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‎CODE_OF_CONDUCT.md‎

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---
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title: "Contributor Code of Conduct"
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---
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As contributors and maintainers of this project,
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we pledge to follow the [The Carpentries Code of Conduct][coc].
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Instances of abusive, harassing, or otherwise unacceptable behavior
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may be reported by following our [reporting guidelines][coc-reporting].
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[coc]: https://docs.carpentries.org/topic_folders/policies/code-of-conduct.html
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[coc-reporting]: https://docs.carpentries.org/topic_folders/policies/incident-reporting.html
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‎LICENSE.md‎

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---
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title: "Licenses"
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---
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## Instructional Material
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All Carpentries (Software Carpentry, Data Carpentry, and Library Carpentry)
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instructional material is made available under the [Creative Commons
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Attribution license][cc-by-human]. The following is a human-readable summary of
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(and not a substitute for) the [full legal text of the CC BY 4.0
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license][cc-by-legal].
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You are free:
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- to **Share**\---copy and redistribute the material in any medium or format
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- to **Adapt**\---remix, transform, and build upon the material
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for any purpose, even commercially.
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The licensor cannot revoke these freedoms as long as you follow the license
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terms.
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Under the following terms:
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- **Attribution**\---You must give appropriate credit (mentioning that your work
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is derived from work that is Copyright (c) The Carpentries and, where
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practical, linking to [https://carpentries.org/](https://carpentries.org/)), provide a [link to the
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license][cc-by-human], and indicate if changes were made. You may do so in
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any reasonable manner, but not in any way that suggests the licensor endorses
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you or your use.
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- **No additional restrictions**\---You may not apply legal terms or
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technological measures that legally restrict others from doing anything the
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license permits. With the understanding that:
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Notices:
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- You do not have to comply with the license for elements of the material in
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the public domain or where your use is permitted by an applicable exception
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or limitation.
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- No warranties are given. The license may not give you all of the permissions
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necessary for your intended use. For example, other rights such as publicity,
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privacy, or moral rights may limit how you use the material.
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## Software
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Except where otherwise noted, the example programs and other software provided
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by The Carpentries are made available under the [OSI][osi]\-approved [MIT
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license][mit-license].
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Permission is hereby granted, free of charge, to any person obtaining a copy of
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this software and associated documentation files (the "Software"), to deal in
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the Software without restriction, including without limitation the rights to
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use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies
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of the Software, and to permit persons to whom the Software is furnished to do
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so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.
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## Trademark
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"The Carpentries", "Software Carpentry", "Data Carpentry", and "Library
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Carpentry" and their respective logos are registered trademarks of
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[The Carpentries, Inc.][carpentries].
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[cc-by-human]: https://creativecommons.org/licenses/by/4.0/
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[cc-by-legal]: https://creativecommons.org/licenses/by/4.0/legalcode
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[mit-license]: https://opensource.org/licenses/mit-license.html
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[carpentries]: https://carpentries.org
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[osi]: https://opensource.org
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‎config.yaml‎

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#------------------------------------------------------------
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# Values for this lesson.
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#------------------------------------------------------------
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# Which carpentry is this (swc, dc, lc, or cp)?
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# swc: Software Carpentry
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# dc: Data Carpentry
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# lc: Library Carpentry
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# cp: Carpentries (to use for instructor training for instance)
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# incubator: The Carpentries Incubator
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carpentry: 'dc'
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# Overall title for pages.
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title: 'Geospatial Workshop Overview'
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# Date the lesson was created (YYYY-MM-DD, this is empty by default)
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created: '2018-03-06'
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# Comma-separated list of keywords for the lesson
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keywords: 'software, data, lesson, The Carpentries' # FIXME
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# Life cycle stage of the lesson
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# possible values: pre-alpha, alpha, beta, stable
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life_cycle: 'stable'
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# License of the lesson
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license: 'CC-BY 4.0'
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# Link to the source repository for this lesson
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source: 'https://github.com/datacarpentry/geospatial-workshop'
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# Default branch of your lesson
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branch: 'main'
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# Who to contact if there are any issues
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contact: '[email protected]'
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# Navigation ------------------------------------------------
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#
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# Use the following menu items to specify the order of
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# individual pages in each dropdown section. Leave blank to
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# include all pages in the folder.
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#
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# Example -------------
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#
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# episodes:
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# - introduction.md
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# - first-steps.md
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#
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# learners:
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# - setup.md
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#
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# instructors:
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# - instructor-notes.md
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#
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# profiles:
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# - one-learner.md
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# - another-learner.md
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# Order of episodes in your lesson
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episodes:
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- introduction.Rmd
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# Information for Learners
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learners:
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# Information for Instructors
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instructors:
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# Learner Profiles
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profiles:
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# Customisation ---------------------------------------------
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#
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# This space below is where custom yaml items (e.g. pinning
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# sandpaper and varnish versions) should live
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url: 'https://datacarpentry.github.io/geospatial-workshop'
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analytics: 'carpentries'
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lang: 'en'
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overview: true

