Seeing through the trees LIDAR for the Puget

  • Slides: 20
Download presentation
Seeing through the trees: LIDAR for the Puget Lowland Ralph Haugerud, Craig Weaver U.

Seeing through the trees: LIDAR for the Puget Lowland Ralph Haugerud, Craig Weaver U. S. Geological Survey Jerry Harless Puget Sound Regional Council and thanks to Terra. Point LLC, Houston TX

• Why LIDAR? • What is LIDAR? • How are we doing LIDAR?

• Why LIDAR? • What is LIDAR? • How are we doing LIDAR? • What are we finding?

In some places, it is easy to see where the active faults are. 30

In some places, it is easy to see where the active faults are. 30 km

Seattle Tacoma 30 km In other places, it is not.

Seattle Tacoma 30 km In other places, it is not.

What are the salient differences? SF Bay area Puget Lowland slip rate 3 cm/yr

What are the salient differences? SF Bay area Puget Lowland slip rate 3 cm/yr strike slip 4 mm/yr shortening average tree height ? 10 ft ? 100 ft ~106 18, 000 years age of landscape

age slip rate = feature size 18, 000 yr 1 mm/yr = 18 m

age slip rate = feature size 18, 000 yr 1 mm/yr = 18 m 106 yr 1 mm/yr = 1 km In the Puget Lowland, to see a fault with the same slip rate as in the SF Bay area, we have to look more closely.

LIght Detection And Ranging • Airborne scanning laser rangefinder • Differential GPS • Inertial

LIght Detection And Ranging • Airborne scanning laser rangefinder • Differential GPS • Inertial Navigation System 30, 000 points per second at ~15 cm accuracy • $400–$1000/mi 2, 106 points/mi 2, or 0. 04– 0. 1 cents/point Extensive filtering to remove tree canopy (virtual deforestation)

10 -meter DEM from contours

10 -meter DEM from contours

12 -ft DEM from LIDAR

12 -ft DEM from LIDAR

Picture: Oblique view of S end Rockaway Beach

Picture: Oblique view of S end Rockaway Beach

High-resolution LIDAR topography

High-resolution LIDAR topography

Uses for high-resolution topography • Finding faults (earthquake frequency, kinematics) • Geologic mapping •

Uses for high-resolution topography • Finding faults (earthquake frequency, kinematics) • Geologic mapping • Landslide hazards • Flood hazards, groundwater infiltration, runoff modelling • Fish habitat • Precision forestry ? Noise propagation

Why is LIDAR better than photogrammetry? (It’s the trees) Suppose timber allows 1 of

Why is LIDAR better than photogrammetry? (It’s the trees) Suppose timber allows 1 of 3 arbitrary rays to reach ground; 1/3 of ground can be surveyed by LIDAR Photogrammetry requires 2 separate views of a point; only 1/9 of ground will be locatable

Bainbridge Island, KPUD 1996 -1997 Seattle Snoqualmie, USGS-NMD 1998 -2001? Tacoma

Bainbridge Island, KPUD 1996 -1997 Seattle Snoqualmie, USGS-NMD 1998 -2001? Tacoma

Puget Sound LIDAR Consortium Participants • Kitsap County • Kitsap PUD • City of

Puget Sound LIDAR Consortium Participants • Kitsap County • Kitsap PUD • City of Seattle • Puget Sound Regional Council • NASA • USGS Expertise (exclusive of USGS) –Contracting –Surveyor –prior LIDAR experience –Geologist –GIS

Puget Sound LIDAR Consortium • • • No formal structure One agenda One contract

Puget Sound LIDAR Consortium • • • No formal structure One agenda One contract Separate payments Share data Release all data to public domain (www. Get. It. Yourself. Bob, to be hosted by UW library)

PSLC Feb 2001 March-April 2000, Feb 2001 Seattle Tacoma

PSLC Feb 2001 March-April 2000, Feb 2001 Seattle Tacoma

~$3 M LIDAR already flown Seattle to be flown Winter 2001 -2002 Tacoma ~$3.

~$3 M LIDAR already flown Seattle to be flown Winter 2001 -2002 Tacoma ~$3. 3 M

15 km west of Seattle Toe Jam Hill fault scarp Waterman Point scarp beach

15 km west of Seattle Toe Jam Hill fault scarp Waterman Point scarp beach uplifted during 900 AD earthquake

LIDAR Uvod u daljinsku detekciju LIDAR 2 LIDARLIDAR Uvod u daljinsku detekciju LIDAR 2 LIDAR
Tournament Trees Winner trees Loser Trees Winner TreesTournament Trees Winner trees Loser Trees Winner Trees
Tournament Trees Winner trees Loser Trees Winner TreesTournament Trees Winner trees Loser Trees Winner Trees
Selection Trees Winner trees Loser Trees Winner TreesSelection Trees Winner trees Loser Trees Winner Trees
Trees trees binary trees traversals of trees templateTrees trees binary trees traversals of trees template
Puget Sound Nearshore Partnership Puget Sound Partnership LeadershipPuget Sound Nearshore Partnership Puget Sound Partnership Leadership
Puget Sound Bats Gregory A Green Puget SoundPuget Sound Bats Gregory A Green Puget Sound
Puget Energy Puget Sound Energy EEI Company UpdatePuget Energy Puget Sound Energy EEI Company Update
PUGET SOUND LABOR AGENCY Volunteer Orientation PUGET SOUNDPUGET SOUND LABOR AGENCY Volunteer Orientation PUGET SOUND
Puget Sound Partnership Processes Required to Measure PugetPuget Sound Partnership Processes Required to Measure Puget
Finding faults with LIDAR in the Puget LowlandFinding faults with LIDAR in the Puget Lowland
Lidar and the Oregon Lidar Consortium Beaverton photoLidar and the Oregon Lidar Consortium Beaverton photo
Praktikum IV LIDAR 20092010 LIDAR light detection andPraktikum IV LIDAR 20092010 LIDAR light detection and
Introduction to LIDAR Mapping Technology LIDAR Light DetectionIntroduction to LIDAR Mapping Technology LIDAR Light Detection
Introduction to LIDAR Mapping Technology LIDAR Light DetectionIntroduction to LIDAR Mapping Technology LIDAR Light Detection
LIDAR IPRAL IPSL HiPerformance multiwavelength Raman Lidar forLIDAR IPRAL IPSL HiPerformance multiwavelength Raman Lidar for
Overview What is LIDAR Example schematic LIDAR returnOverview What is LIDAR Example schematic LIDAR return
UNDERSTANDING LIDAR LIGHT DETECTION AND RANGING LIDAR isUNDERSTANDING LIDAR LIGHT DETECTION AND RANGING LIDAR is
LIDAR Introduction to selected topics Michael Gerding LIDARLIDAR Introduction to selected topics Michael Gerding LIDAR