The zip file contains a large tiff mosaic stitched together from a series of aerial photographs of the Calhoun CZO area taken in 1933, when the area was being acquired by the US Forest Service. USFS archaeologist Mike Harmon delivered the black-and-white photographs, known to him as the "Sumter National Forest Purchase Aerials", to us in a box. The photographs include most of the Enoree District of the Sumter National Forest, including the entirety of the Calhoun CZO, not just the long-term plots and small watersheds. The photographs were scanned and georectified, then color-balanced and stitched together following "seams" - high-contrast features such as rivers and roads ("seamlined"). In addition to the main tiff are four files that can be used to properly geolocate the composite image in ArcGIS.
The multilayer pdf file includes a smaller version of the seamlined 1933 aerial photography mosaic raster layer, as well as this aerial mosaic transparent over slope map (for a 3D-like 1933 image raster). Other layers include contours, roads, boundaries, sampling locations, 1.5 m DEM, 1.5m slope, 1m 2013 NAIP aerial imagery, and 2014 canopy height. The pdf file includes both "interfluve order" and "landshed order." These two layers mean the same thing, but the landshed is the area unit around the interfluve that is used for statistics; this dataset has been QC'ed. The Interfluve Order network was used to delineate the landsheds and agrees with it >95% of the time, but has a few inaccuracies (it was automated by the computer) that were fixed manually. Use the network for viewing and considering the landscape at large, but for the specific interfluve order, check the color of the "Landshed Order" dataset to verify its accuracy.
GIS, Calhoun, historical photographs
XML is in ISO-19115 geographic metadata format, compatible with ESRI Geoportal Server.
Citation for This Webpage
Brecheisen, Zachary S.; Cook, Charles W.; Harmon, M.A. (1933). "CZO Dataset: Calhoun Experimental Forest, SC - GIS/Map Data, Photographic Imagery (1933) - 1933 aerial imagery composite." Retrieved 24 Jan 2020, from http://criticalzone.org/calhoun/data/dataset/4324/
Data Use Policy
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
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.