‎data.md‎

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---
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title: Workshop data
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---
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## NEON Spatio-temporal Teaching Data Subset
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Available on FigShare:
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[NEON Spatio-temporal Teaching Data Subset](https://figshare.com/articles/Spatio_temporal_Series_Teaching_Data_Subsets/2009586).
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**CITATION:** Data Skills Teaching Data Subsets, NEON; Wasser, Leah; Jones, Megan A. (2016):
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NEON Spatio-temporal Teaching Data Subset. figshare. Fileset. [https://doi.org/10.6084/m9.figshare.2009586.v10](https://doi.org/10.6084/m9.figshare.2009586.v10)
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The data and lessons in this workshop were originally developed through a hackathon funded by the [National Ecological Observatory Network (NEON)](https://www.neonscience.org/) - an NSF funded observatory in Boulder, Colorado - in collaboration with Data Carpentry, SESYNC and CYVERSE. NEON is collecting data for 30 years to help scientists understand
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how our aquatic and terrestrial ecosystems are changing. The data used in these lessons cover two NEON field sites:
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- Harvard Forest (HARV) - Massachusetts, USA - [fieldsite description](https://www.neonscience.org/field-sites/field-sites-map/HARV)
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- San Joaquin Experimental Range (SJER) - California, USA - [fieldsite description](https://www.neonscience.org/field-sites/field-sites-map/SJER)
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You can download all of the data used in this workshop by clicking
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[this download link](https://ndownloader.figshare.com/articles/2009586/versions/10).
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Clicking the download link will automatically download all of the files to your default download directory as a single compressed
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(`.zip`) file. To expand this file, double click the folder icon in your file navigator application (for Macs, this is the Finder
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application).
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These data files represent teaching version of the data, with sufficient complexity to teach many aspects of data analysis and
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management, but with many complexities removed to allow students to focus on the core ideas and skills being taught.
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| Dataset | File name | Description |
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| ---------------------------- | ---------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| Site layout shapefiles | NEON-DS-Site-Layout-Files.zip | A set of shapefiles for the NEON's Harvard Forest field site and US and (some) state boundary layers. |
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| Meteorological data | NEON-DS-Met-Time-Series.zip | Precipitation, temperature and other variables collected from a flux tower at the NEON Harvard Forest site |
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| Airborne remote sensing data | NEON-DS-Airborne-RemoteSensing.zip | LiDAR data collected by the NEON Airborne Observation Platform (AOP) and processed at NEON including a canopy height model, digital elevation model and digital surface model for NEON's Harvard Forest and San Joaquin Experimental Range field sites. |
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| Landstat 7 NDVI raster data | NEON-DS-Landsat-NDVI.zip | 2011 NDVI data product derived from Landsat 7 and processed by USGS cropped to NEON's Harvard Forest and San Joaquin Experimental Range field sites |
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### About the Site Layout Shapefiles
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These vector data provide information on the site characterization and infrastructure at the
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[National Ecological Observatory Network's](https://www.neonscience.org/)
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[Harvard Forest](https://www.neonscience.org/field-sites/field-sites-map/HARV) field site.
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The Harvard Forest shapefiles are from the [Harvard Forest GIS \& Map](https://harvardforest.fas.harvard.edu/gis-maps/) archives.
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US Country and State Boundary layers are from the [US Census Bureau](https://www.census.gov/geo/maps-data/data/tiger-cart-boundary.html).
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### About the Meteorological Data
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The data used in this lesson were collected at the [National Ecological Observatory Network's](https://www.neonscience.org/)
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[Harvard Forest](https://www.neonscience.org/field-sites/field-sites-map/HARV). These data are proxy data for what will be available
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for 30 years on the [NEON data portal](https://data.neonscience.org/home) for the Harvard Forest and other field sites located across
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the United States.
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### About the Airborne Remote Sensing Data
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This data was collected at the [National Ecological Observatory Network's](https://www.neonscience.org/)
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[Harvard Forest](https://www.neonscience.org/field-sites/field-sites-map/HARV) and
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[San Joaquin Experimental Range](https://www.neonscience.org/field-sites/field-sites-map/SJER) field sites.
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Data are collected during peak greenness at each field site and are processed to provide useful data products to the community. The following NEON data products are used in these lessons:
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Data Created from Discrete Return (point clouds) Lidar Data:
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- DSM (Digital Surface Model; full mosaic)
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- DTM (Digital Terrain Model; full mosaic)
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- CHM (Canopy Height Model; full mosaic; Harvard Forest site only)
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and
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- RGB imagery (Harvard Forest site only) derived from the RGB Camera
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Additional information about airborne remote sensing data, including other data types for these and other sites can
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be found on [NEON's Airborne Data](https://www.neonscience.org/data-collection/airborne-remote-sensing) page.
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### About the Landstat 7 NDVI Raster Data
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The imagery data used to create this raster teaching data subset were collected over the
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[National Ecological Observatory Network's](https://www.neonscience.org/)
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[Harvard Forest](https://www.neonscience.org/field-sites/field-sites-map/HARV)
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and [San Joaquin Experimental Range](https://www.neonscience.org/field-sites/field-sites-map/SJER) field sites.
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The imagery was created by the U.S. Geological Survey (USGS) using a
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[multispectral scanner](https://eros.usgs.gov/#/Find_Data/Products_and_Data_Available/MSS) on a
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[Landsat Satellite](https://landsat.usgs.gov/). The data files are Geographic Tagged Image-File Format (GeoTIFF).
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‎index.md‎

