20210329 1.0 FGDC CSDGM Metadata FALSE Madison_River_2018 002 1381201.256234 1471241.509186 212186.291995 602509.250328 1 1.344 Projected GCS_North_American_1983 Linear Unit: Foot_US (0.304801) NAD_1983_StatePlane_Montana_FIPS_2500_Feet <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/10.6'><WKT>PROJCS[&quot;NAD_1983_StatePlane_Montana_FIPS_2500_Feet&quot;,GEOGCS[&quot;GCS_North_American_1983&quot;,DATUM[&quot;D_North_American_1983&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;,-109.5],PARAMETER[&quot;Standard_Parallel_1&quot;,45.0],PARAMETER[&quot;Standard_Parallel_2&quot;,49.0],PARAMETER[&quot;Latitude_Of_Origin&quot;,44.25],UNIT[&quot;Foot_US&quot;,0.3048006096012192],AUTHORITY[&quot;Esri&quot;,102700]]</WKT><XOrigin>-117014100</XOrigin><YOrigin>-98447500</YOrigin><XYScale>3048.0060960121928</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>102700</WKID><LatestWKID>102700</LatestWKID></ProjectedCoordinateSystem> 20200116 16211900 20200116 16211900 150000000 5000 FGDC 14395000 Version 6.2 (Build 9200) ; Esri ArcGIS 10.6.1.9273 Madison_River_2018 vector digital data 2018-03-21 Quantum Spatial 517 SW 2nd St., Suite 400 Corvallis OR 97333 US 541-752-1204 http://www.quantumspatial.com Quantum Spatial 1 -111.807156 -111.416096 45.885479 44.808560 Madison River LiDAR 2017-10-27 2017-11-28 Provide support for high resolution terrain elevation data from the Madison River dataset. <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>This shapefile represents the 3D building footprints contained within the Madison River LiDAR Study Area. The LiDAR derived building heights of each structure are provided within each polygon. The horizontal datum for this dataset is NAD83(2011) - FIPS 2500, the vertical datum is NAVD88, Geoid 12B, and the data is projected in Montana State Plane. Horizontal units are in International Feet and Vertical units are in US Survey Feet. Quantum Spatial collected the Madison River LiDAR data for the Montana Department of Natural Resources and Conservation between 10/27/17 and 11/28/17.</SPAN></P></DIV></DIV></DIV> Montana Department of Natural Resources and Conservation Light Detection and Ranging LiDAR Building Polygons Shapefile Madison and Gallatin counties Montana Light Detection and Ranging, LiDAR, Building, Footprint, Shapefile Madison and Gallatin counties Montana This data is projected in Montana State Plane Steve Story Montana Department of Natural Resources and Conservation 1424 9th Ave. Helena Montana 59620-1601 sestory@mt.gov US (406) 444-6816 Please contact the Montana Department of Natural Resources and Conservation for information regarding the use of this data. Feature Class 1 1.344 Steve Story Montana Department of Natural Resources and Conservation 1424 9th Ave. Helena Montana 59620-1601 sestory@mt.gov US (406) 444-6816 dataset Esri 8.0.1 0 Simple FALSE 0 TRUE TRUE Madison_River_2018 Feature Class 0 Madison River LiDAR Boundary Quantum Spatial OBJECTID OBJECTID OID 4 10 0 Internal feature number. Esri Sequential unique whole numbers that are automatically generated. GISFLOOD.FLOOD_DO.Madison_River_2018.Area GISFLOOD.FLOOD_DO.Madison_River_2018.Area Double 8 13 6 Shape Shape Geometry 8 0 0 Feature geometry. Esri Coordinates defining the features. Area Area Double 14 13 6 Area of building footprint in square feet. Quantum Spatial Square feet calculated in Montana State Plane Height Height of structure in feet. QSI Float 0 Feet calculated in Montana State Plane Height 13 6 LAG LAG = Lowest Adjacent Grade elevation in feet. QSI Float 0 Feet calculated in Montana State Plane LAG 13 6 Easting Easting at centroid of building footprint. QSI Float 0 Easting coordinate is in Montana State Plane Easting 13 6 Shape.STArea() Shape.STArea() Double 0 0 0 Shape.STLength() Shape.STLength() Double 0 0 0 Northing Northing at centroid of building footprint. QSI Float 0 Northing coordinate is in Montana State