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Introduction to Geospatial Concepts
Unrestricted Use
CC BY
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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
Introduction to Geospatial Raster and Vector Data with R
Unrestricted Use
CC BY
Rating
0.0 stars

Data Carpentry lesson to open, work with, and plot vector and raster-format spatial data in R. The episodes in this lesson cover how to open, work with, and plot vector and raster-format spatial data in R. Additional topics include working with spatial metadata (extent and coordinate reference systems), reprojecting spatial data, and working with raster time series data.

Subject:
Applied Science
Computer Science
Information Science
Mathematics
Measurement and Data
Material Type:
Module
Provider:
The Carpentries
Author:
Ana Costa Conrado
Angela Li
Anne Fouilloux
Brett Lord-Castillo
Ethan P White
Joseph Stachelek
Juan F Fung
Katrin Leinweber
Klaus Schliep
Kristina Riemer
Lachlan Deer
Lauren O'Brien
Marchand
Punam Amratia
Sergio Marconi
Stéphane Guillou
Tracy Teal
zenobieg
Date Added:
08/07/2020