time of the light pulse, elevations were calculated for each point of impact.

Pennsylvania partnered with the U.S. Geological Survey (USGS) to become one of the first states in the nation to collect lidar elevation data for the entire state. There are four lidar-derived data products that came out of the PAMAP Program:

Point Clouds          Digital Elevation Models          Breaklines       Contours

You can select and download PAMAP lidar-derived products free of charge through the PAMAP Data Download Portal. The data are stored on servers maintained by Pennsylvania Spatial Data Access (PASDA) and can also be downloaded from the PASDA website ( Data units are in feet, and all data use the NAD83 horizontal datum, GRS80 ellipsoid, NAVD88 vertical datum, and GEOID03 National Geodetic Survey.

The lidar-derived data products were clipped to the PAMAP tiles and are organized into datasets by collection year. The resulting digital data files have names that start with a concatenation of the first four digits of the State Plane northing and easting that defines the northwest corner of the tile covered by the data. This number is followed by the state identifier “PA” and the State Plane zone “N” or “S.” The counties flown each year and the associated State Plane zones are illustrated on the map below. There is about one tile of overlap between the two zones.


PAMAP Lidar Years


The lidar data were primarily acquired to produce a digital, high-resolution, bare-earth model of Pennsylvania. This new base map updates and is more accurate than the USGS 1:24,000-scale, paper topographic maps in use at the time. The bare-earth model was to support floodplain mapping and flood-control projects, and as such, the lidar data were collected and processed to generally meet specifications called for at the time by FEMA in Guidelines and Specifications for Flood Hazard Mapping Partners—Appendix A, Guidance for Aerial Mapping & Surveying—Section A.8, Airborne Light Detection and Ranging (LiDAR) Surveys.

More information on PAMAP lidar data can be found on the Documents web page, which includes links to reports on vertical accuracy, data quality, repaired errors, and other relevant topics.

Lidar Point Clouds

Lidar data were collected as three-dimensional points defined with x, y, and z coordinates, and a set of these points forms a point cloud. The points were saved in binary LAS format, and each point is attributed for intensity, classification, and location. The classifications are as follows: Class 1, Default (mixture of points remaining after the ground classification); Class 2, Ground (points on the bare-earth surface); Class 8, Model Key (thinned-out ground points used to generate digital elevation models and contours); Class 9, Water (points inside hydrographic features); Class 12, Non-Ground (points identified as first or intermediate of many returns); and Class 15, Road Edges (points that fall within 1.5 feet of road breaklines).

Point clouds were filtered for noise, anomalies, and sidelap, and were clipped to the aforementioned program tiles. The sizes of the LAS files vary based on terrain, features, and other particulars, but the files generally average 120 MB per tile. 

Data collection was engineered to meet the FEMA standard of 1.4-meter average spacing between points. Quality testing showed that many of the collected points exceed the bare-earth-surface vertical accuracy of 18.5-centimeters RMSE required by the FEMA guidelines. Horizontal accuracy follows the 1998 National Standard for Spatial Data Accuracy of 5 feet RMSE or better for 95 percent of the checked points.

The banner at the top of this web page shows a cross-section view of a PAMAP point cloud through Hershey Park (note the high loops of the roller coasters and the red-pointed top of the kissing tower). The image below shows the LAS file for an area that extends from southernmost Northumberland County into Dauphin County. The high points in the foreground were reflected off of Mahantango Mountain, which is crossed by Pa. Route 225 and Deep Creek at the prominent break. The town of Pillow is located on the north side of the mountain along the same highway.


LAS point Clouds


Digital Elevation Models

The digital elevation models (DEMs) are raster images of Pennsylvania’s bare-earth surface created from representative lidar ground points (model-key classification). Each DEM GeoTIFF file covers one of the 100-million-square-foot grid tiles used in the PAMAP Program and is approximately 38 MB in size. The GeoTIFFs have a 3.2-foot pixel resolution, and each pixel represents an interpolated elevation value. GIS software can be used to create derivative data products from the DEMs, such as hillshade (shaded-relief), slope (steepness), and slope-aspect (slope-direction) images.

