|Title||LiDAR Elevation, Southeast Minnesota, 2008|
|Abstract||This high accuracy, bare-earth processed LiDAR data includes one-meter resolution DEMs, two-foot contours, edge-of-water breaklines and LAS points for nine counties in Southeast Minnesota: Dodge, Fillmore, Freeborn, Houston, Mower, Olmsted, Steele, Wabasha, and Winona. The project was coordinated by the Minnesota Department of Natural Resources and several partners including the U.S. Geological Survey, the Minnesota Department of Transportation, and staff from the affected counties.
The data was collected by AeroMetric, Inc. in November 2008 and was delivered in tiles that covered an area 1/16th of a 1:24,000-scale USGS quadrangle (approximately 3.25 square miles). DNR conducted the QA/QC starting April 2009. As part of the processing, one- and three-meter county mosaic DEMs were created and used for visual quality assessment.
Note: This metadata record was created at the Minnesota Geospatial Information Office by combining information supplied by AeroMetric and the DNR.
|Purpose||The Southeast Minnesota LiDAR project's goal was to provide high accuracy, bare-earth processed LiDAR data suitable for the FEMA National Flood Insurance Program. In August 2007, the nine counties had experienced a major rainfall event with over 10 inches of rain that caused extensive flooding. The Minnesota Legislature appropriated money to aid in flood relief and to provide mitigation against future floods including the acquisition of high-resolution elevation data using LiDAR technology.|
|Time Period of Content Date||2008|
|Currentness Reference||Data was acquired between November 18 - 24, 2008.|
|Maintenance and Update Frequency||Unknown|
|Spatial Extent of Data||Nine counties in southeastern Minnesota: Dodge, Fillmore, Freeborn, Houston, Mower, Olmsted, Steele, Wabasha, and Winona.|
|Place Keywords||Southeastern Minnesota, Dodge, Fillmore, Freeborn, Houston, Mower, Olmsted, Steele, Wabasha, Winona|
|Theme Keywords||elevation, LiDAR, DEM, digital elevation model, contour, topographic, topo, DTM, LAS, breakline|
|Theme Keyword Thesaurus||ISO 19115|
|Use Constraints||In obtaining this data from MnGeo, it is understood that you and/or your organization have the right to use it for any purpose. If you modify it, you are encouraged to apply responsible best practices by documenting those changes in a metadata record. If you transmit or provide the data to another user, it is your responsibility to provide appropriate content, limitation, warranty and liability information as you see fit.|
|Contact Person Information||Tim Loesch,
GIS Operations Supervisor|
MN Department of Natural Resources
500 Lafayette Road
St. Paul, MN 55155
|Browse Graphic||None available|
|Associated Data Sets||For more information about elevation data for Minnesota, see: www.mngeo.state.mn.us/chouse/elevation/index.html|
|Section 2||Data Quality|
|Attribute Accuracy||See the Vertical Positional Accuracy field|
|Logical Consistency||Contours: Topology checks were done to look for dangles, crossing and intersecting contours, as well as other anomalies. All errors were fixed and a second topology check was done to verify an error free dataset.|
|Horizontal Positional Accuracy||All these data products were acquired at 2400 meters above mean terrain (AMT) and have a horizontal accuracy of 0.40 meters, with a nominal point spacing of 1.0 meters.|
|Vertical Positional Accuracy||1. AeroMetric's Tests:
The Fundamental Vertical Accuracy (FVA) of the TIN achieved 0.161 meters at a 95% confidence level in the 'Open Terrain' land cover category. 26 control points were used in this evaluation.
The Consolidated Vertical Accuracy (CVA) of the TIN achieved 0.36 meters at a 95% confidence level according to ASPRS Guidelines, Vertical Accuracy Reporting for LiDAR for all land cover categories. 127 points covering 5 land cover categories were tested. Land Cover categories are the following: Open Terrain, Tall Weeds and crops, Brush lands and low trees, Forested areas fully covered by trees, and Urban areas with dense man-made structures.
