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R studio 8.12 registration key4/5/2024 ![]() Qmd file and stitched HTML notebook, but I don’t expect you to use GitHub. For the Conservation Biology students, the project will count 50% (10% lightning talk, 40% project).You’re welcome to do this in a Git Repository (nudge nudge), now that we’ve completed the Reproducible Research module. For the Honours students, the project will count 70% of your mark for the module and will be due on Friday the 1st March.For the Conservation Biology MSc course, we’ll do lightning talk presentations on Friday at 10AM.Īfternoons are self-study time where you will incrementally develop your own individual GIS project in R and RMarkdown or Quarto.For the Honours students, Thursday afternoon, 2-4PM, will be lightning talk presentation day (venue TBD).Lectures will be held in the mornings between 10:00 to 12:00 Monday to Thursday in BIOLT1. This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. Any feedback, positive or negative, is welcome! If there is any content you find concerning with regard to licensing, or that you find offensive, please contact me. Content without attribution is my own and shared under the license below. I have only used images etc that were made available online under a non-restrictive license (Creative Commons, etc) and have attributed my sources. Pebesma and Bivand’s Spatial Data ScienceĪll code, images, etc can be found here.Ryan Garnett’s cheatsheet for library(sf).Lovelace et al’s online book Geocomputation with R.These course notes borrow or paraphrase extensively from Adam Wilson’s GEO 511 Spatial Data Science course, Manny Gimond’s Intro to GIS & Spatial Analysis and the 2020 series of GIS Lecture Lunches by Thomas Slingsby and Nicholas Lindenberg from UCT Library’s GIS Support Unit. Some idea of how to help yourself or find help when you inevitably come unstuck….Some hints and resources to help you teach yourself R.Some familiarity with handling spatial data in R.Highlight some of the common problems and pitfalls when using GIS.Some familiarity with GIS jargon and technical terms.Some familiarity with GIS and what it can help you achieve.The core outcomes I hope you’ll come away with: I’ll focus on giving you a broad overview and some idea of how to teach yourself (using R). GIS is a field of research that many people dedicate their entire lives to, yet we only have a week, so this really is a minimalist introduction. The goal is to give you a very brief introduction to Geographic Information Systems (GIS) in general and some familiarity with handling spatial data in R. 9 (Old!) Raster GIS operations in R with raster.8.15 Obtaining satellite data from APIs.8.14 Cloud Optimized GeoTiffs (COGs)!!!.8.13 Visualizing multiple datasets on one map.8 Raster GIS operations in R with terra.7.10 Interactive maps with leaflet and mapview.7.8 Converting a dataframe into a spatial object.7.7 Calling iNaturalist locality (point) data from R.7.6 Combine classes and dissolve by attribute.5.2.4 “On the fly” vs manual projection.5.2.1 Geographic (or “unprojected”) Coordinate Systems.
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