Hydrologic Applications (Conservation Applications of LiDAR) March 2012 1
Audience and Prerequisites
The workshops are designed for GIS and CAD users who address natural resource issues. The target audience works for Watershed Districts, Soil and Water Conservation Districts, counties, cities, not‐for‐profit organizations, private firms, and state and federal agencies.
Before attending any of the workshops, participants must have an intermediate skill level with ArcGIS application, including and not limited to importing and managing files and layers, processing geographic data, and a general understanding of raster data processing and management. Contact the coordinator if you are unsure if you have the background to take these courses.
The “Basics” module is required before taking any of the other modules. The “Hydrology” module is required before taking the “Wetland Mapping” module, and recommended before the “Terrain Analysis” module.
Sean VaughnGIS Hydrologist
Minnesota Department of Natural Resources
Conservation Applications of LiDARData
In collaboration with:
Minnesota Board of Water and Soil Resources
USDA Natural Resources Conservation Service
Minnesota Department of Natural Resources
Presented by:
University of Minnesota
Co‐sponsored by the Water Resources Conference
tsp.umn.edu/lidar
Workshops funded by:
Minnesota Environment and Natural Resources Trust Fund
Conservation Applications of LiDARData
Training Modules:
Basics of Using LiDAR Data
Terrain Analysis
Hydrologic Applications
Engineering Applications
Wetland Mapping
Forest and Ecological Applications
tsp.umn.edu/lidar
Module developed by: Joel Nelson (UM Dept of Soil Water and Climate), Sean Vaughn (MN DNR)
Hydrologic conditioning (culverts), floodplain mapping, watershed delineation, delineating inundation areas, depression analysis.
Focus will be on hydrography related to LiDAR derived DEMs
Initial Acquisitions –Water Related
DEM Display
Digital Dams
Hydrologically Corrected DEMs
Cautions
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 2
Class Introductions
7
Student Introductions
Questions:
Who has worked with raster data?
Who has worked with raster data for hydrologic modeling?
Who uses LiDAR data currently?
Who uses LiDAR data for raster processing to derive products ?
Sean VaughnGIS Hydrologist
Minnesota Department of Natural Resources
DNR Watershed Delineation Project
Lead GIS Specialist / Project Manager
GIS RESEARCH ASSISTANT January 1995 - April 1995
University of Minnesota, College of Natural Resources, Department of Forest Resources, St. Paul, MN
• Digitized soil survey data using ARC/INFO v. 6.0 software and a Compardigitizing tablet.
• Prepared soil survey data for zoom transferring process by highlighting all hydric soil to separate hydric soil from non-hydric.
• Edge matched border coordinates between coverages and joined to create a seamless coverage.
Course Objectives…
Course Objectives
Gain an understanding of some different techniques for LiDAR DEM display
Create a topographic position index raster (TPI).
Perform hydrologic conditioning of DEM.
Understand the importance of QA/QC of LiDAR data.
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LiDAR Acquisition…
To Date, LiDARAcquisition in MN is Related to Hydrology.
Hydraulic modeling, Hydrographic feature generation. Initial Acquisitions –Water Related
Flood Modeling & Mapping
LiDAR Acquisition ‐Hydrology
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 3
Hydrographic Derivatives Watercourse Extraction
Stream Delineation
Wetland Delineation
Watershed Delineation
Erosion Analysis
Water Quality Modeling
LiDAR Acquisition ‐Hydrology
LiDAR “Excitement”& Interest in Minnesota…
Interest – Dissemination – Excitement –Application
Historically “we” derived products from source data then published it for consumption.
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Raster –Vector Integration
Regional Application
Statewide Application
Hydrology/Hydrography Representation16
Minnesota LiDAR Data Coordination…2. Research and Education Subcommittee B
The interest and availability of LiDAR data has led to the creation of a special committee.
A Link ‐ http://www.mngeo.state.mn.us/committee/elevation/index.html B Link ‐ http://www.mngeo.state.mn.us/committee/elevation/research_education/index.html
1. Digital Elevation Committee A
Minnesota has 2 Committees Tasked with LiDAR Data Development, Management and Deployment .
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 4
Minnesota Digital Elevation Committee –Research and Education Subcommittee
Mission Statement:
Design and promote best practices with LiDAR data for MinnesotaEnsure there is consistency in data development, application, and training.
