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 Vaughn GIS Hydrologist Minnesota Department of Natural Resources Conservation Applications of LiDAR Data 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 LiDAR Data 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
46
Embed
Hydrologic Applications (Conservation Applications of LiDAR ...
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
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)
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 .
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.
• 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
43
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?
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
67 56 49
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
67 56 49
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
67 56 49
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
63
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.
64
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.
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
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
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 ‐
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…
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
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.
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 29
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.
171
Topographic Position Index (TPI)
172
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
174
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 30
175
TPI Reclass Grid
Topographic Position Index (TPI)
176
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 .
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.
180
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.
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 …
189
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.
192
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
205 206
The answer to these questions is an issue of scale.
207
Watersheds
208
LiDAR derived DEM
209
Flow Network from LiDAR derived DEM
210
Concentrations of Flow Networks outside of lake and wetland areas indicate problems with the DEM.
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 36
211
LiDAR derived DEM
212
Flow Network from LiDAR derived DEM
213
Re‐interpolated LiDAR derived DEM using Topo to Raster.
Red = New Flow Network.
Blue = Drainage Enforcement Stream Arcs (breaches).
214
Concentrations of Flow Networks outside of lake and wetland areas indicate problems with the DEM.
215 216
Hillshade of Original DEM
Hillshade of FilledOriginal Elevation DEM
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 37
217
Outlet of this ditch system moves after the “filling” process.
218
Re‐interpolated LiDAR derived DEM = Hydrologically Corrected DEM.
219
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
223
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
224
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.
225 226
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
30
40
50
60
70
80
90
100
0 20
40
60
80 100
120
140
160
180
200
220
240
260
Lateral Distance (m)
Eleva
tion (m
)
Original Surface
Modified Surface
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 39
ANUDEM ‐Correction Method 3…
ANUDEM
230
• 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
232
ANUDEM
• The flat areas in this shaded elevation model are wetlands and lakes.
233
ANUDEM
• ANUDEM uses stream data (breaches) to enforce drainage.
• Stream data must have correct directionality and connectivity.
234
Hydrologic Applications (Conservation Applications of LiDAR) March 2012 40
ANUDEM
• The streams have been incorporated into the DEM
235
ANUDEM
• Hydrologically Corrected DEM
236
ANUDEM
• Hydrologically Corrected DEM with streams and watershed boundaries
237
ANUDEM
• A catchment with streams
238
239
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
243
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.