2. 1mb = 1,000 kb
1 gb = 1,000 mb
1 tb = 1,000 gb
2 Terrabytes = 1,428,571 3.5” floppy disks
◦ Today’s cost around $750.00
Stacked on top of one another = 2.5 miles
high!
◦ And at the time, they cost $1.00+
MN GIS/LIS Fall Workshops 11/01/2012
3. LiDAR Derived DEM
Cell Size: 1 meter sq
Vertical Error: 15 cm1
1.5 million points / sq mile
2.5
mi
USGS Standard DEM
Cell Size: 30 meter sq
Vertical Error: “Equal to or
better than 15 meters”2
1600 points / sq mile
1 Varies based on project specifications
2 http://edc.usgs.gov/guides/dem.html
MN GIS/LIS Fall Workshops 11/01/2012
4. LiDAR datasets tend to be very large
◦ LAS Format
All Returns – 4 Million points ~ 55 mb / square mile
Bare Earth – 3 million points ~ 45 mb / square mile
◦ ASCII Format
All Points – 4 million points ~ 75 mb / square mile
Bare Earth – 3 million points ~ 73 mb / square mile
◦ Grid Format
5 mb / square mile in integer format
11.2 mb / square mile in floating point format
OC has over 300GB in raw data!!!
Courtesy of MN GIS/LIS Fall
Workshops 11/01/2012
5. Water Resources Water Quality
◦ Floodplain mapping Watershed modeling
◦ Storm water management
◦ Drainage basin Wetland reconstruction
delineation Land cover/land use
◦ Shoreline erosion mapping
Geology Forestry
◦ Sinkhole identification
◦ Geologic/geomorphic Forest characterization
mapping Fire fuel mapping
Transportation Fish and Wildlife
◦ Road and culvert design
◦ Cut and fill estimation Management
◦ Archaeological site Drainage and water
identification control
Agriculture Walk-in Accessibility
◦ Erosion control structure
design Habitat Management
◦ Soils mapping Emergency
◦ Precision farming Management
Debris removal
Hazard Mitigation
Courtesy of MN GIS/LIS Fall
Workshops 11/01/2012
6. Need licenses:
◦ ArcEditor/ArcInfo
◦ 3D Analyst
◦ Spatial Analyst
AP Framework
ArcHydro Extension
Data in same projection
7. 3D Analyst Extension
◦ Manages 3D data
◦ Generates surfaces for use in ArcHydro
Spatial Analyst Extension performs the
analyses
8. LAS files (Common LiDAR Data Exchange)
◦ Stores a variety of point information
Number of returns
Return Number
Intensity
Classification
X,Y, Z values
Scan Direction
Scan Angle Rank
GPS Time
Courtesy of MN GIS/LIS Fall
Workshops 11/01/2012
9. Intensity = amount of
energy reflected for
each return
Different surfaces
reflect differently based
on wavelength of laser
Example at 1064nm
(NIR), water absorbs,
vegetation highly
reflective
Can be used to build
black and white near-IR
images
11/01/2012 Courtesy of MN GIS/LIS Fall Workshops
Slide courtesy of USGS
10. Single Return
Multiple returns
Waveform
Returns
Courtesy of MN GIS/LIS Fall
Workshops 11/01/2012
Slide courtesy of USGS
11. Single Return
1st return
Multiple returns
2nd return
Waveform 3rd return
Returns
4th return
Courtesy of MN GIS/LIS Fall
Workshops 11/01/2012
Slide courtesy of USGS
13. Classification – Points can be classified to
reflect their ground condition
Class Definition
0 Created, Never Classified
1 Unclassified
2 Ground
3 Low Vegetation
4 Medium Vegetation
5 High Vegetation
6 Building
7 Low Point (noise)
8 Model Key-Point (mass point)
9 Water
12 Overlap
MN GIS/LIS Fall Workshops 11/01/2012
15. Lidar in Red
GPS Topo in Green
Co
urt
es
y
of
Sa
uk
Field was contour strip cropped so vegetation is not uniform which may Co
account for some of the variability along the cross section. un
ty
16. Lidar in Red
GPS Topo in Green
The same cross section with lidar shifted down vertically 3”. Lidar may give
absolute elevations slightly higher than referenced vertical datum, but relative
elevations for similar land cover provide good results.
Courtesy of Sauk County
17. Mowed meadow and lawn land cover provided lidar elevations that
matched absolute reference vertical datum elevations.
Marsh (heavy vegetation, unmowed, not pastured) land cover provided lidar
elevations higher than absolute reference vertical datum elevations.
There is a lidar elevation shift when going from one land cover type to
another, but most sites are typically of one land cover so Sauk County
hasn’t considered it a significant issue.
Courtesy of Sauk
County
18. *
#SCBM2
Maple Creek
Shots within 0.02’
relative to control.
19.
20. 50’ x 50’ Square Open Ground = 52 LIDAR
Points (notice building point removal)
23. Great Planning tool
Engineering may require survey.
Shapefile limitation
Land Use limitation
Data maintenance
24.
