Lidar Data Applications for Natural Resource Management Tom Bobbe, Mark Finco, Ken Brewer, Denise Laes USDA Forest Service Remote Sensing Applications Center Salt Lake City, Utah Geospatial 2007 Conference Thursday - May 10, 2007

Presentation Outline Lidar system fundamentals Resource management applications Digital Terrain Models Vegetation Models Lidar applications in the Forest Service Lidar acquisition specifications

Fundamentals of Lidar Lidar Basics: Lidar = Light Detection And Ranging Scanning Infrared Laser Rangefinder 80-150 thousand pulses per second result in typical point densities between 8 per 1-m2 to 1 per 4-m2 (called post spacing) Multiple returns from a single pulse are possible Coupled with IMU/GPS provides very accurate X,Y,Z point clouds (~15-cm in Z). In the most general sense, the fundamental principals of lidar are very simple … and as the 1st speaker they should be presented very briefly … Lidar is an acronym … Lidar provides measurements from which images can be derived … not images themselves At a lidar system’s heart is a laser rangefinder and a survey grade gps … add a scanning system and lidar systems can acquire 100,000 or more height measurements every second Most modern systems can collect multiple (often 4) height measurements from each pulse of the laser – point out example in figure of 2 returns These height measurements are actually distance from laser measurements … coupled with GPS/IMU they create what we call DIGITAL TERRAIN MODELS (to differentiate them from digital elevation models)

Characteristics of Lidar Data Point data, but … Large volume of data Assume: 1 to 4 pulses / m2 Assume: 2 returns per pulse Assume: 6 values per return Equals: 0.38 – 1.52 GB per acre, or 3.71 – 14.84 TB per 10,000 acres Because of data volume Often standard GIS analyses don’t work Require special pre-processing for analysis Point data, but this is complicated by the volume of data that needs to be analyzed Large volume of data Assume: 1 to 4 pulses / m2 Assume: 2 returns per pulse Assume: 6 attributes per return … e.g., x, y, z, I, angle, return # Equals: 0.38 – 1.52 GB per acre, or 3.71 – 14.84 TB per 10,000 acres Because of data volume … Often standard GIS analyses don’t work … or work so slowly that they aren’t practical Many times tempted to move away from the vector format and quickly turn into a raster, but this amounts to throwing information away Require special pre-processing for analysis. This includes tiling the data into smaller, more manageable, chunks How big is your study area? Consider these characteristics before diving in … The image is of a study area in western Montana (Lubrecht Expt’l Forest) – 77k acres, 2km tiles for analyzability

Examples of Lidar Point Clouds This lidar point cloud transect crosses a forest road Points Colored by Height Highest Lowest These are simply examples of what lidar point clouds look like colored by elevation. The top image – lidar can be used as a profiler to investigate road cuts and gradients. Note that individual trees are visible within the point cloud. The bottom image – Lidar data, however, is collected using either a fixed wing aircraft or helicopter. The resulting dataset can be viewed as a 3-d point cloud. Note in this forested image that there are some man-made structures which are visible under the canopy. In this 3-D perspective of a lidar point cloud note the buildings

Multiple return lidar All Returns 3rd Return 4th Return 2nd Return 1st Return Multiple return lidar contributes to forest structure measurements 1st return is not just top of canopy Last (4th) return is not just the ground First analytical step typically filters ground returns from all returns Figures Courtesy of PNW Seattle Laboratory

Primary Application – High Resolution DTM The first application for lidar data was the creation of high resolution Digital Terrain Models Note: we use the acronym DTM not DEM because DEM is a data format and is usually assumed to be a USGS product. DTM is a more generic term. The largest federal user is FEMA for flood plain mapping This slide visually demonstrates how the 3-d point cloud can be used to generate high resolution Digital Terrain Models (DTM). The lidar points above the ground are typically discarded … vegetative overburden The magic of lidar data analysis is the separation of ground returns from above ground returns Click and the point cloud transitions to a shaded relief map Note: it becomes obvious that this area is a road intersection. The main road also has a 2-track path or frontage road merging with it.

