LiDAR Data Gave Us 2’ Contours, Now What…?

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+

11/01/2012 MN GIS/LIS Fall Workshops


LiDAR Derived DEM Cell Size: 1 meter sq

Vertical Error: 15 cm1

1.5 million points / sq mile

USGS Standard DEM Cell Size: 30 meter sq

Vertical Error: “Equal to or

better than 15 meters”2

1600 points / sq mile

2.5

mi

1 Varies based on project specifications 2 http://edc.usgs.gov/guides/dem.html

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!!!

11/01/2012 Courtesy of MN GIS/LIS Fall

Workshops

Water Resources ◦ Floodplain mapping ◦ Storm water management ◦ Drainage basin

delineation ◦ Shoreline erosion

Geology ◦ Sinkhole identification ◦ Geologic/geomorphic

mapping Transportation

◦ Road and culvert design ◦ Cut and fill estimation ◦ Archaeological site

identification Agriculture

◦ Erosion control structure design

◦ Soils mapping ◦ Precision farming


Workshops

Water Quality Watershed modeling Wetland reconstruction Land cover/land use mapping

Forestry Forest characterization Fire fuel mapping

Fish and Wildlife Management

Drainage and water control Walk-in Accessibility Habitat Management

Emergency Management

Debris removal Hazard Mitigation

Need licenses: ◦ ArcEditor/ArcInfo

◦ 3D Analyst

◦ Spatial Analyst

AP Framework

ArcHydro Extension

Data in same projection

3D Analyst Extension ◦ Manages 3D data

◦ Generates surfaces for use in ArcHydro

Spatial Analyst Extension performs the analyses

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


Workshops

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

Single Return

Multiple returns

Waveform Returns


Workshops Slide courtesy of USGS

Single Return

Multiple returns

Waveform Returns


Workshops

1st return

2nd return

3rd return

4th return

Slide courtesy of USGS


Workshops

Returns

Single Return

Multiple returns

Waveform Returns


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

Land & Water (LCD)

Courtesy

of Sauk County

Field was contour strip cropped so vegetation is not uniform which may account for some of the variability along the cross section.

Lidar in Red

GPS Topo in Green

Courtesy of Sauk County

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.

Lidar in Red

GPS Topo in Green

Courtesy of Sauk County

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.

#*

#*

Maple Creek

SCBM2

Shots within 0.02’ relative to control.

50’ x 50’ Square Open Ground = 52 LIDAR Points (notice building point removal)

50’ x 50’ Square Woods = 16 LIDAR Points

An 11.3 Acre Selection = 13,634 Points

Great Planning tool

Engineering may require survey.

Shapefile limitation

Land Use limitation

Data maintenance

Lidar data can be visualized a number of ways ◦ POINTS ◦ TERRAINS (ESRI) ◦ GRIDS (DEM or DSM) ◦ TINS ◦ CONTOURS


Create File Geodatabase

Convert LiDAR to multipoint feature class

Make a Terrain

Export rasters (i.e. DEM, Grid) for analysis

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.

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

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.

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.

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.

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.

DEM Cellsize Matters

TIN vs. DEM

Terrain (represents, no labels, resolution)

Shapefile

Land Use Matters

2’ as base.

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

Arc Hydro Tools

Regression Tools

1. Terrain Preprocessing – topographic and hydrographic layers

2. Location specific layers – generated by the user

3. Statewide parameter layers – used for flood flow prediction

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

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.

Number of

rows

Number of Columns

(X,Y)

Cell size

NODATA cell

Each cell usually stores the average elevation of grid cell

Alternatively, it may store the value at the center of the grid cell

Elevations are presented graphically in shades or colors

67 56 49

53 44 37

58 55 22

Dig

ital

Gra

phic

al

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

DEM with unfilled sinks DEM with filled sinks Depth of sink

Sinks that are removed (filled) will contribute to downstream flow

Images from ESRI Map Book Gallery http://www.esri.com/mapmuseum/mapbook_gallery/volume19/conservation5.html

http://www.esri.com/mapmuseum/mapbook_gallery/volume19/conservation5.html

New Arc Hydro tools available to screen, evaluate, and leave / remove true sinks (in the exercise, all sinks will be filled)

67 56 49

53 44 37

58 55 22

Elevation

2 2 4

1 2 4

128 1 2

Flow Direction

Dig

ital

Gra

phic

al

32

16

8

64

4

128

1

2

Flow accumulation is the number of upstream grid cells that contribute flow to a given grid cell

Calculated from flow direction

2 2 4

1 2 4

128 1 2

Flow Direction

0 0 0

0 3 2

0 0 8

Flow Accumulation

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

All the cells in a particular segment have the same grid code that is specific to that segment

Junction

Edge

Arc Hydro uses AGREE method to “burn-in” streams

Adjusts elevation of DEM based on input vector line features

Drop/raise elevation of cells corresponding to lines by smoothdrop

Buffer lines by smoothdistance

Elevation of cells inside buffer are adjusted to a straight line from edge of buffer to line.

Drop/raise the elevation of the cells corresponding to the lines by sharpdrop

30

40

50

60

70

80

90

100

0

20

40

60

80

10

0

12

0

140

160

180

200

220

240

260

Lateral Distance (m)

Ele

vati

on (

m)

Original Surface

Modified Surface

Correct drainage path

Derived drainage path

Correct (burned) drainage path

Derived drainage path

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

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

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

1. Terrain Preprocessing – topographic and hydrographic layers

2. Location specific layers – generated by the user

3. Statewide parameter layers – used for flood flow prediction

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)

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

http://pubs.usgs.gov/wri/wri034250/

Layer was obtained from USGS

Each region has a different set of regression equations

Layer was obtained from USGS

Weighted average of the watershed

Original source: 1:250,000 scale soil maps of Wisconsin (Hole et. al. 1968)

Rainfall value determined at the watershed outlet

Rainfall data from Huff and Angel, 1992

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

http://www.climatesource.com/us/fact_sheets/fact_snowfall_us.html

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

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

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

Stream Power Index

Online Tutorial

http://wrc.umn.edu/randpe/agandwq/tsp/lidar/trainingvideos/index.htm



Slope Raster (%) X Flow Accumulation

LN (above)

Symbology (is a guess yet…)

Field proofing

Tweak symbology

Targeted Conservation


Workshops

Lidar Point Cloud of Structures


Emergency Management

Plat Book

Zoning

Stormwater

Other

ENVI EX 4.8 (www.excelisvis.com)

ENVI, EX + IDL

ArcGIS + 3D Analyst

http://www.excelisvis.com/

2010 6” Color Aerial

2010 6” CIR Aerial

2005 6” Black & White Aerial

2005 LiDAR Data (stood alone)

Acquisition

Building Lean

Intermediate Shapefile

Angled Buildings

Grid


Workshops

Planimetrics

Change Detection

Land Use

Wetland ID

Sauk County LCD

MN-DNR

NRCS

USGS

PRESENTER: JEREMY FREUND, P.E. OUTAGAMIE COUNTY LCD

[email protected]

Slides courtesy of:

LiDAR Data Gave Us 2’ Contours, Now What…?

Technology

Transcript of LiDAR Data Gave Us 2’ Contours, Now What…?