Supplemental Vertical Accuracy (SVA) of the TIN are shown below at a 95% confidence level, derived by the ASPRS Guidelines, Vertical Accuracy Report for LiDAR Data based on the 95th percentile error in all of the individual land cover categories. Below are the land cover categories with the achieved accuracy reported at a 95th percentile error and the number of test points:
Open Terrain: 0.144m, 26
Tall Weeds and crops: 0.240m, 23
Brush lands and low trees: 0.248m, 22
Forested areas fully covered by trees: 0.165m, 22
Urban areas with dense man-made structures: 0.216m, 34
2. MnDNR's Tests:
Accuracy of the dataset was verified by a second set of ground control points provided and tested by MnDNR. The Consolidated Vertical Accuracy (CVA) of the TIN as tested by MnDNR achieved 0.287 meters at a 95% confidence level of all land cover categories. 1009 control points covering the 5 land classes were used in this evaluation. The vertical RMSE and sample count per county as tested by MnDNR is as follows: Dodge 0.129m, 121; Fillmore 0.155m, 128; Houston 0.110m, 134; Mower 0.161m, 115; Olmsted 0.117m, 125; Steele 0.125m, 137; Wabasha 0.106m, 97; Winona 0.161m, 176.
|Lineage||The LiDAR data was captured using fixed wing aircraft equipped with LiDAR systems. The LiDAR system included a differential GPS unit and inertial measurement system to provide superior accuracy. Both AeroMetric, Inc. and Surdex Corporation acquired LiDAR data over the project area. Surdex's data was post-processed to a raw point cloud by Surdex and then delivered to AeroMetric to be merged into one raw point cloud dataset.
1. Scanners - Optech ALTM Gemini (AeroMetric) and Leica ALS50-2 (Surdex)
2. Flight Height - 2400 meters above mean terrain
3. Swath Width - 32 degrees
4. Sidelap - 60%
5. Nominal Post Spacing - 1.0 meter
GPS and IMU processing parameters:
1. Processing Programs - AeroMetric= Applanix - POSGPS and POSProc; Surdex= GravNav GNSS and Leica IPAS
2. Maximum baseline length - Not greater than 30km.
3. Number of base stations during LiDAR collection - A minimum of 2 MnDOT CORS stations were occupied during any of the lifts to acquire the LiDAR data. The following were the occupied base stations: BLUE, CLDN, DDGC, ELKT, EYTA, LCHI, LCRS, NALB, PRSP, REDW, RSHF, STWV, TWNL, WBSH, WINO, and WSCA.
4. GPS and IMU processing monitored for consistency and smoothness - Yes.
Point Cloud Processing:
1. Program - AeroMetric= Optech Dashmap; Surdex= Leica ALS Post Processor
2. Horizontal Datum - NAD83(2007)
3. Horizontal Coordinates - UTM, Zone 15, in meters
4. Vertical Datum - NAVD88
5. Geoid Model used to reduce satellite derived elevations to orthometric heights - NGS Geoid03.
1. Processing Programs and versions - TerraSolid TerraScan (version 009.010), TerraModeler (version 009.002) and TerraMatch (version 009.003) and Intergraph MicroStation (version.08.01.02.15).
2. Point Cloud data was imported to TerraScan in a Microstation V8 (V) CAD environment.
3. The data is projected to the horizontal project coordinate system of UTM - Zone 15 in meters.
4. Analyzed the data for overall completeness and consistency. This was to ensure that there are no voids in the data collection.
5. Inspected for calibration errors in the dataset using the TerraMatch software. This was accomplished by sampling the data collected across all flight lines and classifying the individual lines to ground. The software used the ground-classified lines to compute corrections (Heading, Pitch, Roll, and Scale).
6. Orientation corrections (i.e., calibration corrections) were then applied to the entire dataset.
7. Automatic ground classification was performed using algorithms with customized parameters to best fit the project area. Several areas of varying relief and planimetric features were inspected to verify the final ground surface.
8. AeroMetric provided Quality Assurance and Quality Control (QA/QC) data for this project. AeroMetric captured 127 QA/QC points in multiple land cover categories that were used to test the accuracy of the LiDAR ground surface. TerraScan's Output Control Report (OCR) was used to compare the QA/QC data to the LIDAR data. This routine searches the LIDAR dataset by X and Y coordinate, finds the closest LIDAR point and compares the vertical (Z) values to the known data collected in the field. Based on the QA/QC data, a bias adjustment was determined, and the results were applied to the LIDAR data. A final OCR was performed with a resulting RMSE of 0.109 meters.