25. Lidar data can be visualized a number of ways
◦ POINTS
◦ TERRAINS (ESRI)
◦ GRIDS (DEM or DSM)
◦ TINS
◦ CONTOURS
MN GIS/LIS Fall Workshops 11/01/2012
26. Create File Geodatabase
Convert LiDAR to multipoint feature class
Make a Terrain
Export rasters (i.e. DEM, Grid) for analysis
27. Here’s our process:
1. Need 3D Analyst or Spatial Analyst for LIDAR Processing.
2. In ArcCatalog, right-clickNEWCreate a file geodatabase.
3. In Arc Catalog, right-click the named file geodata baseCreate a
feature dataset and import County coordinate system for horizontal
projection.
4. Choose vertical projection of LIDAR data (NAVD 88 for us)
5. In ArcCatalog Use 3D-Analyst ToolsConversionFrom File”ASCII
3d to Feature Class” tool to select tiles to process (careful over 6 tiles.)
6. In ArcCatalog, right-click the Feature DatasetNEWTerrain.
7. Follow the Terrain Wizard. We let GIS Calculate the Pyramids.
8. In ArcCatalog Use 3D-Analyst ToolsConversionFrom
Terrain”Terrain to Raster” tool to convert Terrain to a DEM. (3
min./tile)
9. For hydrology, “CELLSIZE 15” seems to be good compromise.
10. For Cross-Section work, may want to use 3D-Analyst
ToolsConversionFrom Terrain”Terrain to TIn” tool to convert
Terrain to a TIN.
11. A county-wide terrain and DEM may need to run over the weekend.
28. Per ESRI, a terrain dataset is a multiresolution, TIN-
based surface built from measurements stored as
features in a geodatabase.
Terrains reside in the geodatabase, inside feature
datasets with the features used to construct them.
Terrains have participating feature classes and
rules, similar to topologies. Common feature
classes that act as data sources for terrains include
the following:
◦ Multipoint feature classes of 3D mass points such as lidar
◦ 3D point and line feature classes, i.e. breaklines
◦ Study area boundaries that define the bounds of the terrain
dataset
29. Courtesy of MN GIS/LIS Fall
Workshops 11/01/2012
Slide courtesy of USGS
30. From the 3D Analyst Tools, double-click the
Terrain To Raster geoprocessing tool to open it.
Input Terrain
◦ add the terrain dataset
Output Raster
◦ specify the location where the raster dataset is to be
created.
◦ Recommend including grid size in name
Output data type
◦ Either 32-bit floating point or 32-bit integer.
◦ Floating point is the default value.
31. Interpolation method
◦ Either Linear or Natural Neighbors.
◦ Both are TIN-based interpolation methods applied through
the triangulated terrain surface.
◦ The Linear option finds the triangle encompassing each cell
center and applies a weighted average of the triangle's
nodes to interpolate a value.
◦ The Natural Neighbors option uses the Voronoi neighbors
of cell centers.
◦ Consider the natural neighbors method for interpolating a
terrain surface.
◦ Natural neighbor interpolation takes longer processing
time; however, the generated surface is much smoother
than that produced with a linear interpolation. It is also less
susceptible to small changes in the triangulation.
32. Sampling Distance
◦ Either Observations or Cellsize, which controls the
horizontal resolution of the raster.
◦ Observations method
calculates the cell size based on the set value this
number represents and the number of cells you want
on the longest edge of the raster surface.
◦ Cellsize method
You set the cell size explicitly
i.e. “CELLSIZE 15” outputs a raster with 15’ square
representing the surface.
33. Resolution
◦ The resolution parameter indicates which
pyramid level of the terrain dataset to use for
conversion.
◦ To output a raster dataset at full resolution, set
this parameter to 0.
To extract a subset of the terrain, click the
Environments button on the bottom of the
geoprocessing tool. Click the General
Settings tab and define the extent of the
output DEM.
34.
35.
36.
37. DEM Cellsize Matters
TIN vs. DEM
Terrain (represents, no labels, resolution)
Shapefile
Land Use Matters
2’ as base.
38.
39. A data infrastructure for storing and
integrating hydro data within ArcGIS
◦ A set of hydro objects
◦ A set of standardized attributes
◦ A vocabulary for describing data
◦ A toolset for data model applications
41. 1. Terrain Preprocessing – topographic and
hydrographic layers
2. Location specific layers – generated by the
user
3. Statewide parameter layers – used for flood
flow prediction
42.
43. Multiple ways of representing elevation
◦ Contours and points (Vector)
◦ Triangulated irregular network (TIN)
◦ Digital elevation model (Raster)
Each has advantages and disadvantages
DEM is used for Arc Hydro terrain analysis
and watershed delineation
44. DEMs have become a common way of representing elevation where every grid cell is given
an elevation value. This is allows for very rapid processing and supports a wide-array of
critical analyses.