10-m DEM / 1-m Lidar DTM Comparison USGS 10-meter Digital Elevation Model (DEM) Lidar-derived 1-m Digital Terrain Model (DTM) Site A Site A Site B Site B This is a comparison of a 10-m USGS DEM and the 1-m Lidar-derived DTM Differences are obvious. Micro-topography in the lower left hand side of the image is interesting. Two sites – A and B – are going to be compared at larger scale in the next slide. These high resolution DTMs seem to answer a lot of questions … but they also raise a few more For example, if you have a 1-m DTM and there is a 36” stump on the ground … should it be included in the DTM as part of the “terrain”? (do we have a choice?) New and important features are recognizable on the 1-meter digital terrain model (micro-hydrologic patterns, roads / trails, and other man-made features)

Comparison Areas USGS 10-meter Digital Elevation Model (DEM) Lidar-derived 1-m Digital Terrain Model (DTM) Site A The comparison of site A shows that an earthen dam is easily discernable in the 1-m lidar DTM, but wholly un-recognizable in the 10-m DEM. Also note the road system leading to and away from the dam. The site B comparison simply shows the micro relief in the 1-m DTM Though interesting visual comparisons, these sites and other comparisons have practical implications for engineering applications. Consider, for example the improved cut-and-fill estimates and run-off/erosion calculations that could be created with 1-m DTMs. Site B

DTM’s are just the beginning however … Tools are being developed in the Forest Service and commercial sector to extract information about the vegetation Individual Tree Measurements (potentially height, crown base height, crown diameter depending on crown spacing) Canopy Height, Cover, Density Vegetation Structural Characteristics In addition to the bare earth DTM’s, the lidar data contains a wealth of information about the vertical distribution of vegetation (structure) on the landscape. While these applications are relatively new (<5 years for areas of any size) they are rapidly being facilitated by new software being developed within the Forest Service and commercially Some of the leaders in resource application development are right here in the USFS PNW Seattle Lab – McGaughy and Reutebuch … application called FUSION for lidar data visualization and analysis FUSION is distributed and supported by RSAC … (say more?) RMRS researchers in Moscow, Idaho (and Others) are developing resource analysis methods and other applications …

Fusion Software Developed by USDA Forest Service Pacific Northwest (PNW) Research Station (McCaughey, Reutebuch & Andersen) Originally intended for PNW internal use RSAC agreed to distribute and provide support for FS users Capabilities include: View lidar data quickly and easily Handles almost any format of lidar data Creates surfaces (bare earth models (DTMs), canopy surface models) QA/QC of vendor-processed data Easily measures heights of features Large number of forestry-related measurements And much more… * One lidar analysis tool, FUSION, which was developed at USFS PNW in Seattle allows for (among many other things) the measurement of individual trees.

Fusion Tutorial

Lidar Tutorial

Vegetation information starts with DTMs Raw lidar returns (Colored by height) DTM All returns normalized by the DTM DTM extraction is a necessary 1st step in most vegetation analyses … The image shows the progression from raw lidar points (top), to bare earth DTM (middle), to lidar points that are normalized based on the DTM … this changes the color scheme and you can see tall trees in the front and right of the image that were not visualizeable without the normalization.

USFS PNW’s FUSION Software Individual Tree Measurements FUSION facilitates many types of measurements … One set of tools are provided to individual trees … Other tools allow for the summarization of the lidar returns over larger areas

Lidar and ground measurements relationships Strong relationships with ground measured variables Height, Basal Area, Volume, Crown Bulk Density, etc. Relationships verified by numerous researchers McGaughy, Reutebuch & Andersen (USFS PNW) Hudak and Evans (USFS RMRS) Lefsky (Colorado State) Evans (Mississippi State) Wynne (Virginia Tech) Popescu (Texas A&M) Naesset (Norway) Many others … Dominant height (r 2 = 0.98) Relationships between lidar data and ground-based forestry measurements are very strong … Modeled height, BA, Volume, CBD and other structural variables are strongest Some work (primarily at PNW) has been done to use the intensity attribute provide additional information (e.g., sub-lifeform) These relationships have been confirmed by many researchers ... The next challenge is to use these relationships to meet an operational mapping objective Figures Courtesy of PNW Seattle Laboratory

Lidar Applications in the USFS Recent tally of lidar applications in the USFS (Lachowski and Reutebuch) A recent study by RSAC and PNW reports on the known lidar applications / studies in the USFS More detail and full report at http://fsweb.rsac.fs.fed.us/documents/0073-RPT2.pdf

