20210329
1.0
FGDC CSDGM Metadata
FALSE
Powell_2018
002
697330.662246
700626.506840
328885.179750
333592.060223
1
0.000
Projected
GCS_North_American_1983
Linear Unit: Foot_US (0.304801)
NAD_1983_StatePlane_Montana_FIPS_2500_Feet
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20200917
10063000
20200917
10063000
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FGDC
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Version 6.2 (Build 9200) ; Esri ArcGIS 10.6.1.9273
Powell_2018
vector digital data
2019-12-18
Quantum Spatial
1100 Circle Blvd. Suite 126
Corvallis
OR
97330
US
541-752-1204
http://www.quantumspatial.com
Quantum Spatial
1
-124.675925
-124.661578
47.850419
47.837081
Deer Lodge County LiDAR
2019-06-30
2019-07-31
Provide support for high resolution terrain elevation data from the Deer Lodge County dataset.
<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>This shapefile represents the 3D building footprints contained within the Deer Lodge County LiDAR study area. The horizontal datum for this dataset is NAD83 (2011), the vertical datum is NAVD88, Geoid 12B, and the data is projected in Montana State Plane. Horizontal Horizontal units are in International Feet and Vertical Units are in US Survey Feet. Vertical units are in US Survey feet. Airborne Imaging collected the Deer Lodge County LiDAR data on behalf of Quantum Spatial between 06/30/2019 and 07/31/2019.</SPAN></P></DIV></DIV></DIV>
Montana DNRC Water Resources Division
Light Detection and Ranging
LiDAR
Building Polygons
Shapefile
Buildings
Montana
Upper Phyllis Lake, Oreamnos Lake, Toomey Lake, Martin Lake, Rainbow Lake, Warren Lake, Lost Lakes, Hicks Lake, LaMarche Lake, Emerald Lake, Upper Seymour Lake, Lower Seymour Lake, Fourmile Basin Lakes, Twin Lakes, Lake of the Isle, Georgetown Lake, Silver Lake, Daly Lake, Thornton Lake, Storm Lake, Olson Mountain, Cottonwood Mountain, Orofino Hill, Sugarloaf Mountain, Saratoga Mountain, Donell Mountain, Dickie Peak, Dickie Hills, Georgetown, Anaconda
Light Detection and Ranging, LiDAR, Building Polygons, Shapefile
Montana
Upper Phyllis Lake, Oreamnos Lake, Toomey Lake, Martin Lake, Rainbow Lake, Warren Lake, Lost Lakes, Hicks Lake, LaMarche Lake, Emerald Lake, Upper Seymour Lake, Lower Seymour Lake, Fourmile Basin Lakes, Twin Lakes, Lake of the Isle, Georgetown Lake, Silver Lake, Daly Lake, Thornton Lake, Storm Lake, Olson Mountain, Cottonwood Mountain, Orofino Hill, Sugarloaf Mountain, Saratoga Mountain, Donell Mountain, Dickie Peak, Dickie Hills, Georgetown, Anaconda
This data is projected in Montana State Plane
Steve Story
Montana DNRC Water Resources Division
1429 9th Avenue
Helena
Montana
59620
sestory@mt.gov
US
406-444-6816
Please contact Montana DNRC Water Resources Division for information regarding the use of this data.
Feature Class
1
0.000
Steve Story
Montana DNRC Water Resources Division
1429 9th Avenue
Helena
Montana
59620
sestory@mt.gov
US
406-444-6816
dataset
Esri
8.0.1
0
Simple
FALSE
0
TRUE
TRUE
Powell_2018
Feature Class
0
Deer Lodge County LiDAR Boundary
Quantum Spatial
OBJECTID
OBJECTID
OID
4
10
0
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
Building_Z
Building_Z
Double
8
13
6
LAG
LAG
Double
8
13
6
Area_SQFT
Area_SQFT
Double
8
13
6
Shape
Shape
Geometry
8
0
0
Feature geometry.
Esri
Coordinates defining the features.
Shape.STArea()
Shape.STArea()
Double
0
0
0
Shape.STLength()
Shape.STLength()
Double
0
0
0
2019-12-18
Quantum Spatial
1100 Circle Blvd. Suite 126
Corvallis
OR
97330
US
541-752-1204
http://www.quantumspatial.com
Quantum Spatial
Quantum Spatial
This shapefile was created by extracting LiDAR derived average elevations and applying them to each corresponding building polygon within the dataset. All non- mobile building structures ≥ 100 sqft including carports, awnings, and sheds were captured in 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.
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 0.014 ft (0.046 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_us
0.014 ft (0.046 m)
The Non-vegetated Vertical Accuracy (NVA) of this dataset, tested at 95% confidence level is 0.279 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 56 ground check points. These check points were not used in the calibration or post processing of the LiDAR point cloud data.
NVA
ft_us
0.279 ft (0.085 m)
The Vegetated Vertical Accuracy (VVA) of this dataset, evaluated at the 95th percentile is 0.508 ft (0.155 m). Please see the LiDAR data report for a discussion of the statistics related to this dataset.
Vegetated Vertical Accuracy was assessed using 47 VVA check points. These check points were not used in the calibration or post processing of the LiDAR point cloud data.
VVA
ft_us
0.508 ft (0.155 m)
Acquisition. Airborne Imaging collected the Deer Lodge County LiDAR data on behalf of Quantum Spatial between 06/30/2019 and 07/31/2019. The survey used a Riegl 1560i laser system mounted in a Piper PA-31 Navajo. Ground level GPS and aircraft IMU were collected during the flight. Sensor: Riegl 1560i
Maximum returns: unlimited
Nominal pulse density: 2 pulses/m^2
Nominal pulse spacing: 0.71 m
AGL: 2,300 m
Speed: 140 knots
FOV: 60°
Scan frequency: 80 Hz Pulse rate: 700 kHz
Pulse duration: 2.5 ns
Pulse width: 32.4 cm
Wavelength: 1,064 nm
Pulses in air mode: Multi-Pulse in Air (MPIA)
Beam divergence: 0.18 mrads
Swath width: 2,655 m
Overlap: 30%
2019-07-31
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 PosPac MMS v.8.3 and RiProcess v.1.8.5 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.
2019-12-18