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Training: Course Planning and Design Survey
http://www.mngeo.state.mn.us/committee/elevation/research_education/index.html
1 Adam Birr Minnesota Department of Agriculture - MDA (507) 206-2881 [email protected]
2 Pete CooperNatural Resources Conservation Service -Minnesota State Office NRCS - MN State Office
(651) 602-7884 [email protected]
3 Les Everett University of Minnesota (612) 625-6751 [email protected]
4 Tom Hollenhorst US EPA Mid Continent Ecology Division - Duluth (218) 529-5220 [email protected]
5 Dave Kirkpatrick Houston Engineering (701) 499-2058 [email protected]
6 Steve Kloiber Minnesota Department of Natural Resources - DNR (651) 259-5164 [email protected]
7 Tim Loesch Minnesota Department of Natural Resources - DNR (651) 259-5475 [email protected]
8 Grit May International Water Institute - IWI (701) 231-5266 [email protected]
9 Joel Nelson University of Minnesota – U of MN St. Paul (612) 625-9235 [email protected]
10 Nancy Rader Minnesota Geospatial Information Office - MnGeo (651) 201-2489 [email protected]
11 Nels Rasmussen Minnesota Pollution Control Agency (507) 206-2614 [email protected]
12 Mark Reineke WSN Engineering (320) 335-5050 [email protected]
13 Chris Sanocki U.S. Geological Survey - MN USGS (763) 783-3151 [email protected]
14 Shelly Sentyrz Minnesota Department of Natural Resources – DNR (218) 308-2374 [email protected]
15 Gerry SjervenNatural Resources Research InstituteUniversity of Minnesota – Duluth - NRRI
(218) 720-4388 [email protected]
16 Sean Vaughn (chair) Minnesota Department of Natural Resources - DNR (763) 689-7100 x226 [email protected]
Digital Elevation Committee –Research and Education Subcommittee
Web Page Hydrologically Correcting LiDAR Derived
DEMs Terminology Culvert Inventory Guidelines Training
http://www.mngeo.state.mn.us/committee/elevation/research_education/index.html
Link:
The Role of LiDAR Related Training in MN. Expertise
Coordination
Data Development/Developers
Guidance & Best Practices
Work with Digital Elevation Committee 22
Personal Perspective…
Interest and Excitement
Excitement –
A Personal Perspective on Mapping Hydrography…24
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 5
Manual Interpretation
Manual Illustration
25
One dimensional ‐ Planar view ‐Manual ‐GIS
1992
Field Inspection ‐Groundtruthing
Depressions & Impressions
Drainage Discoveries
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Field Inspection –Aerial Review
Oblique photos indicate linear signatures of ditching.
GIS – Innovation
GIS Brings it all together
Raster
Vector
Landscape
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1994
DRGs & DOQs The 30 meter DEM was used to create the DOQ.
Statewide 30 mDEM
DRG Draped on 30m DEM
30
Resurrection of the DEM
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 6
Elevation Data Sources –LiDAR
Laser reflectance measurement
6‐in vertical accuracy
Spacing can be as little as 2‐feet apart
$150 ‐ $250 / sq. mile
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High Quality DOQ 3Meter DEM
LiDAR products allow me identify all of those hydrography features from one high accuracy data set.
But it’s still not perfect.
Digital Elevation Background & Theory
DEMs Details
DEM resolution
Basic Terrain Derivatives
Minnesota LiDAR
Formats ‐ Contour Elevation Data• Source Independent
• USGS topo maps
• Contour shows a line of constant elevation
• Generally used more as a cartographic representation
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 7
DEM’s consist of an array representing elevation values at regularly spaced intervals commonly known as cells.
ELEVATION VALUES (ft)
Formats ‐ Digital Elevation Models
X
Y
Z
DEM Details…
DEM = Raster = Grid
Digital Elevation Models
Raster (Format) DEM = Grid
vs. Vector data format
Raster (Format) DEM = Grid
vs. Vector data format
DEM Structure
Each cell usually stores the average elevation of grid cell.
Typically they 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
Digital
Graphical
Digital Elevation Models
DEMs are a common way of representing elevation where every grid cell is given an elevation value. This allows for very rapid processing and supports a wide‐array of analyses.
Digital Elevation Models
DEM Resolution…
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 8
Resolution
30 Meter
USGS produced from Quad Hypsography.
DNR published format in MN.
Course resolution
10 Meter
Interpolated
Resampled
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Previously Published National DEMs
Resolution
1 Meter
3 Meter
Most common published format in MN.
Storage requirements & faster drawing speeds.
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Previously Published National DEMs
Resolution Tradeoff
Lower resolution = Faster processing
Higher resolution = Maintain small features
1‐meter DEM claims 9‐times more process resources and storage than a 3‐meter DEM
Basic Terrain Derivatives
Slope
Aspect
Flow Direction
Topographic Depressions (Sinks)
Slope Analysis
Surface slope is defined as the change in elevation with respect to distanceri
se
run
Looks simple . . . Right?
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 9
Slope Analysis
Elevation varies in both x and y directions
a b c
d e f
g h i
Example Slope Calculation
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53 44 37
58 55 22
2X
2X
Z, X, and Y units need to be the same!
Caution some programs output radians.
Aspect
dx
dz
dy
dz
45
90
135
180
225
270
315
Direction of steepest descent
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53 44 37
58 55 22
The direction of the maximum rate of change in the z‐value from each cell in a raster surface.
Degrees from 0 to 359.9, measured clockwise from north.
Calculate the solar illumination for each location in a region as part of a study to determine the diversity of life at each site.