Lidar Mission Specifications Wide lidar usage (in resource mapping) is just in its infancy Like aerial photos – specifications are linked to information requirements Currently no industry standards for specific applications 2 Areas to specify Acquisition specs Processing and Delivery specs Government Vendor Specs QA / QC Setting specifications for lidar data acquisitions are not available as “boilerplate” for contracting … 1st step is to clearly understand and articulate (better yet write) Experiences of research and pilot projects – and other agencies – can be used as guidance

Lidar Specifications – Acquisition Acquisition Specifications Point density (post spacing) DTM -> based on vertical accuracy requirements Vegetation Applications 1.5 point per square meter absolute minimum 4-6 points per square meter are preferable Specify whether collected leaf on or leaf off Multiple returns per pulse Maximum 15-degree off nadir scan angle unfiltered data Flight lines should have 50% “side lap” (30% minimum) Cross flights for calibration Attributes delivered: X, Y, Z, Intensity, Scan Angle, Return # High resolution digital imagery (if possible) Acquisition Specifications 1.5 point per square meter absolute minimum; 2-4 points per square meter are preferable (note: ask the vendor specify nominal point density, not "contour intervals") Multiple returns per pulse (typically a maximum of 4; you want more than just first and last return lidar) – required if you need vegetation structure information (more than just top of canopy) you may want to specify whether the lidar is collected leaf on or leaf off, depending on mission objectives … often leaf off in hardwood systems Sidelap allows a more detailed analysis of the sub-top of canopy structure because you can look into the trees maximum of 15-degree off nadir scan angle unfiltered data (i.e., unfiltered for ground returns) should be delivered in LAS format one or more cross flights for calibration vertical and horizontal accuracy specification should be provided by vendor (typically ~15-cm vertical, 30-cm horizontal w/95% CI) attributes in LAS file should be X, Y, Z, Intensity, Scan Angle, Return Number, and [Optional: GPS Time]

Lidar Specifications – Processing and Delivery Vendor Processing and Delivery Specifications Lidar data delivered in overlapping tiles GIS dataset of the tiling system GIS dataset of the flight lines Report on GPS ground station locations Geographic projection information (including vertical datum) Heights should be orthometric heights Report that lists all files delivered Optional: Tiled points filtered for bare earth returns A high resolution DTM Vendor Processing and Delivery Specifications lidar data should be tiled into practical units, often 2-km x 2-km; a GIS dataset of the tiling system should be included lidar data should be delivered with a GIS dataset of the flight lines used to collect the data, typical overlap is about 30% a report on what GPS ground station locations were used to reference the data all geographic projection information should be included; heights should be orthometric heights a list of all files delivered to verify contract performance and full delivery you may want to specify whether the lidar is collected leaf on or leaf off, depending on mission objectives [Optional: Tiled points that have been filtered for bare earth returns] [Optional: A high resolution digital terrain model (1-m or 2-m resolution)] [Optional: High resolution photography (or digital equivalent) is a very valuable addition to the lidar data and can often be acquired at the same time]

Approximate Costs of Acquisition Mobilization $8k – $15k Administration Project and flight planning Weather contingency Pre-collection tasks Basic Data Collection and Post-processing Depends on study area size ($0.50 -$2.50/acre for 1M – 15k acres) ~$1/acre for a 250K acre project Raw lidar data Bare earth First surface These figures are presented very hesitantly … it is a dynamic market One downside of lidar data is it’s relatively high cost. This too is changing, however. Costs are a function of how much area is to be collected … and more so on the derived products you want the vendor to provide. Note that the third level of processing (above, Generating GIS Data Sets) is only available from a very limited number of vendors and are by no means standard products. Lidar data consortiums are being created to collect lidar data over entire states –Carolinas, Wyoming, Nevada?, Washington? The image shows the progression from raw lidar points (top), to bare earth DTM (middle), to lidar points that are normalized based on the DTM … this changes the color scheme and you can see tall trees in the front and right of the image that were not visualizeable without the normalization. Advanced Processing Additional $3 – $7/acre Canopy cover Tree height Forest biomass Other vegetation derivatives

Summary Lidar is an exciting (relatively) new technology Provides measurements! Vegetation structural information are its strengths Existing research provides a strong foundation Lidar processing requires special skills/tools Data volume can be an issue Specialized software (not just ESRI products) required for efficient large scale analysis Lidar missions Specifications becoming better understood Still expensive, but costs coming down Multiple resource applications & consortia allow for cost sharing