Oregon LIDAR data server at OSU Andrew Meigs, College of Earth, Oceanic, and Atmospheric Sciences Michael Olsen, School of Civil and Construction
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1 Oregon LIDAR data server at OSU Andrew Meigs, College of Earth, Oceanic, and Atmospheric Sciences Michael Olsen, School of Civil and Construction Engineering, College of Engineering Paul Montagne, School of Civil and Construction Engineering, College of Engineering Background Over the past 6 years, the Oregon Department of Geology and Mineral Industries (DOGAMI) has amassed very large research-grade light detection and ranging (LIDAR) datasets covering about 30% of the State of Oregon (Fig. 1). Research grade LIDAR data of the type collected and housed in DOGAMI have centimeterdecimeter scale topographic and spatial resolution. These data, which span coastlines, cities, rivers, volcanoes and deserts, provide a wealth of new information about the landscape as well as the structures and vegetation on the land. DOGAMI, the USGS, University Researchers, and a myriad of other scientists and engineers use LIDAR data to map and model natural hazards and to develop risk assessments associated with earthquake, tsunami, flood, channel migration, volcanic eruptions, landslide and coastal erosion hazards, and in dozens of other investigations of landscapes, streams and vegetation, the built environment, land use, and change detection. LIDAR data have revolutionized our ability to image and quantitatively analyze the surface of the Earth (Figs. 2 and 3). The potential uses of LIDAR are vast. Whereas LIDAR data collected and stored by DOGAMI are in the public domain, these data have been essentially unobtainable by users in practice. The principal reason for the lack of accessibility has been that DOGAMI has neither the manpower nor the resources to distribute the data on request due to its size. Some datasets are available through partner organizations; however, these datasets are scattered and it is important to ensure that (1) we have all of the available data (point clouds, QA/QC points, terrain and surface models, etc., and (2) we stay in sync with DOGAMI so that we can make sure we are not missing datasets. Recently, OSU negotiated an agreement with DOGAMI to acquire their complete database (about 25 TB) since LIDAR data can be used for a wide variety of purposes. Ian Madin (DOGAMI) was instrumental in making this happen. Funds were provided by the College of Earth Ocean & Atmospheric Sciences (CEOAS), College of Engineering (CoE), College of Agriculture (CoA) and College of Forestry (CoF) to obtain this database. These data are housed on a server maintained by the CoE and are accessible to any OSU student or researcher by merely logging onto the server and selecting the files they need (see Appendix 1 for instructions). Housing the data at OSU will facilitate the use of the data in teaching and in research and provide the opportunity for use of these data in a wide array of activities to the benefit of the students, faculty and state of Oregon. These costs are minimal compared to the amount of research revenue that could
2 be generated as a result of access to this data and to the usage of the data in courses. Potential upgrades may include (but not limited to): 1. Access to all universities in the Oregon University System. 2. A more intuitive interface to the dataset. 3. GIS server to stream bare earth models 4. Continual server upgrades and maintenance. At this time, we do not know how much demand to expect on the server. 5. DOGAMI staff time to copy future data products and deliver to OSU. These upgrades and others you may be interested in will require additional funding, support, and time. So while you can access and use the data now, please bear in mind that it is not free and there are costs (albeit relatively small when shared by all users). Hence, it is important you are willing to contribute and let your departments know of the importance of the data so that we are able to continue to provide the service and make upgrades such as those listed. Figure 1, Status of LIDAR coverage in Oregon. Colored polygons are regions with LIDAR data in the database we propose to acquire.
3 Standard DEM LIDAR data Figure 2. Comparison of Traditional DEM (30m cell size +) to LIDAR data (grey, 1m cell size). Note the increased detail in riverbeds and on slopes. Figure 3. Terrestrial LIDAR point cloud data of a sea cliff.
4 Additional acknowledgments: Jim Lundy led the coordination of the funding between CEOAS, Engineering, Forestry, and Agriculture. The Engineering IT staff provided substantial time in building the server and copying and verifying the data. Ian Madin and Johnny English of DOGAMI coordinated the agreement and delivery of the data to OSU. The Oregon LIDAR Consortium coordinated the acquisition of the data itself as well as funding from several state and federal agencies. We thank all of those who made this happen and know that it will be a valuable resource across campus. Any research publications or products derived from using this data should acknowledge DOGAMI and the Oregon LIDAR consortium as the source of the data.