Hydrologic Applications of Terrain Analysis
Automated Stream Delineation
DEM Derived Hydro Data
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53 44 37
58 55 22
Elevation
2 2 4
1 2 4
128 1 2
Flow Direction
Digital
Graphical
D8 Flow Direction Encoding
32
16
8
64
4
128
1
2
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 10
Flow Accumulation
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 Elevation data drapedon Shaded Relief
The flow direction is derived form a digital elevation model.
The flow direction is derived from a digital elevation map (DEM).
DEM
Generating Surface Parameters
28May04
Elevation Grid (Z ‐ ft)
66 55 48 45
52 43 36 37
57 54 21 30
60 46 20 15
128
2 2 4 8
1 2 4 8
1 2 4
2 1 4 4
Flow Direction Grid
Generating Surface Parameters
28May04
128
We will now take a look at how this flow direction grid is developed.
2 2 4 8
1 2 4 8
1 2 4
2 1 4 4
Flow Direction Grid
Each cell is coded with a value corresponding to the vector direction from the flow direction compass.
Flow Direction is based on the elevation of each grid cell. Water is assumed to flow from each cell to the lowest of its eight neighbors that has the steepest descent.
Generating Surface Parameters
Flow Direction Compass
1
64128
24
8
16
32
128
2 2 4 8
1 2 4 8
1 2 4
2 1 4 4
Flow Direction Grid
Vector Flow Directions
Elevation Grid (Z ‐ ft)
66 55 48 45
52 43 36 37
57 54 21 30
60 46 20 15
Each cell is coded with a value corresponding to the vector direction from the flow direction compass.
Flow Direction is based on the elevation of each grid cell. Water is assumed to flow from each cell to the lowest of its eight neighbors that has the steepest descent.
Generating Surface Parameters
2 2 4 8
1 2 4 8
1 2 4
2 1 4 4
128
Flow Direction Compass
1
64128
24
8
16
32
2 2 4 8
1 2 4 8
1 2 4
2 1 4 4
Flow Direction Grid
128
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 11
Flow Direction
Generating Surface Parameters
Each of the eight directions is represented by a different color
Generating Surface Parameters
Flow Accumulation is determined from the flow direction grid.
The cell values in the Flow Accumulation Grid are the number of upstream cells which contribute to the cell. Let’s look at how this is developed.
2 2 4 8
1 2 4 8
1 2 4
2 1 4 4
128
Flow Direction Flow Accumulation
0 0 0 0
0 3 3 0
0 0 10 0
0 0 1 1262
Generating Surface Parameters
The cell values in the Flow Accumulation Grid are the number of upstream cells.
This cell has three contributing cells.
3
As a result, a flow accumulation value of “3” is coded to the cell.
2 2 4 8
1 2 4 8
1 2 4
2 1 4 4
128
Flow Direction
0
0
0
Flow Accumulation
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Generating Surface Parameters
3
0
0
0
0
0
0
10
3 0
1
0
12
2 2 4 8
1 2 4 8
1 2 4
2 1 4 4
128
Flow Direction
0
0
0
Flow Accumulation
0
0
0
The same process is completed for each cell, computing the number of upstream cells for each cell
in the GRID.
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Original Flow Accumulation
0 0 0 0
0 3 3 0
0 0 10 0
0 0 1 12
The synthetic stream patterns may be displayed by reclassifying the accumulation values to either a 0 or 1 at a user defined accumulation threshold.
For this flow accumulation grid, a threshold of 2 is used.
Values greater than 2, are replaced with 1 and values less than or equal to 2 replace with 0.
Reclass of Flow Accumulation
0 0 0 0
0 1 1 0
0 0 1 0
0 0 0 1
Generating Surface Parameters
65
Original Flow Accumulation
0 0 0 0
0 3 3 0
0 0 10 0
0 0 1 12
1 1 1 1
1 4 11 12
1 1 5 2
1 3 1 1
Reclass of Flow Accumulation
0 0 0 0
0 1 1 0
0 0 1 0
0 0 0 1
Add color to the cells with a value of “1” and the stream patterns emerge.
Generating Surface Parameters
1
1
1 1
66
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 12
The raster flow accumulation grid is converted to vector flow network
Generating Surface Parameters
1 1 1 1
1 4 11 12
1 1 5 2
1 3 1 1
Reclass of Flow Accumulation
0 0 0 0
0 1 1 0
0 0 1 0
0 0 0 1
1
1
1 1
Vector Flow Network
0 0 0 0
0 0
0 0 0
0 0 0 67
A very brief Introduction to Some Hydrologic Applications of Terrain Analysis…
Other Hydrologic Terrain Analyses
Stream Delineation
Watershed Delineation
Wetland Delineation
Erosion Modeling
Flood Analysis
Automated Stream Delineation: Is it…
Flow Accumulation ‐Stream Definition
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
Stream Vectorization
Junction
Edge
Flow Accumulation ‐Stream Definition
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 13
Flow Accumulation vs. Stream Delineation
Flow accumulation is a user specified threshold ofupstream catchment area.
