Lidar and the Oregon Lidar Consortium Beaverton photo

Lidar and the Oregon Lidar Consortium Beaverton: photo and lidar highest hit model Portland State Office Building: photo and lidar point cloud Eagle Creek landslides, abandoned railroad: photo and bare earth model

What is lidar (light detection and ranging)? - Simply making lots of accurate distance measurements with a laser rangefinder. Accurate laser rangefinders are commonly used as surveying instruments, measuring tapes, rifle scopes, even golf aids! Distance is calculated by measuring the time that a laser pulse takes to travel to and from an object.

Millions of very precise laser range measurements are made from a precisely located aircraft, producing an accurate and detailed 3 -D map of the earth’s surface, as a “point cloud. ” Aircraft attitude is precisely measured by Inertial Motion Unit, so that the exact position and orientation of the laser rangefinder is always known. The rangefinder scans across the surface at 100, 000 to 200, 000 pulses per second, collecting millions or billions of precise distance measurements, which are converted to 3 -D coordinates. On-ground RTK-GPS base stations broadcast corrections to airborne GPS unit, locating the aircraft with an accuracy of a few centimeters.

Point cloud data define the 3 -D shape and location of the land, vegetation, and structures. The complete collection of measured points for an area is called the point cloud, which is the fundamental form of lidar data. It provides a very detailed and accurate 3 D map of ground surface, vegetation, and structures. (above) Animated point cloud image of the Portland LDS Temple; points are colored by their relative height: red highest, blue lowest. (right) Photo of the same building; note statue on left hand spire, visible in both images.

Each laser pulse can produce multiple consecutive measurements from reflections off several surfaces in its path. This provides detailed images of vegetation structure and density, and returns data from the ground under tree cover. Image on the left is a point cloud lidar view of the tree in the photo on the right. Each point is colored by which return it was from a particular pulse: • red= 1 st return • yellow = 2 nd return • green = 3 rd return

OLC data are collected at very high pulse density, producing very detailed images. Point cloud image on left compared to orthophoto on right shows actual point density of lidar data acquired over school bus lot. Each bus has been measured by 180 -200 lidar points!

The lidar point cloud can even image livestock in the field! Red and yellow clusters of points above ground are cattle standing or lying in pasture.

Even ifhigh only one point one hundred is aeven ground point, the huge number ofitpoints means The vendor uses variety of software filters choose the points the point For comparison, theainbest previously available ground model isout shown the Verylidar point density means that in to heavily forested areas, ison still that a. The smooth seamless ground model can made. The image on the left is aimage bare earth cloud that measure the ground surface. In be the image onofthe right, points are left. 10 -m USGS Digital Elevation Model shows only a vegetation crude possible to get a large number of measurements the ground. Left is digital elevation model, with 3 ft pixels, and reveals incredible detail of the terrain beneath green and ground points yellow. Even in thick forest there are numerous ground points. representation of the real surface. orthophoto of the Tualatin River, right image is lidar point cloud with the trees, including a hidden landslide. red points high, blue points low.

Bare earth lidar can show features that you cannot even see on the ground. Perspective view of lidar (Dec. 2007) on left matches photograph (July 2008) on right. The lidar was flown before clear cut logging of the reddishbrown slope, yet clearly shows an old logging road that is barely visible in the photograph. Arrows connect matching locations.

Additional standard lidar products include a “highest hit” or “first returns” model, which shows the tops of trees and buildings, and an intensity image, which is a form of infrared photograph. True color orthophoto with 0. 5 ft pixels Lidar highest intensityhit image model with 1 ft 3 pixels ft pixels Transmission lines Nursery stock Residence Quarry Auto

Lidar data allow a wide variety of information about forests to be measured with unprecedented accuracy and completeness. Tallest tree at 252 ft! • Locate and measure individual trees in forest • Estimate fuel loads, carbon content, timber volume • Tell conifer from deciduous • Identify damaged forest Image at right shows a simple analysis, subtracting the bare earth surface model from a first return (highest hit) surface model to produce a canopy height model. Low canopy is violet, high is red. The shapes of individual trees are apparent, and the tallest tree in the forest can be easily found and measured. 150 -250 ft forest 60 -100 ft forest 135 -190 ft forest 100 -125 ft forest Brush and grass 40 -60 ft forest 50 -80 ft forest

Comparing the highest hit or surface and bare earth surface provides a detailed and accurate model of building area and height Building, 9, 000 sq ft, 27 ft high Building, 4, 900 sq ft, 11 ft high Residence, 2, 300 sq ft, 12 ft high Building, 19, 850 sq ft, 89 ft high Building, 16, 750 sq ft, 79 ft high Light standards, 54 ft high Building, 20, 100 sq ft, 155 ft high Parking structure, 79, 400 sq ft, 3 -20 ft high, sloped for drainage Powerline, 56 ft high Highway sign, 27 ft high Overpass, 23 ft high

The highly detailed bare earth model allows for accurate location of roads and provides easy access to unprecedented levels of detail about slopes and shapes Yellow lines are best current digital road map. Roadcut not too steep Drainage ditch on uphill side Properly crowned for drainage The lidar image can show where existing maps are inaccurate or locate roads that are not on existing maps or show where mapped roads do not exist Because the bare earth model contains detailed information about the shape of the land surface, it is easy to construct a profile across a road to examine its construction and condition

Comparing the streams with the digital stream GIS software canlidar-derived automatically find stream channels from lidar data Stream channels are readily apparent oncurrent lidar bare earth map shows that the current data are often wildly inaccurate images Blue lines are streams generated by Arc. GIS Dark blue lines are best current digital stream map, light blue are lidar-derived. Crosses divide, mouth wildly off misses sinuous channel, climbs ridges cross divides

