GIS and Remote Sensing analyses with R (GARM01)
21 October 2019 - 25 October 2019£515.00
The course will cover the basics to perform spatial analyses using R as a Geographical Information System (GIS) platform and Remote Sensing as main data source. The course will provide a brief theoretical background of GIS tools and Remote Sensing data and techniques. By the end of this 5-day practical course, attendees will have the capacity to search satellite imagery, to manipulate Remote Sensing data, to create new variables, as well as to choose the best spatial tools and techniques to perform spatial analyses and interpret their results.
The course will be mainly practical, with some theoretical lectures. All modelling processes and calculations will be performed with R, the free software environment for statistical computing and graphics (http://www.r-project.org/). Attendees will learn to use the Rpackage RSToolbox for Remote Sensing image processing and analysis such as calculating spectral indices, principal component transformation, or unsupervised and supervised classification.
This course is orientated to PhD and MSc students, as well as other students and researchers working on biogeography, spatial ecology, or related disciplines.
PLEASE READ – CANCELLATION POLICY: Cancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered, contact email@example.com. Failure to attend will result in the full cost of the course being charged. In the unfortunate event that a course is cancelled due to unforeseen circumstances a full refund of the course fees (and accommodation fees if booked through PR statistics) will be credited. However, PR statistics will not be held responsible/liable for any travel fees, accommodation costs or other expenses incurred to you as a result of the cancellation. Because of this PR statistics strongly recommends any travel and accommodation that is booked by you or your institute is refundable/flexible and to delay booking your travel and accommodation as close the course start date as economical viable.
Introductory lectures on the concepts and applications of GIS and Remote Sensing.
Practical lectures on most used spatial tools. Presentations and round-table
discussions about the analysis requirements of attendees (option for them to bring
their own data). Data sets for computer practical modules will be provided by the
instructor, but participants are welcome to bring their own data.
Assumed quantitative knowledge
Basic knowledge in Geographical Information Systems, Remote Sensing, and spatial
Assumed computer background
Familiarity with R. Ability to import/export data, manipulate data frames, fit basic statistical models & generate simple exploratory and diagnostic plots.
Equipment and software requirements
A laptop/personal computer with a working version or R and RStudio installed. R and RStudio are supported by both PC and MAC and can be downloaded for free by following these links
UNSURE ABOUT SUITABLILITY THEN PLEASE ASK firstname.lastname@example.org
Monday 21st – Classes from 09:00 to 17:00
Theory – Introduction to GIS.
Practical – Introduction to GIS with R: Import and plot data.
Theory – Coordinate systems.
Practical – Projecting vectorial & raster files.
Tuesday 22nd – Classes from 09:00 to 17:00
Theory – Vector database operations.
Practical – Attribute and spatial queries: join/merge, filter/subset, select by attribute, select by
location, summarize, add/calculate new attributes (columns), plot attributes.
Theory – Vector analyses.
P: Vector analyses – buffer, merge, dissolve, intersect, union, select, calculate areas.
Wednesday 23rd – Classes from 09:00 to 17:00
Theory – Raster GIS.
Practical – Raster analyses: rasterize, crop, mask, merge, distance surface, zonal statistics.
Theory – Introduction to Remote Sensing. RS as main data source: RS sensors & variables.
Practical – Getting and plotting RS data. Downloading, reading, and plotting RS data in R.
Manipulating satellite data.
Thursday 24th – Classes from 09:00 to 17:00
Theory – Working with RS variables. Image classification, Vegetation indexes, data fusion.
Practical – Calculating RS variables with RStoolbox: Vegetation indexes and classification
Theory: Remote Sensing applications to biology
Practical: Statistical analyses with RS data
Friday 25th – Classes from 09:00 to 17:00
“PR-statistics offers a variety of courses, but ‘Introduction to Ecological Niche Modelling’ taught by an esteemed researcher of the field, Dr. Neftali Sillero, is definitely (either in their early in career or more experienced) a course any ecologist should attend.
The course started with a smooth and gentle introduction to the underlying principles of ecological niche modelling and provided a solid basis of how to build, test and evaluate an ecological niche model from start to finish. The instructor also took special care to point out which are the caveats you need to take care of when dealing with this kind of analysis. Dr. Sillero was always keen to answer our questions and attend to our needs and he even had time to discuss the problems we were facing with our own data (which ranged from plant/animal ecology to disease mapping).
It is an ideal course for anyone interested in species distribution modelling, either experienced or not, since it constitutes an extremely thorough and detailed step-by-step guide of how to approach the ever-growing ENM field. At least for me, it clarified a lot of concepts and I now feel confident about my modelling methodology.
Finally, Dr. Oliver Hooker, the heart and soul of PR-statistics, ensured that our stay in the Scottish Centre of Ecology and the Natural Environment (SCENE) would be as nice as possible and that we only had to worry about attending the lectures and nothing else. It was a memorable and fulfilling experience participating in the ENM course and I strongly recommend attending it.”
Kostas Kougioumoutzis, Ecologist
(Attended ENMR course)