Data Note: Spatializing South African Agricultural Censuses, 1918–2017 (Dataset)
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1918
2017
2017
Date completed
2021-03-21
Date updated
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Title
Data Note: Spatializing South African Agricultural Censuses, 1918–2017 (Dataset)
Published Date
2023-06-15
Group
Author Contact
Senay, Senait D
ssenay@umn.edu
ssenay@umn.edu
Type
Dataset
Spatial Data
Spatial Data
Abstract
Agriculture is an intrinsically spatial production process. Where on the landscape agriculture occurs affects the environmental (e.g., soil, water, climate) factors that have large output and production risk consequences. The location of agriculture also has substantial logistic, policy and market performance implications. To facilitate analysis of the spatial dynamics of agriculture, we developed a collection of new ADM 2 boundary files whose geographical dimensions and naming standards map directly to the 18 agricultural censuses that report farm inputs, outputs and related statistics for South African agriculture over the period 1918-2017. The statistical aggregates—representing Magisterial and Municipal Districts—, changed in number, area size and boundaries over time. Cross-referencing these changing statistical aggregates to our newly digitized census boundaries, is an essential step for any geospatial assessment of the causes and (productivity and environmental) consequences associated with the changing physical footprint of South African agriculture over the past century.
Description
This dataset contains 18 GIS boundary datasets that correspond with the South African Agricultural Census Data for about a century ( 1918–2017). The datasets are key to spatialize the aforementioned historical agricultural census data opening up the possibility to use this historical information in new ways that would not have been possible with just the aspatial Census reports.
The dataset comes in Shapefiles (.shp) that contain polygon features at the administrative level two (ADM2). The administrative district names reported in the Agricultural Censuses for each respective year concord with the polygon names given in the shapefiles. The supporting material that is associated with the accompanying paper is uploaded alongside the dataset under submission, and it has detailed accounts on the development of the shapefiles for each of the respective Agricultural Censuses.
Disclaimer: These maps constitute part of the University of Minnesota’s GEMS Informatics digital historical administrative map collection. In constructing this digital collection, extensive efforts were made to adhere to the highest geodetic standards, nonetheless there may remain certain discrepancies, omissions, and inconsistencies within the digitized maps. These inaccuracies can stem from limitations in the original data sources or issues that arise during the data pre-processing stage. Should you identify any errors, we encourage you to assist in their rectification by reaching out to us via the contact information available on our website: http://www.gems.umn.edu/.
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Paper submitted pending review
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Funding information
This dataset and the accompanying paper was developed and prepared respectively, with financial support from Stellenbosch University and the University of Minnesota (Minnesota Agricultural Experiment Station project MIN-14-171 and MNDrive funding to the GEMS Informatics Center), with additional support from the Bill and Melinda Gates Foundation funded by way of the HarvestChoice project (Project ID: OPPGD1450).
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Previously Published Citation
Suggested citation
Senay, Senait D; Greyling, Jan C; Pardey, Philip G; Verhoef, Helene. (2023). Data Note: Spatializing South African Agricultural Censuses, 1918–2017 (Dataset). Retrieved from the University Digital Conservancy, https://doi.org/10.13020/fh35-7m54.
View/Download file
| File View/Open | Description | Size |
|---|---|---|
| Senay_etal_GIS_AdminBoundaryDatasets_August2023.zip | Zipped folder/directory that contains 18 folders that each contain shapefiles that correspond to the boundaries reported by the 18 South African Agricultural Census reports between 1918 and 2017. | 79.87 MB |
| Senay et al_SupportingFiles_June2023.pdf | Supporting material submitted along with a journal article describing the attached dataset. This document details how each dataset was developed and can be used as a 'redme' file for the associated dataset. | 7.84 MB |
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