20101104 20241200 FALSE ProjectRaster "Database Connections\sq50wpchc_CNTYRASTER_os.sde\cntyraster.GISADMIN.LIDAR_2010_DEM5ft" "Database Connections\sql60wpchc_CNTYRASTER_DA_Admin.sde\CNTYRASTER.GISADMIN.DEM_LIDAR_2010_5FT" PROJCS['NAD_1983_HARN_StatePlane_Wisconsin_South_FIPS_4803_Feet',GEOGCS['GCS_North_American_1983_HARN',DATUM['D_North_American_1983_HARN',SPHEROID['GRS_1980',6378137.0,298.257222101]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]],PROJECTION['Lambert_Conformal_Conic'],PARAMETER['False_Easting',1968500.0],PARAMETER['False_Northing',0.0],PARAMETER['Central_Meridian',-90.0],PARAMETER['Standard_Parallel_1',42.73333333333333],PARAMETER['Standard_Parallel_2',44.06666666666667],PARAMETER['Latitude_Of_Origin',42.0],UNIT['Foot_US',0.3048006096012192]] NEAREST "5 5" 'NAD_1927_To_NAD_1983_NADCON + NAD_1983_To_HARN_Wisconsin' # PROJCS['NAD_1927_StatePlane_Wisconsin_South_FIPS_4803',GEOGCS['GCS_North_American_1927',DATUM['D_North_American_1927',SPHEROID['Clarke_1866',6378206.4,294.9786982]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]],PROJECTION['Lambert_Conformal_Conic'],PARAMETER['False_Easting',2000000.0],PARAMETER['False_Northing',0.0],PARAMETER['Central_Meridian',-90.0],PARAMETER['Standard_Parallel_1',42.73333333333333],PARAMETER['Standard_Parallel_2',44.06666666666667],PARAMETER['Latitude_Of_Origin',42.0],UNIT['Foot_US',0.3048006096012192]],VERTCS['NAVD_1988',VDATUM['North_American_Vertical_Datum_1988'],PARAMETER['Vertical_Shift',0.0],PARAMETER['Direction',1.0],UNIT['Foot_US',0.3048006096012192]] CopyRaster "Database Connections\sql60wpchc_CNTYRASTER.sde\CNTYRASTER.GISADMIN.DEM_2010_5FT" U:\elevation\dem_2010\dem_2010.gdb\DEM_2010_5FT # # -3.402823e+38 NONE NONE # NONE NONE "Esri Grid" NONE Rename \\spl103wpi3\e$\arcgisserver\data\elevation\dem_2010\dem_2010.gdb\DEM_2010_5FT \\spl103wpi3\e$\arcgisserver\data\elevation\dem_2010\dem_2010.gdb\dem_2010 RasterDataset DEM_2010_5FT 2484572.966661 2552087.966661 313055.220085 441940.220085 1 Local Area Network file://\\spl103wpi3\e$\arcgisserver\data\elevation\dem_2010\dem_2010.gdb 002 Projected GCS_NAD_1983_2011 Linear Unit: Foot_US (0.304801) NAD_1983_2011_StatePlane_Wisconsin_South_FIPS_4803_Ft_US <ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/10.7'><WKT>PROJCS[&quot;NAD_1983_2011_StatePlane_Wisconsin_South_FIPS_4803_Ft_US&quot;,GEOGCS[&quot;GCS_NAD_1983_2011&quot;,DATUM[&quot;D_NAD_1983_2011&quot;,SPHEROID[&quot;GRS_1980&quot;,6378137.0,298.257222101]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic&quot;],PARAMETER[&quot;False_Easting&quot;,1968500.0],PARAMETER[&quot;False_Northing&quot;,0.0],PARAMETER[&quot;Central_Meridian&quot;,-90.0],PARAMETER[&quot;Standard_Parallel_1&quot;,42.73333333333333],PARAMETER[&quot;Standard_Parallel_2&quot;,44.06666666666667],PARAMETER[&quot;Latitude_Of_Origin&quot;,42.0],UNIT[&quot;Foot_US&quot;,0.3048006096012192],AUTHORITY[&quot;EPSG&quot;,6609]]</WKT><XOrigin>-118121300</XOrigin><YOrigin>-97418300</YOrigin><XYScale>37501932.948264509</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.0032808333333333331</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>103191</WKID><LatestWKID>6609</LatestWKID></ProjectedCoordinateSystem> 20220328 10411000 20220328 10411000 {4962EC49-DD17-4141-94DF-F0FBDCA2E0E5} 1.0 500000 5000 ItemDescription LIDAR/LIDAR_2010_DEM5ft image Microsoft Windows XP Version 5.1 (Build 2600) Service Pack 3; ESRI ArcCatalog 9.3.1.3500 en 2010 Lidar Data Products for the Milwaukee, WI collection area. ESRI Multipoints and Terrain for the Bare Earth lidar points, Hydro and Transportation Breaklines, 5ft DEM, 1ft Contours tiled to manage file size, Voids >= 10 sq meters, Percent Slope, Degree Slope, 5ft Digital Surface Model (DSM), 5ft nDSM (Height Above Ground raster), Tiled Intensity Rasters. 2010 Lidar Data Products for the Milwaukee, WI collection area. ESRI Multipoints and Terrain for the Bare Earth lidar points, Hydro and Transportation Breaklines, 5ft DEM, 1ft Contours tiled to manage file size, Voids >= 10 sq meters, Percent Slope, Degree Slope, 5ft Digital Surface Model (DSM), 5ft nDSM (Height Above Ground raster), Tiled Intensity Rasters. 