‐Yellow lines > 100,000m2/m‐Red lines > 10,000 m2/m
But where does the streamchannel actually start?
Alternative Methods for Stream Delineation
Use the mean observed catchment area
Assumes catchment area is only factor
Use stream power index
Incorporate slope
Use runoff‐weighted model
Incorporate land cover and soils
Use some combination of the above
Field survey for channel formation
AutomatedWatershed Delineation…
Hydrologic Applications of Terrain Analysis
Automated Watershed Delineation
ArcHydro…
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David Maidment –ArcHydro, GIS/LIS 2000
Hydrologic Applications of Terrain Analysis –Arc Hydro
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 14
DNR Watershed Project
• Starting in 1999, we paralleled some of Dr. David R. Maidment’s ArcGIS 8.0 Hydro Model.
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DataDevelopment ‐ Distribution ‐Application
Arc Hydro
Arc Hydro A data model –Originally created in response to the need for an organized water resource data structure.
A set of tools –Aids in building Arc Hydro‐compliant datasets.
ArcHydro–Two Components
ArcHydro–Data Model
Hydrography
Network
Channel
Drainage
HydroFeatures
Based on inventory of all features for an area.
Behavioral model – trace direction of water movement across landscape.
Credit – David R. Maidment University of Texas at Austin
Developed with National Hydrogrophy Dataset (NHD) in mind.
• Tools intended to be used with NHD
Integrated raster‐vector database.
ArcHydro–Data Model
Credit – David R. Maidment University of Texas at Austin
ArcHydro ‐Tools
Set of tools used to derive end‐products
• Flow network
• Hydrologically conditioned DEM
Iterative, step‐by‐step approach with required inputs
Raster several formats, vector utilizes geodatabase only
ArcHydro ‐Tools
Set of tools used to achieve end‐products• Flow network
• Hydrologically conditioned DEM
• Catchment delineation
Iterative, step‐by‐step approach with required inputs
Raster several formats, vector utilizes geodatabase only
Credit – David R. Maidment University of Texas at Austin
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 15
ArcHydro
Pros
Semi‐automated derivation of key products
Semi‐supported
Free
Integrates data from multiple sources and of different types
Cons
Semi‐automated
Install can be difficult
User interpretation and editing introduces subjectivity
Need to know what default settings mean.
Few training resources.
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Confusion
‐What is a Watershed…
Watersheds
Sometimes confusion as to what a watershed is, especially as it relates to GIS watershed data.
Watersheds are an intangible hydrography product
You cant walk outside and point to a watershed delineation.
You can look at an aerial photograph and see a watershed delineation on the landscape.
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Watersheds
88
Confusion
‐Watershed Type…
Watersheds
89
Watersheds
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 16
Wetland Mapping…
Mapping Wetlands with LiDAR
Wetlands are frequently associated with specific topographic attributes(e.g. lower elevation than surrounding area and a relatively flat surface).
Depressionalwetland
Floodplainwetland
Hydrologic Applications of Terrain Analysis
Automated Wetland Mapping
Erosion Analysis…
Hydrologic Applications of Terrain Analysis Erosion Analysis
Credit – Adam Birr –MN Department of Agriculture
Erosion Analyses
Locate sites of likely gully and other streambankinterface erosion.
Terrain Analysis approach – Stream Power Index (SPI).
High SPI values indicate high potential overland flow.
Quantitative, spatial, repeatable.
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 17
Inundation / Storage Mapping…
Water Storage
Utilize LiDAR to accurately identify size, depth, and location of depressions in the landscape
Reduce Peak Flows
Reduce sediment and nutrients transported downstream
Water Storage
NRCS will have tools available in the future to better calculate
Rough calculation
Perform sink fill
Subtract original DEM from pit‐filled DEM to locate larger depressions
Multiple methods for determining volume
Flood Mapping…
Hydrologic Applications of Terrain Analysis
Flood Modeling & Inundation Mapping
Height‐Above‐Stream
• Calculate the least‐cost cumulative path with slope as the “cost” grid and stream centerline as the “source”
• Slope expressed as rise/run
• Result is the height above the nearest grid cell corresponding to nearest point on a stream centerline
Steep valley
Δh
Wide valley and well developed floodplain
Δh
Wider area of inundation forsame increase in water stage
LCSP: Lowest cumulative slope path
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 18
Height‐Above‐Stream Interpolating from Stream Stage
•High‐water marks surveyed with GPS•Elevation assumed equal for cross‐section•Linear interpolation between cross‐sections
Floods of September 2010 in Southern MNEllison et al. 2011.
USGS SIR 2011‐5045
AssumptionsHeight‐above stream‐ Equal height above assumed baseline gradient
Interpolated from stream stage‐ Assumed linear gradient between measurements
Working With Grids…
Working with Grids in ArcGIS
File Structure
Grid Alignment
Resampling
Aggregation
File Structure
Arc GRID files are not single files.
• Set of inter‐related files within a directory.