5 Appendix 1. How to access the data 1. Using windows explorer (or equivalent in other operating systems), go to the network address: \\lidar.engr.oregonstate.edu\lds 2. You will likely need to login with your ONID account and specify the onid domain. If you do not have an ONID account, you will not be able to access the data at this time. The login screen will look something like this, replacing xxxxxx with your user name: 3. You may want to add the folder as a network drive to your computer if you plan on revisiting often. (Click on Map Network Drive in the menu options in windows explorer and enter the address above). 4. Open LDQ-pubs-index.pdf to determine what the name of the section of interest. Alternatively, you can see data coverage at: 5. The data are organized into regions (e.g. Deschutes, Klamath, Mt. Hood) that are color coded. Determine which region your dataset is in. Also note the quadrangle(s) you will need. 6. Next, the folders on the drive are then organized by disks on which the data were delivered. Use Appendix 2 to determine which disk contains the region of interest. 7. Browse the directory of the disks to find your region and quadrangle. Note that quadrangles are split into tiles. The tiles are numbered from the upper left. Many of the datasets include a vectors directory which has shape files to show how they quads are divided.
6 8. Once you find the tiles of interest, there will be several types of files, depending on your interests. Because of evolving technology and organization schemes, there will be variability between data formats. 9. If you are interested in point clouds, they will be available as las,laz,txt or pts files. Newer datasets will have separate LAS files with ground points only and all points. Working with the point clouds will require much more expertise and computing power than just the DTMs. 10. Bare earth DTMs will be available in the Rasters folder in ESRI grid format (note that if you are not familiar with ESRI grid format and all of the necessary files, you will want to use ArcCatalog to copy the data to make sure you copy all of the necessary files). 11. Intensity imagery are often provided as GeoTiffs. 12. Please do not stream directly from the network drive (e.g. bare earth models). Please download a local copy to your machine to use. 13. Each directory will also contain a report regarding QA/QC and the purpose of the data collection, time, etc. 14. Usually the trajectory will also be provided as a shapefile. 15. When downloading files, please verify everything copied over properly. These are large files and you time outs and data drop outs can occur periodically. 16. Finally, there are a few courses on campus that will help you learn how to use LIDAR data. These include, but are not limited to: CE 505 3D laser scanning CE 562 Digital Terrain Modeling FE 309 Forest Photogrammetry GEO 544 Remote Sensing SOIL 468/568 Soil Landscape Analysis 17. Any research publications or products derived from using this data should acknowledge DOGAMI and the Oregon LIDAR consortium as the source of the data. 18. Please note that at this time there is no formal support staff for help with accessing the data aside from within the above listed courses. However, we may offer a quick course\help session periodically, if there is sufficient interest. Limited support will be provided through lidar@oregonstate.edu
7 Appendix 2. Disk organization Drive Number Data Included Drive 1 Klamath ddssv3 Klamath Bof R Burns Drive 2 Deschutes ddssv3 Eagle Point Pine Creek Ochoco Umatilla Drive 3 Newberry2 ddssv3 Shasta Panther Creek 2011 Catherine Creek Grande Ronde Catherine Creek 09 Cottonwood Canyon Damon Malhuer HJ Andrews LC West USFS Lake Billy Chinook Drive 4 Drive 5 Crater Lake ddssv2 Newberry 1 Rogue Valley 09 Yambo Glass Buttes MacDonald Dunn Oregon City Sandy River 2008 Umpqua (PSLC Coe) Wood River Camp Creek Ontario PDX_Hood ddssv1 Deschutes2005 Lower Columbia Sprague River 2004 Salmon River Hood Sandy 2006 Portland_Hills Coos Bay
8 Panther Creek 2007 Portland Pilot Ashland 2006 Honeymon Salmon River Coast Silver Falls Soda Butte Sumpter Drive 6 North Coast Yambo Drive 7 Willamette Valley 2009 Drive 8 Drive 9 Coastal Malheur River 2008 Oregon City Rogue Valley SF John Day Southcoast Survey 2008 Yamhill OLC_CENTRAL_COAST_2012 OLC_KENO_2012 OLC_TILLAMOOK_YAMHILL_2012 OLC_UNION_BAKER_2012
9 Appendix 3. General Deliverables provided by DOGAMI to OSU Bare earth and highest hit 3ft (or 1m) digital elevation models (DEM) in Esri grid format. These rasters are tiled using USGS 7.5 minute quadrangles and named using quadrangle Ohio code (e.g. be45123b5 or hh45123b5). Intensity Geotiffs at 1.5ft (or 0.5m) resolution (projected using TIFF headers and comes with world files). These rasters are tiled using USGS 1/100th 7.5 minute quadrangles and named using quadrangle Ohio code - quarter quad tile # (e.g 45123b5103). Ground Density Rasters depicting ground point density used to create bare earth ground DEMs. These rasters are tiled using USGS 1/100th 7.5 minute quadrangles and named using quadrangle Ohio code - quarter quad tile # (e.g g45123b5103). All points LAS files containing all points used in DEM creation classified as ground or non-ground (classes 1 and 2). Ground Classified Points in LAS format Vectors files in either shape file or geodatabase format that were delivered with data. typically these are reference files pertaining to either the delivery Reports provided by the LIDAR vendor as well as QC reports created by DOGAMI. DOGAMI QC reports contain content which includes description of precise GPS measurements. These measurements do not represent an actual survey.
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