11042010 DEM_2010_5FT vector digital data ContourTiles_001_032 REQUIRED: The basis on which the time period of content information is determined. November 2010 Complete None planned -88.065311 -87.879920 43.196035 43.160110 2516137.020672 2565313.354479 430001.167537 441902.499837 DEM DSM Voids Lidar Elevation Breaklines Digital Surface Model Slope Contours REQUIRED: Restrictions and legal prerequisites for accessing the data set. REQUIRED: Restrictions and legal prerequisites for using the data set after access is granted. File Geodatabase Feature Class Thom Salter Pictometry International Corp Senior Photogrammetric Engineer mailing and physical address
100 Town Centre Drive, Suite A
Rochester NY 14623 US 585.486.0093 585.486.0098 thom.salter@pictometry.com en FGDC Content Standards for Digital Geospatial Metadata FGDC-STD-001-1998 local time 20101104 Simple Polyline FALSE 30804 TRUE FALSE String 30804 Vector Pixel 25777 13503 5.000000 5.000000 32 1 Upper Left FALSE LZ77 1 pixel codes FGDBR TRUE GCS_North_American_1927 NAD_1927_StatePlane_Wisconsin_South_FIPS_4803 row and column survey feet 5.000000 5.000000 North American Datum of 1927 Clarke 1866 6378206.400000 294.978698 North American Vertical Datum of 1988 feet Karen Kwasnowski GroundPoint Technologies LLC Chief Technical Officer 315.833.9389 kkwasnowski@groundpointllc.com Terrain, DEM, Slope, and 1ft Contours:For the Bare Earth Data, the Lidar Data was converted to a Multipoint feature class, with a filter for Ground (class 2). Breaklines were created from the Milwaukee planimetric data that was provided by the customer for hydrographic and transportation features. All hydrographic features, including water bodies and streams, and transportation features (including edge of road and road centerline) were exported from the planimetric data and elevation values from the lidar data were conflated to the “z-values” of the features. The original z-values of the planimetric data were checked to see if they matched the lidar data and in all spot checks the elevation values did not match close enough to be used as breakline values for the lidar products. Elevation values were conflated to the transportation lines at 10ft intervals from the lidar data using QCoherent’s LP360 software. Elevation values were conflated to the Single Line Stream Breaklines at 10ft intervals with an downstream constraint algorithm. After the single line streams were conflated, a script was used to copy the elevation values from the single line streams to the surrounding double line stream polygons. Elevation values for the water body polygons were added as an attribute to the feature class based on the minimum lidar elevation value along the shoreline of the water body. The multipoint feature class, water bodies, hydrolines, and transportation lines were used to create a bare earth terrain for the collection area. The terrain was converted to a DEM with 5ft cell resolution. Percent Slope and Degree Slope were created from the DEM. The DEM was smoothed using a 3x3 rectangular focalmean algorithm to create the 1ft tiled contours. The contours were edited in the following manner: Lines shorter than 30 ft were deleted, looped contour lines in water ways were deleted, the shape of contour lines along the edge of water ways were edited where the lines wove more than half way across the waterway, contour lines in water bodies were checked and deleted if loops occured within the water. Attributes were also added for 2ft, 10ft, 20ft, and 50ft Index contours. A Lidar Tile Index Feature Class was also created for the original lidar files.Voids: FEMA defines data voids as areas that are not within two times the DEM posting of data points, which equates to 10m for the 2ft contour interval accuracy standard. Data voids are acceptable over bodies of water or where points have been removed over man-made structures. Data voids are not acceptable with LiDAR system malfunction or flight error. Data voids need to be flagged in areas where LiDAR points have been removed due to dense vegetation. If the data voids in areas of dense vegetation are less than 1 acre then the voids may usually be