Use ArcCatalog to copy, move, or rename
Alternatively, you can save as *.img file
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 19
Raster Analysis Environment Settings…
Environment Settings –For Raster Processing
Geoprocessing Environment Settings can be thought of as additional parameters that affect a tool's results.
Often a prerequisite to performing Geoprocessing tasks.
110
The four environment levels form a hierarchy.
Environment settings are passed down to the next level.
At each level, the passed‐down environment settings can be overridden.
Level Hierarchy
Environment Settings –For Raster Processing
Note: All levels contain the same environment variables and have the same effect on output
results. They differ only in how you access and set them. 111
Where did my output go?…
Four levels of environment settings: 1. Application ‐ default settings that will be applied to any
tool when it is executed.
2. Tool ‐ applied to a single run of a tool and override the application level settings
3. Model ‐ specified and saved with a mode and override tool level and application level settings.
4. Model process ‐ specified at the model process level, are saved with the model, and override model level settings.
Environment Settings –For Raster Processing Environment Settings –For Raster Processing
114
All tools automatically create an output dataset name for you. ESRI has “logic” for generating the output name is as follows:
If the Current Workspace environment is specified, and the Scratch Workspace is not specified, all tools will use the Current Workspace to generate output paths.
If the Scratch Workspace environment is specified, all tools will use this path to generate output paths.
If the scratch workspace environment is not set, the current workspace environment is checked. If current workspace is set, the autogenerated output will be the current workspace.
If both the Scratch and Current Workspace environments are not specified, tools will generate an output path based on the path of the first input dataset.
If both the Scratch and Current Workspace environments are not specified and the location of the first tool input is read‐only, output will be written to the system's temp directory.
If neither the scratch or current workspace is set, the autogenerated output path will be the workspace of one of the inputs. In this case, certain restrictions apply. For example, if the workspace is a coverage workspace and the output is a new feature class, the output will be a shapefile to the directory above the coverage workspace. There are other restrictions as well, such as write access. In some cases, the output will be written to the system temp directory.
If you enter a base name for the output dataset, the current workspace will be used to construct the output path, regardless of whether the scratch workspace is set.
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 20
Environment Settings –For Raster Processing
After you've run a tool, you may find that output isn't written where you expect.
• Perhaps you made a mistake when entering the output name• Didn’t set the Workspace Environments• Or you just forgot where it was written.
Snap Raster…
Snap Raster Setting
The cells in the output raster are aligned with the cells of the snap raster.
The lower‐left corner of the extent is snapped to a cell corner of the snap raster.
The output cell size is same as the snap raster cell size.
Environment Settings –For Raster Processing
No Snap Raster Setting = No Grid Alignment
Environment Settings –For Raster Processing
Note Using raster data with different cell alignments together in the same tool causes Nearest
Neighbor Interpolation to be used to match the different cell alignments during analysis. Causes unwanted artifacts with continuous data sources and is not recommended. 118
Environment Settings –For Raster Processing
Under Processing Extent
• Set “Extent”
• Set “Snap Raster”
119
Snap Raster Setting Proper Snap Raster Setting = Grid Alignment
Environment Settings –For Raster Processing
120
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 21
Resolution / Resampling
Changing the resolution
• Upscaling – if cells evenly divisible, use AGGREGATE
• If not evenly divisible or changing the alignment, then use RESAMPLE
• You can downscale, but this does not create any new information
AGGREGATE
Increasing the cell size by aggregating groups of cells into larger cells
Based on statistical summary
sum, min, max, mean, median
RESAMPLE
Interpolation methods Nearest Neighbor Fast, maintains original values, primarily for categorical data
Bilinear or Cubic Fits data based on distance weighted functions, less geometric distortion, primarily for continuous data
LiDAR Derived DEM / Raster Display… Hill Shading…
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 22
127
HillshadeDOQ
128
HillshadeDOQ ‐ study areas
129
Hillshaded DEM ‐Obliquely simulated illumination.
130
DEM display – Elevation Grid with “Standard” color ramp draped on Hillshade
131
Hillshaded Grid
The Basics of Hill Shading…
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 23
The azimuth is the angular direction of the sun.
Measured from north in clockwise degrees from 0 to 360.
The altitude is the slope or angle of the illumination source above the horizon.
Degrees, from 0 (on the horizon) to 90 (overhead).
DisplayingElevation by Hill Shading
The ESRI default hill shade has an azimuth of 315 and an altitude of 45 degrees.
DisplayingElevation by Hill Shading
DisplayingElevation by Hill Shading
By default, shadow and light are shades of gray associated with integers from 0 to 255 (increasing from black to white).
The Azimuth and Angle change with the season thus the cast shadows do as well. Should we
model that? 136
Default Hillshaded DEM
Hillshade: Azimuth = 315 - Altitude = 45
Hillshade: Azimuth = 315 - Altitude = 70
137
Hillshade: Azimuth = 315 - Altitude = 80
138
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 24
Hillshade: Azimuth = 90 - Altitude = 45
139
Hillshade: Azimuth = 180 - Altitude = 45
140
Hillshade: Azimuth 360 - Altitude = 45
141
Hill Shading Methods…
DisplayingElevation by Hill Shading
There are 3 methods to Hill Shade a DEM . Hill Shading Method #1…
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 25
1. Rendering the DEM with Data Frame Illumination
ArcMap and its associated Extensions compute hillshade values for raster surfaces by considering the illumination angle and shadows.
