Dataset Listing

Reynolds Creek - LiDAR, Snow Depth - Snow-Depth (2009)

LiDAR-derived Snow-on Digital Elevation Model (DEM) 2009 (1 meter)

Variables:  point cloud returns

Standard Variables:  Lidar

Date Range:  (2009-2009)

Dataset Creators/Authors:  Boise State University; Boise Aerospace Center Laboratory; Nancy Glenn

Contact:  Nancy Glenn 1910 University Drive Boise, ID 83725

Field Area:   Reynolds Creek Experimental Watershed

Keywords & XML
  • Description

    Snow depth was calculated for the general area of Reynolds Mountain East in Reynolds Creek Experimental Watershed using lidar data collected in November 10-18, 2007 (snow off) and March 19, 2009 (snow on). The raw point clouds were filtered using the BCAL Lidar Tools and then 2007 and 2009 point clouds were georeferenced to each other. The point clouds were then rasterized to 1 m and the 2007 bare earth raster was subtracted from the 2009 snow on raster to create a 1 m snow depth product. ( and
    Data acquisition and processing were funded by the Bureau of Land Management Owyhee Uplands Pilot Project, US Department of Agriculture Cooperative States Research Education and Extension Service SGP award 2005- 34552-15828, Idaho NSF EPSCoR Program and the National Science Foundation under award number EPS-0447689, Idaho State University, U. S. Forest Service Rocky Mountain Research Station, University of Idaho, and the USDA Agricultural Research Service, Northwest Watershed Research Center. Data collection: The LiDAR survey was conducted using a Leica ALS50 Phase II laser mounted in a Cessna Caravan 208B. The sensor scan angle was ±14 degrees from nadir with a pulse rate designed to yield an average native density (number of pulses emitted by the laser system) of ? 4 points per square meter over terrestrial surfaces. The Leica ALS50 Phase II system allows up to four range measurements (returns) per pulse, and all discernable laser returns are processed for the output dataset. To accurately solve for laser point position (geographic coordinates x, y, z), the positional coordinates of the airborne sensor and the attitude of the aircraft are recorded continuously throughout the LiDAR data collection mission. Aircraft position is measured twice per second (2 Hz) by an onboard differential GPS unit. Aircraft attitude is measured 200 times per second (200 Hz) as pitch, roll and yaw (heading) from an onboard inertial measurement unit (IMU). To allow for post-processing correction and calibration, aircraft/sensor position and attitude data are indexed by GPS time.
  • Keywords

    LiDAR, snow, Reynolds Creek, RCEW, CZO, digital elevation model, DEM

    XML Metadata

    XML is in ISO-19115 geographic metadata format, compatible with ESRI Geoportal Server.

  • Citation for This Dataset

    Glenn, Nancy. 2009. LiDAR-derived Snow-on Digital Elevation Model of Reynolds Creek Experimental Watershed LiDAR (1 meter). Boise State University, Boise Aerospace Center Laboratory. Boise, ID.

    Citation for This Webpage

    Boise State University; Boise Aerospace Center Laboratory; Nancy Glenn (2009). "CZO Dataset: Reynolds Creek - LiDAR, Snow Depth (2009) - Snow-Depth." Retrieved 24 Jan 2020, from

  • Acknowledgements


    US Department of Agriculture Cooperative States Research Education and Extension Service SGP award 2005- 34552-15828
    National Science Foundation EPS-0447689


Reynolds Creek Experimental Watershed - Snow Depth

(a/4/)   Data Level 1

Data Use Policy
Data Sharing Policy
  • Data Use Policy

    DRAFT v.0.4.0

    1. Use our data freely. All CZO Data Products* except those labelled Private** are released to the public and may be freely copied, distributed, edited, remixed, and built upon under the condition that you give acknowledgement as described below. Non-CZO data products — like those produced by USGS or NOAA — have their own use policies, which should be followed.

    2. Give proper citation and acknowledgement. Publications, models and data products that make use of these datasets must include proper citation and acknowledgement. Most importantly, provide a citation in a similar way as a journal article (i.e. author, title, year of publication, name of CZO “publisher”, edition or version, and URL or DOI access information. See Also include at least a brief acknowledgement such as: “Data were provided by the NSF-supported Southern Sierra Critical Zone Observatory” (replace with the appropriate observatory name).

    3. Let us know how you will use the data. The dataset creators would appreciate hearing of any plans to use the dataset. Consider consultation or collaboration with dataset creators.

    *CZO Data Products.  Defined as a data collected with any monetary or logistical support from a CZO.

    **Private. Most private data will be released to the public within 1-2 years, with some exceptionally challenging datasets up to 4 years. To inquire about potential earlier use, please contact us.

  • Data Sharing Policy

    DRAFT v.0.2.5

    All CZO investigators and collaborators who receive material or logistical support from a CZO agree to:

    1. Share data privately within 1 year. CZO investigators and collaborators agree to provide CZO Data Products* — including data files and metadata for raw, quality controlled and/or derived data — to CZO data managers within one year of collection of samples, in situ or experimental data. By default, data values will be held in a Private CZO Repository**, but metadata will be made public and will provide full attribution to the Dataset Creators†.

    2. Release data to public within 2 years. CZO Dataset Creators will be encouraged after one year to release data for public access. Dataset Creators may chose to publish or release data sooner.

    3. Request, in writing, data privacy up to 4 years. CZO PIs will review short written applications to extend data privacy beyond 2 years and up to 4 years from time of collection. Extensions beyond 3 years should not be the norm, and will be granted only for compelling cases.

    4. Consult with creators of private CZO datasets prior to use. In order to enable the collaborative vision of the CZO program, data in private CZO repositories will be available to other investigators and collaborators within that CZO. Releasing or publishing any derivative of such private data without explicit consent from the dataset creators will be considered a serious scientific ethics violation.

    * CZO Data Products. Defined as data collected with any monetary or logistical support from a CZO. Logistical support includes the use of any CZO sensors, sampling infrastructure, equipment, vehicles, or labor from a supported investigator, student or staff person. CZO Data Products can acknowledge multiple additional sources of support.

    ** Private CZO Repository. Defined as a password-protected directory on each CZO’s data server. Files will be accessible by all investigators and collaborators within the given CZO and logins will be maintained by that local CZO’s data managers. Although data values will not be accessible by the public or ingested into any central data system (i.e. CUAHSI HIS), metadata will be fully discoverable by the public. This provides the dual benefit of giving attribution and credit to dataset creators and the CZO in general, while maintaining protection of intellectual property while publications are pending.

    † Dataset Creators. Defined as the people who are responsible for designing, collecting, analyzing and providing quality assurance for a dataset. The creators of a dataset are analogous to the authors of a publication, and datasets should be cited in an analogous manner following the emerging international guidelines described at