byandell / geospatial

Geospatial Carpentries Workshop Play area

geospatial

Yandell's Geospatial Workshops Play Area

This is now a library. Note that all needed packages are listed as Depends except basemapR. You can install as follows without cloning the library:

devtools::install_github('Chrisjb/basemapR')
devtools::install_github('byandell/geospatial')

There is a draft shiny app for the redline example at this point, which will mature. Try

library(geospatial)
redlineApp()

See slide deck for ESIIL Geospatial R Package.

Geospatial Resources

Books and Online Docs

• Data Carpentry Workshop

  • Introduction to R for Geospatial Data
  • Introduction to Geospatial Concepts
  • Introduction to Geospatial Raster and Vector Data with R

• Spatial Data Science book by Edzer Pebesma and Roger Bivand

• Geospatial Vector Data in R with SF (Coding Club)

• Online Comparisons of Some Spatial Packages

  • Comparison of terra and stars packages by Chris Brown
  • Marius Appel - Creating and Analyzing Multi-Variable Earth Observation Data Cubes in R (part 1) (2 hours)
  • Stack Overflow: stack geotiff with stars 'along' when 'band' dimension contains band + time information

• ArcGIS Online

  • Free online accounts, with new features added over time

• QGIS

  • RPubs: R to QGIS workflow
  • Spatial stratified sampling with RStudio and QGIS
  • RQGIS, Utilizing Rstudio as an alternative GIS
  • Processing lidar data using QGIS, LAStools and R
  • ESCAP: Land cover change maps with QGIS & RStudio
  • Columbia U: GIS, Cartographic and Spatial Analysis Tools in R / Rstudio

R Packages

Packages to Create Data Cube Layers

• gdalcubes
  • https://github.com/appelmar/gdalcubes
  • 1. Creating data cubes from local MODIS imagery by Marius Appel
• https://r-spatial.org/
  • sf (https://github.com/r-spatial/sf)
  • starshttps://github.com/r-spatial/stars
• https://rspatial.org/
  • terra (https://github.com/rspatial/terra)
  • sf (https://github.com/rspatial/raster)
• tidyterra
  • https://dieghernan.github.io/tidyterra/
  • Extension of the 'tidyverse' for 'SpatRaster' and 'SpatVector' objects of the 'terra' package

Packages to Access Data

• rstac: Access, search and download from SpatioTemporal Asset Catalog (STAC)
• osmdata: Download and import of 'OpenStreetMap' ('OSM') data
  • https://www.openstreetmap.org/
  • Open Street Map Data
  • Retrieving Open Street Map data using the osmdata package
  • Database of Open Street Map Names
  • https://osmnames.org/
• geos: R API to the Open Source Geometry Engine ('GEOS')
• landsat: Processing of Landsat and other multispectral satellite imagery

Previous package rgdal is now obsolete. Unsure about status of raster package.

Data Repositories

• https://data-library.esiil.org
  • American Indian and Alaska Native Areas
• See list on menu of https://cu-esiil.github.io/hackathon2023_datacube/code_for_building_cube/Pull_flood_data/

These have been compiled in datasets.csv.

Data are stored in different coordinating systems, which makes it important to transform between them. Some common ones:

• EPSG:4326: WGS84 = World Geodetic System 1984
• EPSG:32618: WGS84 for UTM zone 18N (North America)
• EPSG:32730: WGS84 for UTM zone 20S (South America)

Geospatial Workshops

ESIIL Hackathon, CU Boulder, November 15-17, 2023

ESIIL_Art_Data_Cube.Rmd: Yandell edit of Ty Tuff's The Art of Making a Datacube

Geospatial Data Carpentry Workshop, UW-Madison, June 5-8, 2023 https://go.wisc.edu/i4gsfr

Carpentries Etherpad

Geospatial.Rmd: Rmarkdown from Workshop

Geospatial Download for Data Carpentry Workshop

The data have been organized in The Carpentries nicely in FigShare as workshop data from carpentries site. See also the https://datacarpentry.org/geospatial-workshop/ page section on Data and more information at https://datacarpentry.org/geospatial-workshop/data.html. The data seem to come from NEON Raster Intro page NEON Raster 00: Intro to Raster Data in R, via Download Dataset. The data are from two field sites:

• Harvard Forest (HARV)
• San Joaquin Experimental Range (SJER)

The key raster data are the following "geotif" files:

• HARV_dsmCrop.tif
• HARV_dsmCrop.tif
• HARV_DSMhill.tif

It should be possible using some of the commands in the The art of making a data cube to elegantly download needed data on the fly.