Hill Shading Method #2…
2. Image Analysis Window
Supports the analysis and exploitation of image and raster data.
Allows you to interactively adjust
• Brightness ( )• Contrast ( )• Gamma ( ) • Transparently ( )
Enhancements are applied to the rendered screen display, not to the original raster dataset values.
147
Hill Shading Method #3…
3. Using Spatial Analyst & 3D Analyst to Create the Hillshade.
149
Rendering the DEM with Layer Properties Different stretches will produce different results in the raster
display. A stretch increases the visual contrast of the raster display. You can experiment to find the best stretch for a particular raster
dataset.
150
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 26
Rendering the DEM with Layer Properties
Gamma The degree of contrast between the
midlevel gray values. Low gamma coefficient darkens the
middle tones. High gamma coefficient lightens the
DEM. If the gamma coefficient is set too high, middle tones appear too light, can look bleached out.
Does not affect the black or white values in a raster dataset, only the middle values.
Gamma controls the overall brightness of a raster dataset.
151 152
Hillshaded DEM
Problems with Hillshading…
Problems with Raster Hill Shading Highlights features at right angles to the
hypothetical light source.
Landscape features can be lost in the Cast Shadows.
Bottoms of low relief features such as ditches can be distorted.
Visual interpretation of the distortion can lead to vertex coordinate shift from actual feature delineation and digitization.
154
Ground/Topography
Displaying Slope with Hillshading…
156
Slope
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 27
157
Slope on Hillshade
Drape the Hillshade on a DOQ…
159
Hillshade raster draped on DOQ exhibits the uniqueness of each product.
DEM / Raster Display
– Hydrography Identification…
Problems with Raster Hill Shading
An exploration of techniques to exploit hydrography.
Visual
Derived outputs
Color symbology
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Visually appealing symbology of LiDAR derived DEMs.
Allows for effective visual interpretation of water conveyance features in regions of low topographic relief .
Simple/Easy grid hillshade technique that adds visual complexity in place of obliquely simulated illumination.
Hydrography Identification ‐A personal Mission ‐
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 28
When hillshading, the purpose of the map should be paramount.
This objective is to emphasize the terrain to identify the water conveyance features.
Use techniques that bring out details in the landscape.
The terrain representation should also take into consideration the unique characteristics of the area mapped.
Relief and orientation of physiographic features.Development of a PreferredColor Scheme…
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DEM display – “Fire” on Hillshade
Taking Raster Display Further…
Realized goal ‐ to tightly define the side banks and bottoms of watercourses, depressions and swales on the landscape.
Purposes of digitizing water conveyance features at a scale of 1:2,000 ‐ 1:4,000.
Least distortion from elevation stretching
Without Exaggeration
Minimize sunlit side slopes and shadowing effects.
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DNR Watershed Project
The intent of this process was to find a visually appealing symbology of LiDAR derived DEMs that allows for effective visual interpretation of water conveyance features in regions of low topographic relief with simple grid/hillshade techniques that add visual complexity to obliquely simulated illumination.
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Topographic Position Index…
The main objective of my R & D exercise was to classify landforms within a watershed to identify and extract local geomorphometric properties of 3m resolution DEMs.
Bring out the relief of features that might bemasked by a single source of illumination.
rise
Run 170
Topographic Position Index (TPI)
TPI is the difference between a cell’s elevation value and the average elevation of the neighborhood around that cell.
Positive values mean the cell is higher than its surroundings while
Negative values mean it is lower.
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Topographic Position Index (TPI)
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TPI Raster ‐This display simulates an areal perspective that makes the higher elevations lighter and the lower elevations darker.
TPI Availability…
Topographic Position Index (TPI)
Andrew Weiss, 2001 ESRI International User Conference
Jeff Jenness , Wildlife Biologist, GIS Analyst, Jenness Enterprises.
He wrote the code in Avenue for ArcView 3.3. Available for ArcGIS 10 at: http://corridordesign.org/
Thomas Dilts , Research Scientist, University of Nevada, Reno.
Migrated the TPI functionality to an ArcGIS toolbox. Available for ArcGIS 9.x at:
http://arcscripts.esri.com/details.asp?dbid=15996
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Hydrologic Applications (Conservation Applications of LiDAR) March 2012 30
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TPI Reclass Grid
Topographic Position Index (TPI)
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TPI Grid the using the “Fire” Display Settings
Topographic Position Index (TPI)
Swiss Method…
Swiss Method –Bring It All Together
The Swiss method creates rasters from the input DEM through raster calculation.
The source DEM and the derived rasters are used together in the final display in a “stacked” format with viable transparency .
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Complex image of stacked rasters.
