# Spatial data analysis with R Link to this page: siili.rahtiapp.fi/Rspatial_23 --- ### :link: Links * Coursepage: https://ssl.eventilla.com/rspatial_23 * Materials and exercises: https://github.com/csc-training/r-spatial-course * CSC Notebooks: https://notebooks.csc.fi/ --- ### :calendar: Program All times Helsinki summer time, that is EEST (UTC+3). **Wednesday 10.05.2023** 9:00-10:30 Handling and plotting vector data in R 10:45-12:00 Handling and plotting cont. 13:00-14:30 Spatial operations (intersection, clipping, conversions etc) 14:45-16:00 Spatial operations cont. **Thursday 11.05.2023** 9:00-10:30 Spatial analysis of vector data (clustering, density surfaces, autocorrelation) 10:45-12:00 Spatial analysis cont. 13:00-14:15 Visualizing spatial data 14:30-16:00 Raster basics with R **Friday 12.05.2023** 9:00-10:30 Raster data manipulation 10:45-12:00 Map algebra 13:00-14:30 Spatial modelling with raster data 14:45-15:30 Intro Spatio-Temporal Asset Catalogs (STAC) and how to use them from R. Kylli Ek (CSC) 15:30-16:00 [Mini-intro to possibilities of using R in CSC's supercomputer Puhti](https://a3s.fi/gis-courses/r_spatial/2305_Rspatial.html). Samantha Wittke (CSC) --- ### Course environment 1) Go to https://notebooks.csc.fi/ 2) Finnish university and research institute users should be able to login with Haka or VIRTU. For users from non-Finnish institutions we will provide a separate username and password during the course (“Special Login”) 3) In the Notebooks dashboard click the “Join workspace” button in the upper left corner, and copy-paste there the join code `rsp-b7bij1x1` 4) You should now see "Spatial data analysis with R" RStudio Notebook appear in the list: start the application (opens in new tab). 5) Find the terminal tab, next to the console tab within RStudio. 6) Switch to `my-work` directory and copy the course materials there: ``` cd my-work git clone https://github.com/csc-training/r-spatial-course.git ``` 7) You can now find the course materials from the Files panel under `my-work/r-spatial-course`. ### Own course environment (optional!) If you want to set up your own course environment on your own computer, you will need to install RStudio and all packages mentioned in https://github.com/csc-training/r-spatial-course/blob/main/install_packages.sh . For the STAC part, you in addition need `rstac`, `httr` and `gdalcubes`. Then clone the course repository (`git clone git@github.com:csc-training/r-spatial-course.git`) and you are good to go :) ### Day 3. STAC [Slides](https://a3s.fi/gis-courses/r_spatial/CSC_STAC_2023_05_12.pdf) ### Hands-on instructions: 1) Copy the example file to RStudio. Open Terminal and give these commands: ``` mkdir ~/my-work/stac cd ~/my-work/stac wget https://raw.githubusercontent.com/csc-training/geocomputing/master/R/STAC/STAC_CSC_example.R ``` 2) Open the new RScript in RStudio from `stac` folder. 2) In R script change the path setting in row 45: ``` setwd('~/my-work/stac') ``` 4) Run the script section-by-section. 4) Do not run rows 202-220, not enough memory in Notebooks. ## Questions and Answers * is this how to ask questions? * yes, and here is an answer! * great!