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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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|[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. |
|[Introduction to Geospatial Concepts](https://datacarpentry.org/organization-geospatial/) ([instructor notes](https://datacarpentry.org/organization-geospatial/guide/index.html)) |**75 minutes** - estimated, will not be accurate | Learners have no experience with geospatial data. |
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|[Introduction to R for Geospatial Data](https://datacarpentry.org/r-intro-geospatial/) ([instructor notes](https://datacarpentry.org/r-intro-geospatial/guide/index.html)) |**4 hours** - estimated, will not be accurate | Learners have no experience with R. |
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|[Introduction to Geospatial Raster and Vector Data with R](https://datacarpentry.org/r-raster-vector-geospatial/) ([instructor notes](https://datacarpentry.org/r-raster-vector-geospatial/guide/index.html)) |**7 hours** - estimated, will not be accurate | Always. |
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|[Introduction to Geospatial Concepts](https://datacarpentry.org/organization-geospatial/) ([instructor notes](https://datacarpentry.org/organization-geospatialinstructor/instructor-notes.html)) |**75 minutes** - estimated, will not be accurate | Learners have no experience with geospatial data. |
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|[Introduction to R for Geospatial Data](https://datacarpentry.org/r-intro-geospatial/) ([instructor notes](https://datacarpentry.org/r-intro-geospatialinstructor/instructor-notes.html)) |**4 hours** - estimated, will not be accurate | Learners have no experience with R. |
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|[Introduction to Geospatial Raster and Vector Data with R](https://datacarpentry.org/r-raster-vector-geospatial/) ([instructor notes](https://datacarpentry.org/r-raster-vector-geospatialinstructor/instructor-notes.html)) |**7 hours** - estimated, will not be accurate | Always. |
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If the workshop audience is experienced in both R and geospatial concepts, this workshop could theoretically be taught in one day. However, note that these timings are estimates and we are relying on feedback from pilot workshop Instructors to add accurate timing information.
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#### Installation
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- For the [Introduction to Geospatial Raster and Vector Data with R](https://datacarpentry.org/r-raster-vector-geospatial/) lesson, learners MUST download the data and install the software before the workshop. The data set is large (>150 Mb) and there are numerous software packages and R libraries to install. **Remind your learners multiple times!**
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- Instructions to download data and set up a machine to analyze and process geospatial data: [http://datacarpentry.org/geospatial-workshop/setup.html](https://datacarpentry.org/geospatial-workshop/setup.html)
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- Instructions to download data and set up a machine to analyze and process geospatial data: [http://datacarpentry.org/geospatial-workshop/setup.html](https://datacarpentry.org/geospatial-workshop/index.html#setup)
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- You may find it helpful to host an "install party" prior to your workshop where you and your co-instructors help learners install the necessary software for the workshop. If this is unfeasible, leave time at the beginning of your workshop to ensure that learners have necessary geospatial software (GDAL, GEOS, PROJ.4) installed prior to teaching the course.
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[Instructors: add information about supporting learners with installation here]
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The installation of the geospatial libraries GDAL, GEOS, and PROJ.4 varies significantly based on operating system. These are all dependencies for `sf`, the `R` package that we will be using for spatial data operations throughout this workshop.
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## Windows
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To install the geospatial libraries, install the latest version [RTools](https://cran.r-project.org/bin/windows/Rtools/)
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## macOS - Install with Packages (Beginner)
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## macOS - Install with Homebrew (Advanced)
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## Linux
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Linux users will have to install UDUNITS separately. Like the geospatial libraries discussed above, this is a dependency for the `R` package `sf`. Due to conflicts, it does not install properly on Linux machines when installed as part of the `sf` installation process. It is therefore necessary to install it using the command line ahead of time.
Participants who do not already have `R` installed should download and install it.
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## Windows
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To install `R`, Windows users should select "Download R for Windows" from RStudio and CRAN's [cloud download page](https://cloud.r-project.org), which will automatically detect a CRAN mirror for you to use. Select the `base` subdirectory after choosing the Windows download page. A `.exe` executable file containing the necessary components of base R can be downloaded by clicking on "Download R 3.x.x for Windows".
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## macOS
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To install `R`, macOS users should select "Download R for (Mac) OS X" from RStudio and CRAN's [cloud download page](https://cloud.r-project.org), which will automatically detect a CRAN mirror for you to use. A `.pkg` file containing the necessary components of base R can be downloaded by clicking on the first available link (this will be the most recent), which will read `R-3.x.x.pkg`.
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## Linux
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Please be aware that the `R` package `rasterVis` is not included in the `rocker/geospatial` Docker image. If your instructor teaches with this package then you will need to install this `R` package yourself. All other `R` packages will already be installed for you.
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## Downloading and Installing Docker Community Edition
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## Using the `rocker/geospatial` Docker Image via the Command Line
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## Using the `rocker/geospatial` Docker Image via Kitematic
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