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---
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site: sandpaper::sandpaper_site
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---
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Data Carpentry's aim is to teach researchers basic concepts, skills, and tools for working with data so that they can get more done in less time, and with less pain.
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Interested in teaching these materials? We have an [onboarding video](https://www.youtube.com/watch?v=Qtnb_eeHt7E) available to prepare Instructors to teach these lessons. After
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watching this video, please contact [[email protected]](mailto:[email protected]) so that we can record your status as an onboarded
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Instructor. Instructors who have completed onboarding will be given priority status for teaching at centrally-organized Data Carpentry Geospatial workshops.
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:::::::::::::::::::::::::::::::::::::::::: prereq
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## Getting Started
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Data Carpentry's teaching is hands-on, so participants are encouraged to use
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their own computers to ensure the proper setup of tools for an efficient
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workflow. To most effectively use these materials, please make sure to download
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the data and install everything before working through this lesson.
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This workshop assumes no prior experience with the tools covered in the workshop. However, learners with prior
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experience working with geospatial data may be able to skip the
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[Geospatial Project Organization and Management](https://www.datacarpentry.org/organization-geospatial/) lesson.
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Similarly, learners who have prior experience with the `R` programming language may wish to skip the
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[Introduction to R for Geospatial Data](https://www.datacarpentry.org/r-intro-geospatial/) lesson.
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To get started, follow the directions in the [Setup](learners/setup.md) tab to
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get access to the required software and data for this workshop.
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::::::::::::::::::::::::::::::::::::::::::::::::::
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:::::::::::::::::::::::::::::::::::::::::: prereq
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## Data
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The data and lessons in this workshop were originally developed through a hackathon funded by the
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[National Ecological Observatory Network (NEON)](https://www.neonscience.org/) - an NSF funded observatory in Boulder, Colorado - in
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collaboration with Data Carpentry, SESYNC and CYVERSE. NEON is collecting data for 30 years to help scientists understand
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how aquatic and terrestrial ecosystems are changing. The data used in these lessons cover two NEON field sites:
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- Harvard Forest (HARV) - Massachusetts, USA - [fieldsite description](https://www.neonscience.org/field-sites/field-sites-map/HARV)
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- San Joaquin Experimental Range (SJER) - California, USA - [fieldsite description](https://www.neonscience.org/field-sites/field-sites-map/SJER)
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There are four data sets included, all of which are available
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[on Figshare](https://figshare.com/articles/Spatio_temporal_Series_Teaching_Data_Subsets/2009586)
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under a CC-BY license. You can download all of the data used in this workshop by clicking
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[this download link](https://ndownloader.figshare.com/articles/2009586/versions/10).
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Clicking the download link will download all of the files as a single compressed
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(`.zip`) file. To expand this file, double click the folder icon in your file navigator application (for Macs, this is the Finder
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application).
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These data files represent the teaching version of the data, with sufficient complexity to teach many aspects of data analysis and
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management, but with many complexities removed to allow students to focus on the core ideas and skills being taught.
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| Dataset | File name | Description |
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| ------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| Site layout shapefiles | NEON-DS-Site-Layout-Files.zip | A set of shapefiles for the NEON's Harvard Forest field site and US and (some) state boundary layers. |
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| Meteorological data | NEON-DS-Met-Time-Series.zip | Precipitation, temperature and other variables collected from a flux tower at the NEON Harvard Forest site |
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| Airborne remote sensing data | NEON-DS-Airborne-RemoteSensing.zip | LiDAR data collected by the NEON Airborne Observation Platform (AOP) and processed at NEON including a canopy height model, digital elevation model and digital surface model for NEON's Harvard Forest and San Joaquin Experimental Range field sites. |
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| Landstat 7 NDVI raster data | NEON-DS-Landsat-NDVI.zip | 2011 NDVI data product derived from Landsat 7 and processed by USGS cropped to NEON's Harvard Forest and San Joaquin Experimental Range field sites |
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[More information on this dataset](instructors/data.md)
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::::::::::::::::::::::::::::::::::::::::::::::::::
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# Workshop Overview
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| Lesson | Overview |
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| ---------------------------------------------------------- | ------------------------------------------------------------ |
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| [Introduction to Geospatial Concepts](https://www.datacarpentry.org/organization-geospatial/) | Understand data structures and common storage and transfer formats for spatial data. |
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| [Introduction to R for Geospatial Data](https://www.datacarpentry.org/r-intro-geospatial) | Import data into R, calculate summary statistics, and create publication-quality graphics. |
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| [Introduction to Geospatial Raster and Vector Data with R](https://www.datacarpentry.org/r-raster-vector-geospatial) | Open, work with, and plot vector and raster-format spatial data in R. |
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