Terrain Analysis Principles and Applications by zbs19295

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									 High-Resolution Surface
Modeling of River Channels
 using Light Detection and
   Ranging (LiDAR) Data

        Graeme Aggett
        Center for Spatial Information @
        Central Washington University


        RGIS-Pacific NorthWest
        aggettg@cwu.edu
           Talk Outline
Intro to terrain modeling
Topographic attributes
Channel surface modeling
LiDAR
Developing and testing a LiDAR DEM
Questions and Answers
Hydraulic Modeling
Resolution Comparison – 1 sq mile
Bainbridge island, WA
Processing LiDAR points and
Developing the LiDAR DEM
Classification and interpolation
Creation of bare earth model
Hydraulic “continuity” and the need for
breaklines
Error assessment
Developing the LiDAR DEM & Terrain Surface




Point_cloud1   Point_cloud2   river fly
Developing the LiDAR DEM & Terrain Surface –
                 classification
VDF algorithm
                               ARC-INFO command

Convert TIN to grid1           tinlattice

Calculate 3x3 mean at each     grid2 = focal mean
cell                           (grid1)

Convert TIN vertices to        Tinarc TIN
point database (Z value in     cover1 point
item SPOT)

Calculate item SPOT2 =         latticespot
value of GRID2 at each         grid2 cover1
point in database              spot2

CURVATURE = SPOT2 – SPOT

If CURVATURE > testvalue1
or CURVATURE < testvalue2
then mark point for deletion
What is LiDAR?




                 CSI
Creation of “bare earth”
     terrain model
Fly-thru01
      Inputs for Creating a TIN

 Mass Points           Soft Breaklines      Hard Breaklines




• Hard breaklines define locations of abrupt surface change
(e.g. stream bank, bridges, dams)
• Soft breaklines are used to ensure that known z values
along a linear feature are maintained in the TIN.
                                                         Bank


                                                     Sa




                                      L
                                                W

                                          N         Sr
                                                          H

                                          θ l
See next slide for nomenclature




                                  Stream Bed
Developing the LiDAR DEM & Terrain
    Surface – error assessment
  Simple Error budget for LiDAR
             points:
Survey grade
GPS used to
extract control
heights at random
locations
RMS error
calculated
Simple Error budget for LiDAR DEM:

  Z error = [ (measurement error)2 +
  (classification error)2 + (interpolation
  error)2 ]1/2
Naches 2 points 1501-1639 {5z}
   River   Mid-channel Bar   River
                             Comparison plotting
                                              Profile 01

                   840


                   820


                   800
Elevation (Feet)




                                                                                 LIDAR
                   780                                                           Photo

                   760
                                                                                 USGS


                   740


                   720
                      0.00    5000.00   10000.00           15000.00   20000.00
                                        Distance (feet)
      LiDAR advantages

ease of data acquisition
increased ability to determine surface
elevations in difficult areas
expeditious data delivery
data sets may be acquired at reduced
costs when compared to traditional field
survey/ photogrammetric mapping
Terrain Resolution ~ Payback
Terrain Resolution ~ Payback

								
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