The images shown below represent an area of Pittsburgh just southwest of the Monongahela River. The left image is the DEM as it appears when imported into the Esri ArcGIS platform ArcMap. In this image, the light areas are relatively high ground, and the dark areas are relatively low ground. The right image is a hillshade of the same area with labels added. Fine etchings of city streets can be seen throughout the hillshade. Sawmill Run and Pa. Route 51 form the prominent northwest-trending valley. The northerly trending valley just left of center follows U.S. Route 19, and midway up that valley, U.S. Route 30 can be seen looping in from the west. You’ll notice that the valley of U.S. Route 19 terminates just after the highway crosses Pa. Route 51; it’s at this point that the highway enters the Fort Pitt Tunnel. The Pittsburgh neighborhoods labeled on the hillshade include Duquesne Heights (DH), Mt. Washington (MW), Beechview (BE), Banksville (B), Green Tree (GT), and Westwood (W).



Breaklines are 3-D lines that represent breaks in the slope of the land surface, such as occur at the edges of roads, streams, lakes, and bridges. A breakline shapefile was created for each PAMAP tile area. The slope breaks were digitized from PAMAP aerial photography with most of the elevation values coming from PAMAP lidar points. These lines are critical to creating an accurate surface model, as surface triangulation stops at a breakline. PAMAP BreaklinesPAMAP breaklines were primarily used to enhance PAMAP contours and DEMs, aid in the classification of lidar points, and help maintain the position of linear ground features in orthophotographs. Breakline file sizes vary by tile, but almost all are less than 1 MB in size.

In the image to the right, the breaklines prepared for PAMAP tile 41001330PAS (representing an area in the southern part of Pittsburgh) are shown superimposed on the hillshade of that tile. Although PAMAP breaklines are attributed by feature type, they do not rigorously delineate the features they represent and should not be used to support engineering or similar analyses. More information on how the breaklines were compiled can be found in the white paper PAMAP Breakline Information.


Two-foot topographic contours were derived from the PAMAP DEM 100-million-square-foot tiles using MicroStation CAD software. They were exported to a DXF file that was then imported into Esri ArcGIS as a 3-D shapefile. The contours were attributed for elevation values and type, which includes index, index depression, intermediate, and intermediate depression. Every fifth contour (value a multiple of 10) was considered an index contour. All contours were edge matched to contours in adjacent areas. Contour file sizes vary by tile but generally average 40 MB.

The images below compare the 20-foot topographic contours from a tiny part of the USGS Pittsburgh West 7.5-minute quadrangle (top) to the PAMAP 2-foot contours derived for the same area (bottom). The PAMAP contours were created from the DEM of PAMAP tile 41001330PAS, which in turn was based on data collected in 2006. For readability, the image only shows the upper right (northeast) corner of the tile area. The higher level of detail made possible with lidar data is clearly seen in this example. In the PAMAP image, the 10-foot index contours are shown in red and labeled sporadically; the intermediate contours are in brown. Breaklines were added in gray to help orient the viewer, as they indicate the position of the roads shown in the top image. The PAMAP contours are jagged compared to the contours from the printed quadrangle map, a reflection of the data-centric (as opposed to cartographic) origin of the PAMAP contours.

PAMAP Contours captioned

Obtaining the Data

As mentioned above, the official distributor of PAMAP lidar data is PASDA. Tiles of the four lidar-derived products are easily identified and downloaded using the Pennsylvania Geological Survey’s PAMAP Data Download Portal. PAMAP data and related products may also be downloaded from the PASDA website (

The point cloud data in LAS format is also available through the USGS Center for Lidar Information Coordination and Knowledge (CLICK) at

All PAMAP data products are available for bulk and/or offline acquisition from the Pennsylvania State Data Center.