Plane Northing 13 6 2018-03-09 Quantum Spatial 517 SW 2nd St., Suite 400 Corvallis OR 97333 US 541-752-1204 http://www.quantumspatial.com Quantum Spatial Quantum Spatial Shaded relief images have been visually inspected for data errors such as pits, border artifacts, and shifting. LiDAR flightlines have been examined to ensure consistent elevation values across overlapping flightlines. The Root Mean Square Error (RMSE) of line to line relative accuracy for this dataset is 0.082 ft (0.025 m). Please see the LiDAR data report for a discussion of the statistics related to this dataset. Data was examined at a 1:2000 scale. Relative accuracy of the flightlines was assessed in Microstation using TerraMatch. RMSE ft_i 0.082 ft (0.025 m) The Non-vegetated Vertical Accuracy (NVA) of this dataset, tested at 95% confidence level is 0.278 ft (0.085 m). Please see the LiDAR data report for a discussion of the statistics related to this dataset. Non-vegetated Vertical Accuracy was assessed using 22 ground check points. These check points were not used in the calibration or post processing of the LiDAR point cloud data. NVA ft_i 0.278 ft (0.085 m) The Vegetated Vertical Accuracy (VVA) of this dataset, evaluated at the 95th percentile is 0.703 ft (0.214 m). Please see the LiDAR data report for a discussion of the statistics related to this dataset. Vegetated Vertical Accuracy was assessed using 9 VVA check points. These check points were not used in the calibration or post processing of the LiDAR point cloud data. VVA ft_i 0.703 ft (0.214 m) Acquisition. Quantum Spatial collected the Madison River LiDAR data between 10/27/17 and 11/28/17. The survey used a Leica ALS80 laser system mounted in a Cessna Caravan. Ground level GPS and aircraft IMU were collected during the flight. Sensor: Leica ALS80 Maximum returns: Unlimited Nominal pulse density: 8 pulses/m^2 Nominal pulse spacing: 0.35 m AGL: 1,700 m Speed: 105 knots FOV: 36° Scan frequency: 45.0 hz Pulse rate: 325 kHz Pulse duration: 2.5 ns Pulse width: 37.4 cm Wavelength: 1064 nm Pulses in air mode: Multiple Pulses in Air Beam divergence: 22 mrads Swath width: 1,105 m Overlap: 63% 2017-11-28 1. Flightlines and data were reviewed to ensure complete coverage of the study area and positional accuracy of the laser points. 2. Laser point return coordinates were computed using Waypoint Inertial Explorer v.8.6 and Leica Cloudpro v. 1.2.2 software based on independent data from the LiDAR system, IMU, and aircraft. 3. The raw LiDAR file was assembled into flightlines per return with each point having an associated x, y, and z coordinate. 4. Visual inspection of swath to swath laser point consistencies within the study area were used to perform manual refinements of system alignment. 5. Custom algorithms were designed to evaluate points between adjacent flightlines. Automated system alignment was computed based upon randomly selected swath to swath accuracy measurements that consider elevation, slope, and intensities. Specifically, refinement in the combination of system pitch, roll, and yaw offset parameters optimize internal consistency. 6. Noise (e.g., pits and birds) was filtered using post-processing software, based on known elevation ranges and included the removal of any cycle slips. 7. Using TerraScan and Microstation, ground classifications utilized custom settings appropriate to the study area. 8. The corrected and filtered return points were compared to the ground survey points collected to verify the vertical accuracy. 2018-03-09 This shapefile was created by extracting LiDAR derived average elevations and applying them to each building polygon within the dataset. LiDAR data has been collected and processed for all areas within the project study area. Flight plans are designed with sufficient sidelap to ensure there are no gaps between flightlines. Shaded relief images have been visually inspected for gaps.