filled by interpolation. If the data voids are greater than 1 acre then cross sections must be cut to fill the void areas. The Bare Earth Multipoint feature class was converted to raster with a 30ft cell size. The raster was reclassified as NoData: 1 and Any_Value: NoData. The reclassified raster was converted to polygon. Polygons < 1076 sq feet were deleted. Attributes were added for ‘Acreage” and “LandCover”. No voids were found to be due to vegetation removal. Digital Surface Model (DSM): For the DSM, the Lidar Point Data was exported to multipoint format, with a filter for 1st return data only, and a maximum elevation of 300 ft higher than the highest ground point. The multipoints were used to create a 1st return terrain, which was then exported to a 1st surface DSM with 5ft cell resolution. A Hillshade was created using default illumination parameters in ESRI software. The Bare Earth DEM was subtracted from the DSM (making sure the cells aligned properly with one another) to produce a normalized DSM (nDSM), which is a raster comprised of heights above ground. Intensity Rasters: The Intensity Rasters of the All Points data were created with a 2ft cell size, which was determined to be the average post spacing of the point cloud. Again LP360 software was used for this procedure with every effort made to interpolate across voids. ArcGIS 9.3.1 November 2010 Metadata imported. 20101104 20241200 Downloadable Data ContourTiles_001_032 Feature Class 30804 OBJECTID OBJECTID OID 4 0 0 Internal feature number. ESRI Sequential unique whole numbers that are automatically generated. Shape Shape Geometry 0 0 0 Feature geometry. ESRI Coordinates defining the features. ID ID Double 8 0 0 CONTOUR CONTOUR Double 8 0 0 Shape_Length Shape_Length Double 8 0 0 Length of feature in internal units. ESRI Positive real numbers that are automatically generated. Index2ft Index2ft SmallInteger 2 0 0 Index10ft Index10ft SmallInteger 2 0 0 Index20ft Index20ft SmallInteger 2 0 0 Index50ft Index50ft SmallInteger 2 0 0 ArcGIS Metadata 1.0 1104-20-10 Karen Kwasnowski dem_2010 <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>2010 Lidar Data Products for the Milwaukee, WI collection area. ESRI Multipoints and Terrain for the Bare Earth lidar points, Hydro and Transportation Breaklines, 5ft DEM, 1ft Contours tiled to manage file size, Voids &gt;= 10 sq meters, Percent Slope, Degree Slope, 5ft Digital Surface Model (DSM), 5ft nDSM (Height Above Ground raster), Tiled Intensity Rasters.</SPAN></P></DIV></DIV></DIV> Thom Salter Pictometry International Corp Senior Photogrammetric Engineer 585.486.0093 585.486.0098 100 Town Centre Drive, Suite A Rochester NY 14623 US thom.salter@pictometry.com DEM DSM Voids Lidar Elevation Breaklines Digital Surface Model Slope Contours DEM Voids Lidar Elevation Contours 1 -88.075611 -87.811351 43.196127 42.838036 Version 6.2 (Build 9200) ; Esri ArcGIS 10.7.1.11595 2010 Lidar Data Products for the Milwaukee, WI collection area. ESRI Multipoints and Terrain for the Bare Earth lidar points, Hydro and Transportation... Milwaukee County Land Information Offices All 2010 LIDAR terrain products Terrain, DEM, Slope, and 1ft Contours:For the Bare Earth Data, the Lidar Data was converted to a Multipoint feature class, with a filter for Ground (class 2). Breaklines were created from the Milwaukee planimetric data that was provided by the customer for hydrographic and transportation features. All hydrographic features, including water bodies and streams, and transportation features (including edge of road and road centerline) were exported from the planimetric data and elevation values from the lidar data were conflated to the “z-values” of the features. The original z-values of the planimetric data were checked to see if they matched the lidar data and in all spot checks the elevation values did not match close enough to be used as breakline values for the lidar products. Elevation values were conflated to the transportation lines at 10ft intervals from the lidar data using QCoherent’s LP360 software. Elevation values were conflated to the Single Line Stream Breaklines at 10ft intervals with an downstream