In addition to accurately locating streams, lidar easily produces accurate and detailed profiles and sections Light blue line is lidar derived stream location, dark blue are section lines. A detailed elevation profile down the stream shows areas of steep or gentle grade, waterfalls and pools. Culverts at road crossing Section shows shape of show up as upward blips“v”on the profile. rapidly downcutting stream Stream section shows distinct floodplain and channel

What can you do with lidar? You can quickly, cheaply, and accurately…. • Find landslides, old cuts and grades • Measure and estimate fills and cuts • Find stream channels, measure gradients • Measure the size and height of buildings, bridges • Locate and measure every tree in the forest • Characterize land cover • Model floods, fire behavior • Locate power lines and powerpoles • Find archeological sites • Map wetlands and impervious surfaces • Define watersheds and viewsheds • Model insolation and shading • Map road center and sidelines • Find law enforcement targets • Map landforms and soils • Assess property remotely • Inventory carbon • Monitor quarries, find abandoned mines • Enhance any research that requires a detailed and accurate 2 D or 3 -D map

The Portland Lidar Consortium was the first large scale effort to collect lidar in Oregon. “Hood to Coast” survey In. This 2006, the USGS provided with and In 2003, the USGS funded With the USGS funds to anchor the survey was followed in 2005 by. DOGAMI another $100 k to complete the of Portland. DOGAMI for a pilot lidar. City ensure a large enough area for the lowest USGS-DOGAMI flight in the Portland DOGAMI formed the Portland Lidar survey look for possible rate, Federal, State local government Hills, ato. USGS survey of theand Columbia Consortium to develop partnerships earthquake faults. agencies added on and theirafunding areas interest until the River Floodplain, surveyof by Oregon to. City increase thehad area. entire grown boundary. to over 2300 square ofproject its urban growth miles and $1. 1 M, with over 20 funding partners.

The Oregon Lidar Consortium (OLC) originated in 2007 with a request by DOGAMI to the 2007 legislature for funds to acquire lidar over the inhabited parts of Western Oregon. • The legislature provided $1. 5 M of the 4. 5 M • request and encouraged DOGAMI to seek funding partners to increase coverage The relatively small amount of funding requires prioritization to areas with significant local contributions Blue hatch at left shows the original $4. 5 M target based on the inhabited area of Western Oregon. Red hatch shows the area that could be covered by $1. 5 M, magenta shows existing data.

DOGAMI Business Plan for the OLC • Collection areas should be large and contiguous • Collection areas initially anchored by significant contribution • • • from local funding partner OLC builds on anchor funding by finding additional partners State funds used to knit together partner areas State funds are spent on the inhabited areas of the state Collection areas completely outside the inhabited areas are fine if fully partner funded Data in public domain Where possible, collection areas should include entire 6 th field watersheds

DOGAMI selected a vendor to provide lidar to the consortium. A nationwide RFP led to the selection for Watershed Sciences Inc. of Corvallis, Oregon, as the lidar vendor for the consortium under Oregon Price Agreement 8865.

OLC lidar prices are a function of area. DOGAMI adds 10% to the vendor price for quality control and management.

Data Specifications • Laser spot size on ground 15 -40 cm 1 m • Aggregate pulse density > 8/m 2 • Absolute accuracy of each point 20 cm horizontal and vertical • 50% sidelap for complete double coverage 1 m • Swath to swath consistency 15 cm (same point measured by adjacent swaths must have similar value) Point cloud image of field and building: red points are from one swath, blue from another.

DOGAMI provides three-way independent quality control for OLC data. 1. Compare accurately surveyed control points to the final lidar product to test absolute accuracy (+/- 20 cm). OLC lidar image showing DOGAMI quality control points (red triangles) collected by RTK-GPS survey. Colors indicate data from different swaths produce 2. Compare adjacent points from overlapping swaths to test consistency (+/- 15 cm) “Bird” anomalies spikes in bare earth model GPS elevation = 50. 40 m Lidar elevation = 50. 38 m 3. Lidar Inspect bare earth production software models forautomatically artifacts, is used to processing errors for compare locations huge numbers of points from overlapping swaths. Error = 2 cm Swath to swath differences, measured on hundreds of thousands of points per swath, average about 3 cm in this example

OLC Data Products Point cloud, LAS format 1/100 quad tiles 3 ft pixel bare earth DEM ESRI format (quad tiles) 3 ft pixel first return DEM ESRI format (quad tiles) 1 ft pixel intensity images (1/4 quad tiles) Ground points in LAS format (1/100 quad tiles) Aircraft trajectories Report and metadata !!

Data Distribution Options Funding partners: Copies are provided on external hard drives as soon as DOGAMI completes QC. Public: • • NOAA LDART website (point cloud) USGS CLICK website (point cloud) USGS NED website (DEM) GEO spatial data library website (DEM) METRO (Portland area only) PSLC (“Hood to Coast” area only) DOGAMI website (planned) DOGAMI publications on disk or drive (planned)

As of September 2008, 25 partners have added $2. 7 million to the Oregon Legislature’s $1. 5 million. The City of Turner The City of Philomath

As of September 2008, the OLC has been successful in building partnerships for several lidar collections around the state. Current status at http: //www. oregongeology. com/sub/projects/olc/default. htm

Future Plans n DOGAMI is seeking funds in future biennia to extend coverage to other parts of the state, as illustrated in the conceptual draft below.