Overview

Geographic Information Systems (GIS) encompass data, methods and software to collect, represent and analyse spatial data in a myriad of ways. GIS operations can also be carried out in R, thus allowing seamless integration with other R scripts for data visualization and analysis. This course will include both basic theoretical lessons and practical hands-on sessions on the use of R as a GIS, for automated and reproducible mapping and analysis of spatial environmental data.

 

Target audience and assumed background

The course is aimed at researchers and practitioners at any career stage with an interest in the mapping and spatial analysis of biodiversity and/or other environmental data, and who would like to have their procedures scripted in a reproducible and automatable way. Participants should be accustomed to working with computers. Previous basic experience with R is strongly recommended and will make the practicals much less of a struggle. . All R scripts will be provided and explained in detail.

Learning outcomes

By the end of this course, participants will be able to:
‒    Know the basics of GIS, mapping and cartographic projections
‒    Gather spatial data, import them into R and produce maps using scripts
‒    Perform several types of spatial analyses in R
‒    Plot and export maps with the results of these analyses

Daily schedule:
15:00 - 18:00 (Berlin time): live lectures and introduction to / review of the practicals

4 additional hours: self-guided practicals using annotated scripts, with live remote support from 09:00 to 23:00 (Berlin time) to cover the participants' time zones

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Monday – Lectures from 15:00 to 18:00 + 4 hours practicals

- Introduction to cartography and GIS
- Spatial data types: vector, raster and beyond
- Spatial scale: resolution and extent
- Cartographic projections and coordinate systems
- Spatial data file formats
- Obtaining GIS data: online data sources
- Introduction to GIS with R: available packages
- Importing, exporting and plotting maps and spatial data with R
- Mapping spatial and non-spatial attributes
- Customizing map colours and symbols

Tuesday – Lectures from 15:00 to 18:00 + 4 hours practicals

- Managing and manipulating spatial data in R
- Vector GIS operations: filter, subset, select by attribute, select by location, clip, overlay, dissolve, aggregate, disaggregate, join geometries, join attributes, simplify geometry, get centroids
- Raster GIS operations: crop, mask, aggregate / disaggregate (change spatial resolution), reclassify, combine / stack, resample, convert raster map(s) to values table

Wednesday – Lectures from 15:00 to 18:00 + 4 hours practicals

- Spatial analysis with vector maps: distance, buffer, Voronoi polygons / tessellation / Delauney triangulation, random points, vector grids, overlay, intersect, points in polygon, compute line lengths and polygon areas
- Spatial analysis with raster maps: detect patches and boundaries; create a viewshed; terrain analysis: slope, aspect, roughness, hill shade; spatial autocorrelation; moving window / focal analysis; map algebra

Thursday – Lectures from 15:00 to 18:00 + 4 hours practicals

- Raster-vector interactions: rasterize, vectorize; distance surface, cost distance, least cost path; contour lines; interpolate; extract raster values to points, lines or polygons

Friday – Lectures from 15:00 to 18:00

- The sky is the limit: overview of additional specialized GIS applications in R
- Obtaining and cleaning species occurrence data
- Obtaining and managing environmental data
- Cartograms
- Interactive maps
- 3D maps

Cancellation Policy:

> 30  days before the start date = 30% cancellation fee

< 30 days before the start date= No Refund.

Physalia-courses cannot be held responsible for any travel fees, accommodation or other expenses incurred to you as a result of the cancellation.