Idaho LiDAR Consortium (ILC): Nez Perce Reservation
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DOI: https://doi.org/10.5069/G9F18WNM
OT Collection ID: OT.042012.26911.7
OT Collection Name: Idaho LiDAR Consortium (ILC): Nez Perce Reservation
Short Name: ILC02_Nez
Collection Platform: Airborne Lidar
OT Collection ID: OT.042012.26911.7
OT Collection Name: Idaho LiDAR Consortium (ILC): Nez Perce Reservation
Short Name: ILC02_Nez
Collection Platform: Airborne Lidar
Download and Access Products:
| Point Cloud Data | Bulk Download | opentopoID: OTLAS.042012.26911.7 |
Collection Overview:
The lidar survey was conducted by vendor Spencer B. Gross, 13545 NW Science Park dr.,97229, Portland, OR. Lidar instrument Leica ALS40 was flown over the period of 13 and 26 July 2002. The primary goal of the study is to provide operational implementation of Lidar technology in support of project level planning. The proposed applications of Lidar in support of planning are: vegetation structural modeling, erosion modeling, fuels, transportation planning, timber system planning, wildlife habitat modeling, and stream quality. The Rocky Mountain Research Station will provide the development of peer-reviewed forest structural metrics and technical support in implementation of Lidar technology. The technical specifications have been defined to specifically support vegetation modeling using Lidar data. The project area consists of four blocks totaling 24, 729 hectares in Nez Perce Reservation, which is located in central Idaho and is a land of beautiful rivers and steep mountains.
The data were delivered in ASCII format with information on easting, northing and elevation for each Lidar pulse. The ascii files were converted to las format and classified using the Multiscale Curvature Classification (MCC) method of Evans and Hudak (2007). Evans, J.S., and A.T. Hudak. (2007) A multiscale curvature algorithm for classifying discrete return lidar in forested environments. IEEE Transactions on Geoscience and Remote Sensing 45(4): 1029-1038.
Dataset Acknowledgement: Proper credit to Idaho Lidar Consortium.
The ascii files were converted to las format and classified using the Multiscale Curvature Classification (MCC) method of Evans and Hudak (2007):
Evans, J.S., and A.T. Hudak. (2007) A multiscale curvature algorithm for classifying discrete return lidar in forested environments. IEEE Transactions on Geoscience and Remote Sensing 45(4): 1029-1038.
Dataset Citation: Idaho LiDAR Consortium (ILC): Nez Perce Reservation. Distributed by OpenTopography. https://doi.org/10.5069/G9F18WNM . Accessed: 2024-12-21 Copied to Clipboard
Use License: Not Provided
Dataset Keywords: Idaho, lidar
Survey Date: 07/13/2002 - 07/26/2002
Publication Date: 05/04/2012
The lidar survey was conducted by vendor Spencer B. Gross, 13545 NW Science Park dr.,97229, Portland, OR. Lidar instrument Leica ALS40 was flown over the period of 13 and 26 July 2002. The primary goal of the study is to provide operational implementation of Lidar technology in support of project level planning. The proposed applications of Lidar in support of planning are: vegetation structural modeling, erosion modeling, fuels, transportation planning, timber system planning, wildlife habitat modeling, and stream quality. The Rocky Mountain Research Station will provide the development of peer-reviewed forest structural metrics and technical support in implementation of Lidar technology. The technical specifications have been defined to specifically support vegetation modeling using Lidar data. The project area consists of four blocks totaling 24, 729 hectares in Nez Perce Reservation, which is located in central Idaho and is a land of beautiful rivers and steep mountains.The data were delivered in ASCII format with information on easting, northing and elevation for each Lidar pulse. The ascii files were converted to las format and classified using the Multiscale Curvature Classification (MCC) method of Evans and Hudak (2007). Evans, J.S., and A.T. Hudak. (2007) A multiscale curvature algorithm for classifying discrete return lidar in forested environments. IEEE Transactions on Geoscience and Remote Sensing 45(4): 1029-1038.
Dataset Acknowledgement: Proper credit to Idaho Lidar Consortium.
The ascii files were converted to las format and classified using the Multiscale Curvature Classification (MCC) method of Evans and Hudak (2007):
Evans, J.S., and A.T. Hudak. (2007) A multiscale curvature algorithm for classifying discrete return lidar in forested environments. IEEE Transactions on Geoscience and Remote Sensing 45(4): 1029-1038.
Dataset Citation: Idaho LiDAR Consortium (ILC): Nez Perce Reservation. Distributed by OpenTopography. https://doi.org/10.5069/G9F18WNM . Accessed: 2024-12-21 Copied to Clipboard
Use License: Not Provided
Dataset Keywords: Idaho, lidar
Survey Date: 07/13/2002 - 07/26/2002
Publication Date: 05/04/2012
Data Provider and Roles:
Funder Partners
Funder Partners
- Bureau of Indian Affairs
- Idaho LiDAR Consortium
- United States Forest Service Rocky Mountain Research Station
- Spencer B. Gross, Inc.
Total number of points:
145,508,203 pts
Area: 247 km2
Point Density: 0.59 pts/m2
Classifications:
Coordinate System:
Horizontal: NAD83 / UTM Zone 11N Meters [EPSG: 26911]
Vertical: NAVD88 [EPSG: 5703]
Units: meter
Survey Report: Reports
LAS Validation Data Report: ILC02_Nez.html
Area: 247 km2
Point Density: 0.59 pts/m2
Classifications:
| Class 0 - Never classified | 145,508,203 |
Coordinate System:
Horizontal: NAD83 / UTM Zone 11N Meters [EPSG: 26911]
Vertical: NAVD88 [EPSG: 5703]
Units: meter
Survey Report: Reports
LAS Validation Data Report: ILC02_Nez.html
Tile index in shapefile format:
Download
Dataset Extent in GeoJSON format: ILC02_Nez.geojson
Dataset Spatial Bounds: North: 46.5117910667984° South: 46.1403456643792° East: -116.105249895019° West: -116.84316312918°
Dataset Extent in GeoJSON format: ILC02_Nez.geojson
Dataset Spatial Bounds: North: 46.5117910667984° South: 46.1403456643792° East: -116.105249895019° West: -116.84316312918°