46. Each cell usually
Graphical
stores the average
elevation of grid cell
Alternatively, it may
store the value at the
center of the grid cell
67 56 49
Elevations are
Digital
53 44 37 presented graphically
in shades or colors
58 55 22
47. Spurious sinks
◦ Spurious sinks are a byproduct of the DEM
creation / interpolation process
◦ Spurious sinks ought to be removed
True sinks
◦ Some landscapes have natural depressions
◦ e.g. pothole lakes
◦ True sinks may be retained or removed
Sinks are removed by raising the elevation
of the sink to the elevation of the outlet
48. DEM with unfilled sinks DEM with filled sinks Depth of sink
Images from ESRI Map Book Gallery
http://www.esri.com/mapmuseum/mapbook_gallery/volume19/conservation5.html
Sinks that are removed (filled) will contribute
to downstream flow
49. New Arc Hydro tools available to screen,
evaluate, and leave / remove true sinks (in
the exercise, all sinks will be filled)
52. Flow accumulation
is the number of
upstream grid
cells that
contribute flow to
2 2 4 0 0 0
a given grid cell
Calculated from
1 2 4 0 3 2 flow direction
128 1 2 0 0 8
Flow Direction Flow Accumulation
53. Streams are defined
from the flow
accumulation grid
based on a threshold
Reclassify grid
◦ If [Cell] > Threshold
Then [Cell]=Stream
◦ If [Cell] < Threshold
Then [Cell]=Not
Stream
54. All the cells in a particular segment have the same grid code
that is specific to that segment
56. Arc Hydro uses AGREE
100 method to “burn-in” streams
Original Surface Adjusts elevation of DEM
90 Modified Surface based on input vector line
features
80 Drop/raise elevation of cells
corresponding to lines by
Elevation (m)
70 smoothdrop
Buffer lines by
60 smoothdistance
Elevation of cells inside
50 buffer are adjusted to a
straight line from edge of
40 buffer to line.
Drop/raise the elevation of
30 the cells corresponding to
the lines by sharpdrop
20
40
60
80
0
100
120
140
160
180
200
220
240
260
Lateral Distance (m)
59. Difference between LiDAR data and 30-meter
DEM
◦ LiDAR is detailed enough to show road grades /
ditches
◦ More effort required to burn proper drainage paths
Burn short segments at culvert crossings
60.
61.
62.
63. Catchment – the area
draining to a single
segment of stream
between two junctions
Subwatershed – the
drainage area between
two user defined
drainage points
Watershed – the entire
drainage area
upstream of a user
defined drainage point
64. Catchment Grid Delineation – creates a grid of
catchment areas draining into each stream segment
Catchment Polygon Processing – coverts catchments into
a polygon feature class
Adjoint Catchment Processing – For each catchment that
is not a head catchment, a polygon representing the
whole upstream area draining to its inlet point is
constructed
65. 1. Terrain Preprocessing – topographic and
hydrographic layers
2. Location specific layers – generated by the
user
3. Statewide parameter layers – used for flood
flow prediction
66. WatershedPoint – user
defined outlet point
Watershed – resulting
watershed polygon
LongestFlowPath3D –
longest flowpath line
Slp1085Point – points
at 10 and 85 percent
along the longest
flowpath (used for
slope calculation)
67. Rainfall-runoff model: HEC-HMS
◦ Run a synthetic/observed storm over a subdivided
watershed model
◦ HEC-GeoHMS extension can be used to set up model
geometry
Flood-Frequency Characteristics – based on the
USGS Water-Resources Investigations Report 03-
4250, “Flood-Frequency Characteristics of
Wisconsin Streams” by J.F. Walker and W.R. Krug
(2003). http://pubs.usgs.gov/wri/wri034250/
◦ Step 1: Extract watershed parameters
◦ Step 2: Plug parameter values into Regional Regression
Equations
68.
69. Layer was obtained
from USGS
Each region has a
different set of
regression
equations
70. Layer was obtained
from USGS
Weighted average
of the watershed
Original source:
1:250,000 scale
soil maps of
Wisconsin (Hole et.
al. 1968)
71. Rainfall value
determined at the
watershed outlet
Rainfall data from
Huff and Angel,
1992
72. Snowfall was clipped
from a nationwide
grid from the Climate
Source
The same source data
was used to create the
snowfall contours in
USGS Figure 2
Snowfall value
determined at the
watershed outlet
http://www.climatesource.com/us/fact_sheets/fact_snowfall_us.html
73. USGS method is to
determine forest and
storage from the
symbols shown on the
USGS 24K quad maps
(DRGs)
Forest and Storage
grids were developed
from 1992 WISCLAND
land cover
classification for use
in Arc Hydro
Weighted average of
the watershed
74. After extracting parameters, run Regression
Calculator from Arc Hydro
Before applying to real-world situations,
users should…
◦ Understand equation limitations
◦ Know the stand errors of estimate
◦ Be familiar with other calculation techniques listed
in the USGS report
75.
76. Arc hydro link
◦ http://resources.arcgis.com/content/hydro-data-
model
Water resources
◦ http://www.esri.com/industries/water_resources/re
sources/data_model.html
