hydrologic applications (conservation applications of lidar

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


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


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


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


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.

15

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 .


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


Manual Interpretation

Manual Illustration

25

One dimensional ‐ Planar view ‐Manual ‐GIS

1992

Field Inspection ‐Groundtruthing

Depressions & Impressions

Drainage Discoveries

26

Field Inspection –Aerial Review

Oblique photos indicate linear signatures of ditching.

GIS – Innovation

GIS Brings it all together

Raster

Vector

Landscape

28

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


Elevation Data Sources –LiDAR

Laser reflectance measurement

6‐in vertical accuracy

Spacing can be as little as 2‐feet apart

$150 ‐ $250 / sq. mile

32

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


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.

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53 44 37

58 55 22

Digital

Graphical


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.


DEM Resolution…


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.

44

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?


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

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16

8

64

4

128

1

2


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


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.


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.


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


Flow Direction


Each of the eight directions is represented by a different color


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


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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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


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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


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.


1

1

1 1

66


The raster flow accumulation grid is converted to vector flow network


1 1 1 1

1 4 11 12

1 1 5 2

1 3 1 1


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


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…


Automated Watershed Delineation

ArcHydro…

78

David Maidment –ArcHydro, GIS/LIS 2000

Hydrologic Applications of Terrain Analysis –Arc Hydro


DNR Watershed Project

• Starting in 1999, we paralleled some of Dr. David R. Maidment’s ArcGIS 8.0 Hydro Model.

79 80

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


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



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.

86

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.

87

Watersheds

88

Confusion

‐Watershed Type…

Watersheds

89

Watersheds


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


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.


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…


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


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


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


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.



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.


No Snap Raster Setting = No Grid Alignment


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


Under Processing Extent

• Set “Extent”

• Set “Snap Raster”

119

Snap Raster Setting Proper Snap Raster Setting = Grid Alignment


120


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…


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…


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.



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


137


138



139


140

Hillshade: Azimuth 360 - Altitude = 45

141

Hill Shading Methods…


There are 3 methods to Hill Shade a DEM . Hill Shading Method #1…


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


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


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

161 162

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 ‐


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…

165

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.

167 168


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.


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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TPI Raster ‐This display simulates an areal perspective that makes the higher elevations lighter and the lower elevations darker.

TPI Availability…


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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175

TPI Reclass Grid


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TPI Grid the using the “Fire” Display Settings


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 .

178

179

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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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.


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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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…


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.


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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.


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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


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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…


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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)

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Original Surface

Modified Surface


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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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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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/


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250ArcHydro…

DNR Watershed ProjectDavid Maidment –ArcHydro, GIS/LIS 2000


• Starting in 1999, we paralleled some of Dr. David R. Maidment’s ArcGIS 8.0 Hydro Model.

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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)

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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


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


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


Logistics…

ArcHydro–Two Components

Hydrologic

Data Model

Toolset


hydrologic applications (conservation applications of lidar

Documents