9. Once the automatic processing and the testing of LiDAR was complete, AeroMetric meticulously reviewed the generated bare-earth surface data to insure that proper classification was achieved as part of a Quality Control process.
10. Final deliverables were generated and cut out according to the MnDNR tiling and naming scheme (1/16 USGS 7.5 minute quadrangles).
1. The final geodatabase for each of the 1544 tiles (1/16 USGS 7.5 minute quadrangles) was created using ESRI ArcInfo software.
2. Each MicroStation contour file was converted into shapefile format. The contours were created using only the keypoint point features from the LAS data files.
3. The shapefile was inserted into the geodatabase as a feature class named 'Contours' inside the defined feature dataset 'Contour_Data'.
4. Topology checks were done to look for dangles, crossing and intersecting contours, as well as other anomalies. All errors were fixed and a second topology check was done to verify an error free dataset.
5. The contour features have two attributes, 'Contour_Type', which identifies the contour type (index, intermediate, depression, and depression_index) and 'ELEVATION' which indicates the contour elevation in U.S. feet.
6. The BareEarth data within the LAS point files was imported into a feature class named 'Bare_Earth_Points' inside the defined feature dataset 'Terrain_Data'. The points were created as multipoint features which group the LAS points into blocks of data in order to reduce the number of records in the geodatabase.
7. The breaklines were imported as polylines into a feature class named 'Hydro_Breaklines' inside the defined feature dataset 'Terrain_Data'.
8. The 1.0 meter DEM data was imported as raster points into the defined feature dataset 'DEM01'. Each point in the DEM file became a pixel with an assigned elevation in meters.
1. One paper copy of the LiDAR Accuracy Assessment Report.
2. One firewire hard drive containing the following data:
a. Point Cloud Data in LAS 1.1 format for each of the 1544 tiles (1/16 USGS 7.5 minute quadrangles). x=Easting (0.01 resolution), y=Northing (0.01 resolution), z=Elevation (0.01 resolution), i=Intensity (0.1 resolution) LAS data classified using the following codes: 0, 2, 5, 6, 8, 9, 10, 12 according to ASPRS LAS format classification table. Units in meters.
b. Geodatabase files for each of the 1544 tiles (1/16 USGS 7.5 minute quadrangles) including the following feature classes:
i. Bare_Earth_Points - LAS Point Cloud Data
ii. Hydro_Breaklines - Water/shoreline breakline data
iii. Hydro_Breaklines - Enhanced breakline data included, but was not limited to, retaining walls, road edges, ridge lines, dams for Project Area B only.
iv. DEM01 - Bare-Earth DEM raster at 1.0 meter resolution per tile. Vertical units in meters at 0.01 meter resolution.
v. Contours - Vector contours at 2 foot intervals represented in U.S. feet vertically and meters horizontally.
3. FGDC Compliant metadata for the Point Cloud Data LAS delivery.
4. FGDC Compliant metadata for the Geodatabase delivery.
MnDNR reviewed the deliverables for content and accuracy. Any needed corrections to the content of the dataset were addressed and corrected by AeroMetric and redelivered.
MnDNR created the 3-meter DEM using the following method:
- Step 1: Mosaic all the tiles that make up the county into a file geodatabase.
- Step 2: The 1-meter grid is then "filled" to fill in any NO DATA cells that have data around them. This is common when grid tiles are merged. The commmand that was used is the focalmean tool within the con tool in the Spatial Analyst | Map Algebra tool. The equation used is: con(isnull(dem01),focalmean dem01,rectangle,3,3,data),dem01). The DEM01 grid is then deleted and replaced with the output from this step.