constraint algorithm. After the single line streams were conflated, a script was used to copy the elevation values from the single line streams to the surrounding double line stream polygons. Elevation values for the water body polygons were added as an attribute to the feature class based on the minimum lidar elevation value along the shoreline of the water body. The multipoint feature class, water bodies, hydrolines, and transportation lines were used to create a bare earth terrain for the collection area. The terrain was converted to a DEM with 5ft cell resolution. Percent Slope and Degree Slope were created from the DEM. The DEM was smoothed using a 3x3 rectangular focalmean algorithm to create the 1ft tiled contours. The contours were edited in the following manner: Lines shorter than 30 ft were deleted, looped contour lines in water ways were deleted, the shape of contour lines along the edge of water ways were edited where the lines wove more than half way across the waterway, contour lines in water bodies were checked and deleted if loops occured within the water. Attributes were also added for 2ft, 10ft, 20ft, and 50ft Index contours. A Lidar Tile Index Feature Class was also created for the original lidar files.Voids: FEMA defines data voids as areas that are not within two times the DEM posting of data points, which equates to 10m for the 2ft contour interval accuracy standard. Data voids are acceptable over bodies of water or where points have been removed over man-made structures. Data voids are not acceptable with LiDAR system malfunction or flight error. Data voids need to be flagged in areas where LiDAR points have been removed due to dense vegetation. If the data voids in areas of dense vegetation are less than 1 acre then the voids may usually be filled by interpolation. If the data voids are greater than 1 acre then cross sections must be cut to fill the void areas. The Bare Earth Multipoint feature class was converted to raster with a 30ft cell size. The raster was reclassified as NoData: 1 and Any_Value: NoData. The reclassified raster was converted to polygon. Polygons < 1076 sq feet were deleted. Attributes were added for ‘Acreage” and “LandCover”. No voids were found to be due to vegetation removal. Digital Surface Model (DSM): For the DSM, the Lidar Point Data was exported to multipoint format, with a filter for 1st return data only, and a maximum elevation of 300 ft higher than the highest ground point. The multipoints were used to create a 1st return terrain, which was then exported to a 1st surface DSM with 5ft cell resolution. A Hillshade was created using default illumination parameters in ESRI software. The Bare Earth DEM was subtracted from the DSM (making sure the cells aligned properly with one another) to produce a normalized DSM (nDSM), which is a raster comprised of heights above ground. Intensity Rasters: The Intensity Rasters of the All Points data were created with a 2ft cell size, which was determined to be the average post spacing of the point cloud. Again LP360 software was used for this procedure with every effort made to interpolate across voids. Karen Kwasnowski GroundPoint Technologies LLC Chief Technical Officer 315.833.9389 kkwasnowski@groundpointllc.com Accuracy is described in document located at: http://county.milwaukee.gov/ImageLibrary/Groups/MCLIO/Metadata/LiDARQAQC_MilwaukeeWI_final_01.pdf original metadata PD94bWwgdmVyc2lvbj0iMS4wIiBlbmNvZGluZz0idXRmLTgiPz4NCjxtZXRhZGF0YT4NCiAgPEVz cmk+DQogICAgPENyZWFEYXRlPjIwMTAxMTA0PC9DcmVhRGF0ZT4NCiAgICA8Q3JlYVRpbWU+MjAy NDEyMDA8L0NyZWFUaW1lPg0KICAgIDxTeW5jT25jZT5GQUxTRTwvU3luY09uY2U+DQogICAgPERh dGFQcm9wZXJ0aWVzPg0KICAgICAgPGxpbmVhZ2U+DQogICAgICAgIDxQcm9jZXNzIFRvb2xTb3Vy Y2U9IkM6XFByb2dyYW0gRmlsZXNcQXJjR0lTXEFyY1Rvb2xib3hcVG9vbGJveGVzXENvbnZlcnNp b24gVG9vbHMudGJ4XE1ldGFkYXRhSW1wb3J0ZXIiIERhdGU9IjIwMTAxMTA0IiBUaW1lPSIyMTAy NDMiPk1ldGFkYXRhSW1wb3J0ZXIgRDpcUGljdG9tZXRyeVByb2plY3RzXE1pbHdhdWtlZVxUZXJy YWluUHJvZHVjdHMuZ2RiXENvbnRvdXJUaWxlc18wMDFfMDMyIEQ6XFBpY3RvbWV0cnlQcm9qZWN0 c1xNaWx3YXVrZWVcVGVycmFpblByb2R1Y3RzLmdkYlxERU01ZnQgRDpcUGljdG9tZXRyeVByb2pl 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