Interpretation of subtle signatures (dark linear features) of water conveyance features for watercourse delineation and hilltops (light regions) for watershed delineation.
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DNR Watershed Project
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 31
Exercise Logistics…
Organize your Map View.
Please keep ArcMap windows docked to the left and use as Tabs for access.
Root Folder for this exercise :
%root folder%\ = %Flash_Drive%\_sevaughn_LiDAR\DEM_ CONDITIONING
Running this exercise off a flash drive curtails our ability to map drives/Connect To Folders because flash drives can contain different names and are assigned random drive letters.
At this time Use the Connect To Folder at this time to map a drive to the Flash Drive.
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 32
Flow accumulation
Stream thresholds
Watershed delineation
Topographic depressions (sinks)
Topography –
Mapping the Minimum Relief Landscapes of Minnesota …
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LiDAR Derived DEMs Roads represent the highest elevations.Roads and other features create “digital dams”. What are “Digital Dams”…
Elevation Data Sources – LiDAR Bare Earth
LiDAR captures height of land features (roads, dams, bridges) without regard to pass through conveyance of hydrography.
Creates Digital Dams
Digital Dams
Water does not “flow” within the DEM.
Most common problems with DEMs.
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Hydrologic Applications (Conservation Applications of LiDAR) March 2012 33
A Close‐up Look at Digital Dams…
Hydrologically Conditioning Digital Elevation Data to Remove Digital Dams…
Tomorrow’s Data / Yesterday’s MethodsTomorrow’s Data / Yesterday’s Knowledge
Sinks…
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 34
Breaching Digital Dams (Sinks)
Without correction, digital dams, such as roads,will lead to very large “sinks” being filled, potentially leading to large errors.
Arcs digitized across thedigital dam can be used tocreate a breach.
Breaching Digital Dams (Sinks)
A Classic Blunder• Burning less accurate data into the DEM in a wholesale manner• May work for some apps, but will wreck others • Rule‐of‐Thumb: Change the DEM as little as possible
Topographic Depressions (Sinks)
Spurious sinks Some interpolations create spurious sinks.
Spurious sinks ought to be removed.
True sinks Some landscapes have natural depressions.
True sinks may be retained or removed.
Two removal methods Raise the elevation of sink to the elevation of sink outlet (filling).
Breach topographic barriers (burning).
Filling Sinks
DEM with unfilled sinks DEM with filled sinks Depth of sink
A Classic Blunder• Many documents suggest that you should fill all sinks. • Sinks that aren’t removed will not contribute to downstream flow.• If doing a watershed delineation, it may look like Swiss cheese.• However, if you’re not careful . . .
Some Comments about Sinks & Watersheds…
Sinks: Potential Water Storage
Image shows a difference grid between the filled and unfilled DEM. True sinks are natural water storage areas. False sinks, like these, are potential water storage areas.
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 35
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The answer to these questions is an issue of scale.
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Watersheds
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LiDAR derived DEM
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Flow Network from LiDAR derived DEM
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Concentrations of Flow Networks outside of lake and wetland areas indicate problems with the DEM.
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 36
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LiDAR derived DEM
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Flow Network from LiDAR derived DEM
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Re‐interpolated LiDAR derived DEM using Topo to Raster.
Red = New Flow Network.
Blue = Drainage Enforcement Stream Arcs (breaches).
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Concentrations of Flow Networks outside of lake and wetland areas indicate problems with the DEM.
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Hillshade of Original DEM
Hillshade of FilledOriginal Elevation DEM
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 37
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Outlet of this ditch system moves after the “filling” process.
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Re‐interpolated LiDAR derived DEM = Hydrologically Corrected DEM.
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Solutions…
DEM Correction Methods…
DEM Correction Methods
Breaklines Grid Subtraction Agree ANUDEM
Breaklines ‐Correction Method 1…
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 38
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Breaklines are vector features (lines, polygons) that are created to enhance a topographic data product and improve both accuracy and cartographic quality.
Breaklines
We used to call them Hydro Connectors or Arbitrary Arc Flow Connectors.
Slope Breaklines Hydrographic
Breaklines Transportation
Breaklines Hydrologic Structures
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Data courtesy of Merrick & Company.
Vendor Estimated time to complete breakline vector work:• 3 hours per section/ mile.• 40 step process.
Processing time:1.5 – 2 hours per section/mile
All features in color on this hillshade are vector breaklines.
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Low/Poor Resolution DEMsWe incorporated all of those inputs to overcome deficiencies in the 30m DEMs.
High Resolution LiDAR derived high resolution DEMs requires many of the same inputs.
AGREE ‐Correction Method 2…
AGREE Method
RASTER SUBTRACT
AGREE method to “burn‐in” streams
Adjusts elevation of DEM based on input vector line features
Lowers the elevation of the cells corresponding to the lines an specified amount specified by analyst
Creates a smooth transition in a buffer zone
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Lateral Distance (m)
Eleva
tion (m
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Original Surface
Modified Surface
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 39
ANUDEM ‐Correction Method 3…
ANUDEM
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• ANUDEM imbeds vector stream and lake data into elevation data to produce an improved "Hydrologically Corrected" DEM which is better suited for hydrologic modeling using GIS technology.
