Dataset Listing

Reynolds Creek Experimental Watershed - LiDAR, Digital Elevation Model (DEM) - DEM (2014)

LiDAR-derived DEM (1m) from 2014.

Variables:  point cloud returns

Date Range:  (2014-2014)

Dataset Creators/Authors:  Nayani Ilangakoon; Nancy F. Glenn; Lucas P. Spaete; Hamid Dashti; Aihua Li

Contact:  Nancy Glenn, BOISE CENTER AEROSPACE LABORATORY

Field Area:   Reynolds Creek Experimental Watershed

Description
Keywords & XML
Citation
  • Description

    Full waveform lidar data were collected by NASA's Jet propulsion Laboratory (JPL) Airborne Snow Observatory (ASO) in August 2014 for a NASA Terretrial Ecology project (NNX14AD81G). The data were collected using a Riegl LMS Q-1560 dual laser scanner system. The full waveforms were decomposed in Riegl RiPROCESS software to generate 3D point cloud with an average point density of 14-20 pts/m2. The point clouds were corrected for elevation and roll misalignment between adjacent flight lines in TerraScan. A Digital Elevation Model (DEM) of 1 m resolution was derived using the corrected point cloud using BCAL Lidar Tools (https://bcal.boisestate.edu/tools/lidar and https://github.com/bcal-lidar/tools/wiki/BareDEM).
  • Keywords

    Reynolds Creek, DEM, LiDAR, 1 meter

    XML Metadata

    criticalzone.org/reynolds/data/xml-metadata-test/5270/

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

  • Citation for This Dataset

    Ilangakoon, Nayani; Glenn, Nancy F.; Spaete, Lucas P.; Dashti, Hamid; and Li, Aihua. (2016). 2014 Lidar-Derived 1m Digital Elevation Model Data Set for Reynolds Creek Experimental Watershed, Southwestern Idaho [Data set]. Boise, ID: . http://doi.org/10.18122/B26C7X

    Citation for This Webpage

    Nayani Ilangakoon; Nancy F. Glenn; Lucas P. Spaete; Hamid Dashti; Aihua Li (2014). "CZO Dataset: Reynolds Creek Experimental Watershed - LiDAR, Digital Elevation Model (DEM) (2014) - DEM." Retrieved 20 Mar 2019, from http://criticalzone.org/reynolds/data/dataset/5270/

Data

Reynolds Creek Experimental Watershed - LiDAR, DEM 2014

(a/3/)   Data Level 2,   DOI: 10.18122/B26C7X

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 http://www.datacite.org/whycitedata). 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 http://www.datacite.org/whycitedata.


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