- Step 3: The filled raster is then reduced to 3-meter resolution using the Spatial Analyst, Aggregate Tool. A 3x3 window of 1-meter cells are combined into one 3x3 meter cell and assigned a value based on the mean of the 9 cells.
|Section 3||Spatial Data Organization (not used in this metadata)|
|Section 4||Coordinate System|
|Horizontal Coordinate Scheme||Universal Transverse Mercator|
|UTM Zone Number||15|
|Overview||The LAS files have points that are classified using the following categories:
2 - Ground
5 - Vegetation
6 - Building
8 - Model Keypoint (points required to maintain surface integrity)
9 - Water
10 - Bridge Decks
12 - Overlap Points
The contour features have two attributes:
Contour_Type: Index, intermediate, depression, and depression_index
Elevation: Contour elevation in U.S. feet
All of the DEMs are floating point rasters with Z-Values in meters.
Note that the point file is comprised of multi-point features. What this means is that there are likely 3000 - 5000 points included in each of the records in the table. Using the interactive select tool to select one point actually selects one record and all of the points associated with this record. Doing an Identify on the points will not list a Z value because it does not exist as an attribute in the table, rather it's a property of the point. It also means labels cannot be listed on the points.
|Publisher||Minnesota Department of Natural Resources|
|Contact Person Information||Nancy Rader,
GIS Data Coordinator|
Minnesota Geospatial Information Office
658 Cedar Street
St. Paul, MN 55155
|Distributor's Data Set Identifier||SE MN LiDAR 2008|
|Distribution Liability||Minnesota Department of Natural Resources General Geographic Data License Agreement
1) The Minnesota Department of Natural Resources (MNDNR) grants to you a non-exclusive, non-sublicensable, license to use these digital data. This License agreement applies to all digital data acquired from DNR staff, FTP sites, or other internet-based delivery systems. In the event that another license agreement issued by DNR staff is explicitly associated with a particular data set, the terms of the other license agreement prevail, and the terms expressed in this more general license agreement are nullified.
2) The MNDNR makes no representations about the suitability of these data for any purpose. The data are provided 'as is' without express or implied warranties, including warranties of merchantability and fitness for a particular purpose or non-infringement.
3) MNDNR is not obligated to provide updates to these data in the event that newer versions become available. MNDNR provides documentation when available through established distribution mechanisms.
4) The user relieves the MNDNR and its respective officers, agents, and employees of any liability for any and all damages resulting from use of mis-use of these data including, but not limited to:
a. Incidental, consequential, special or indirect damages of any sort, whether arising in tort, contract or otherwise, even if MNDNR has been informed of the possibility of such damages, or
b. For any claim by any other party. Furthermore, in States that do not allow the exclusion of limitation of incidental or consequential damages, you may not use these data.
5) When these data are used in the development of digital or analog (hardcopy) products, MNDNR must be acknowledged as having contributed data to the development of the product.
6) Although the use of these data are not restricted, they may not be sold commercially or privately without the written permission of MNDNR.
MnGeo's data disclaimer is online: www.mngeo.state.mn.us/chouse/disclaimer.html
|Ordering Instructions||The LiDAR data provided by DNR may be downloaded from MnGeo's FTP site by clicking on the link below.
elevation_data.gdb - File Geodatabase (Version 9.3) containing mosaiced 3-Meter DEMs and Breaklines
DEM01 - one meter DEM
DEM03 - three meter DEM
DEM03HS - Hillshade of DEM03
HYDRO_BREAKLINES - Hydro and some Road Breaklines
TILE_INDEX - a tile index with a field called TILE_NAME which identifies all of the tiles.
VALIDATION_POINTS - a feature class of the points used in the vertical accuracy assessment
qaqc_table - a table summarizing all of the tiles and various attributes about them - used for QA/QC purposes.
For more help with Minnesota's LiDAR data, see www.mngeo.state.mn.us/chouse/elevation/lidar.html
|Online Linkage||I AGREE to the notice in "Distribution Liability" above. Clicking to agree will either begin the download process or link to download information. See "Ordering Instructions" above for details.|
|Section 7||Metadata Reference|
|Contact Person Information||Nancy Rader,
GIS Data Coordinator|
Minnesota Geospatial Information Office
658 Cedar Street
St. Paul, MN 55155
|Metadata Standard Name||Minnesota Geographic Metadata Guidelines|
|Metadata Standard Version||1.2|
|Metadata Standard Online Linkage||http://www.mngeo.state.mn.us/committee/standards/mgmg/metadata.htm|