ANUDEM (Topo to Raster)
Developed by M.F. Hutchinson at Australian National University (ANU)
MN DNR Waters used to create Hydrologically Corrected DEMs to aid in watershed delineation.
Differences from AGREE
• More conservative
• Requires directionality
http://cres.anu.edu.au/outputs/anudem.php
ANUDEM
• A Catchment with Streams
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ANUDEM
• The flat areas in this shaded elevation model are wetlands and lakes.
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ANUDEM
• ANUDEM uses stream data (breaches) to enforce drainage.
• Stream data must have correct directionality and connectivity.
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Hydrologic Applications (Conservation Applications of LiDAR) March 2012 40
ANUDEM
• The streams have been incorporated into the DEM
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ANUDEM
• Hydrologically Corrected DEM
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ANUDEM
• Hydrologically Corrected DEM with streams and watershed boundaries
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ANUDEM
• A catchment with streams
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Hydrologic Applications (Conservation Applications of LiDAR) March 2012 41
How you process your data is project‐scope and project‐scale dependant.
LiDAR derived DEMs are absolutely beautiful but they are not an absolute representation of the topography, close but not absolutely perfect.
Breaklines
How you process your data is project‐scope and project‐scale dependant
Hydrologic Reality Check
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Understand the data you are working with. GIS analysis
• Junk In = Junk Out • LiDAR In with “digital dams” = Junk Out• Feeding it into a model doesn’t fix the problem.
Products such as Flow Networks and Watersheds need to represent the hydrology of the landscape.
Take Home Messages
Do assess the validity of assumptions
Do set environment variables
Don’t interpolate from interpolated data
Don’t blindly fill in all sinks
Don’t burn in less accurate stream data
Do understand your data
Do check your results
Resources
http://www.mngeo.state.mn.us/chouse/elevation/lidar.html
http://lidar.cr.usgs.gov/
http://wrc.umn.edu/randpe/agandwq/tsp/lidar/
ftp://lidar.dnr.state.mn.us/data/
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 42
END
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END
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250ArcHydro…
DNR Watershed ProjectDavid Maidment –ArcHydro, GIS/LIS 2000
DNR Watershed Project
• Starting in 1999, we paralleled some of Dr. David R. Maidment’s ArcGIS 8.0 Hydro Model.
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Hydrologic Applications (Conservation Applications of LiDAR) March 2012 43
Mapping Wetlands with LiDAR
Wetlands are frequently associated with specific topographic attributes(e.g. lower elevation than surrounding area and a relatively flat surface).
Depressionalwetland
Floodplainwetland
Wetland Landforms
Many wetlands are sinks, but
Not all wetlands are sinks, and
Not all sinks are wetlands
Landforms
Basin
Floodplain
Fringe/Island
Flat
Slope
Non‐Wetland Sinks (Mostly)
Wetness Index (CTI)
as = upslope drainage area divided by the width of grid cell (orthogonal to flow)
In practice, as = number of upstream grid cells * cell width
β = slope°
Specific catchment area a [m2/m m] (per unit contour length)
tan
Steady‐State Water Table Depth
Mean depth to water table
Rate of decline of sat. hydraulic conductivity with depth
Specific catchment area (m2/m)
Slope°
Mean watershed value of wetness index
Shaman et al. 2003, Water Resources Research, 38:8
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 44
Define Saturated Areas from CTI
Options
User Selected Threshold
Logistic Regression
CART
Erosion Modeling
• Universal Soil Loss Equation
Wischmeier and Smith 1978
Topographic factor
A = average long‐term soil loss
R = rainfall‐runoff factor
K = soil erodibility factor
LS = slope length‐gradient factor (ratio of soil loss compared to standard slope)
C = crop/vegetation factor
P = management practice factor
Erosion Modeling
Stream Power Index
Moore and Nieber 1989
Sediment Transport Capacity Index
Working from the general form of sediment transport equation, Moore and Wilson (1992) showed:
For λ < 100m and β < 14 degrees, use m = 0.6 and n = 1.3
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 45
Revised USLE
RUSLE
Changed LS factor to follow Moore & Wilson (1992)
Better accounts for effect of curvature
Mitasova et al. 1998. Multidimensional soilerosion/deposition modeling and visualizationusing GIS
Limitations for Stream Power Index
Doesn’t really work for stream bank erosion Stream width > grid cell width
Erosion mechanism is different
Advanced H&H Modeling
Flood map as output
HEC‐HMS(flow)
Geo‐Database
PrecipitationLand coverSoilsTopographyWatershedsStreams
Cross‐section profiles HEC‐RAS
(flood elevation)
TopographyFlood Elevation
GISEngineering Models
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 46
Logistics…
ArcHydro–Two Components
Hydrologic
Data Model
Toolset
Credit – David R. Maidment University of Texas at Austin