Data Carpentry lesson to understand data structures and common storage and transfer formats for spatial data. The goal of this lesson is to provide an introduction to core geospatial data concepts. It is intended for learners who have no prior experience working with geospatial data, and as a pre-requisite for the R for Raster and Vector Data lesson . This lesson can be taught in approximately 75 minutes and covers the following topics: Introduction to raster and vector data format and attributes Examples of data types commonly stored in raster vs vector format Introduction to categorical vs continuous raster data and multi-layer rasters Introduction to the file types and R packages used in the remainder of this workshop Introduction to coordinate reference systems and the PROJ4 format Overview of commonly used programs and applications for working with geospatial data The Introduction to R for Geospatial Data lesson provides an introduction to the R programming language while the R for Raster and Vector Data lesson provides a more in-depth introduction to visualization (focusing on geospatial data), and working with data structures unique to geospatial data. The R for Raster and Vector Data lesson assumes that learners are already familiar with both geospatial data concepts and the core concepts of the R language.
- Subject:
- Applied Science
- Computer Science
- Information Science
- Mathematics
- Measurement and Data
- Material Type:
- Module
- Provider:
- The Carpentries
- Author:
- Anne Fouilloux
- Chris Prener
- Dev Paudel
- Ethan P White
- Joseph Stachelek
- Katrin Leinweber
- Lauren O'Brien
- Michael Koontz
- Paul Miller
- Tracy Teal
- Whalen
- Date Added:
- 08/07/2020