Introduction to remote sensing and GIS for ecological applications (IRMS01)
27 November 2017 - 1 December 2017£260.00 - £590
The course will deal with different aspects related to the use of remote sensing and GIS in spatial ecology by using the Free and Open Source Software GRASS GIS coupled with R. By the end of this 5-day practical course, attendees will have the capacity to deal with ecological patterns and processes by using GIS and remote sensing algorithms. The increasing availability of open ecological and geographical data through networks such as the Global Biodiversity Information Facility (GBIF, http://www.gbif.org) or the Data Observation Network for Earth (DataONE) federated data archive (http://www.dataone.org) makes it increasingly possible to test cutting-edge ecological theories. In using a shared open-source code for testing these ecological theories, researchers can be sure that their results are reliable and also that the code they have used is robust. Attendees will be able to process spatial and ecological data by free and open source algorithms. The course will be mainly practical, but grounded on robust theory. All the analyses will be performed in GRASS GIS and the code will be shared with attendees.
This course is oriented to MSc and PhD students and to Post-Doc researchers aiming at increasing their skills in self-programming GIS related algorithms.
We offer COURSE ONLY and ACCOMMODATION PACKAGES;
• COURSE ONLY – Includes lunch and refreshments.
• ACCOMMODATION PACKAGE (to be purchased in addition to the course only option) – Includes breakfast, lunch, dinner, refreshments, minibus to and from meeting point and accommodation. Accommodation is multiple occupancy (max 3 people) single sex en-suite rooms. Arrival Sunday 26th November and departure Friday 1st December PM.
To book ‘COURSE ONLY’ with the option to add the additional ‘ACCOMMODATION PACKAGE’ please scroll to the bottom of this page.
Other payment options are available please email firstname.lastname@example.org
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 PRinformatics must cancel this course due to unforeseen circumstances a full refund for the course will be credited. However PRinformatics cannot be held responsible for any travel fees, accommodation or other expenses incurred to you as a result of the cancellation.
Introduction to the main principles of GIS and remote sensing related to ecological studies. Practical labs will be dedicated to the development of code for solving ecological issue, such as spatial heterogeneity measurements, remote sensing data handling and management, spatial statistics.
Assumed quantitative knowledge
Basic knowledge in Geographical Information Systems and spatial analyses.
Assumed computer background
Familiarity with GIS software like GRASS GIS. Ability to visualise shapefiles and raster files. 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 of GRASS GIS installed.
UNSURE ABOUT SUITABLILITY THEN PLEASE ASK firstname.lastname@example.org
Meet at Margam Discovery Centre approx. 18:30 (Download directions PDF)
Monday 27th – Classes from 09:00 to 17:00
Day 1: Introduction to GIS and Remote Sensing concepts. a theoretical introduction to the main GIS and RS concepts.
Tuesday 28th – Classes from 09:00 to 17:00
Day 2: GRASS GIS: Introduction to the GRASS GIS software; Open source coding; main GIS analysis possibilities.
Wednesday 29th – Classes from 09:00 to 17:00
Day 3: Spatial Ecology and application of RS algorithms to solve ecological issues.
Thursday 30th – Classes from 09:00 to 17:00
Day 4: Use the GRASS GIS temporal framework to analyse big data.
Friday 1st – Classes from 09:00 to 16:00
Day 5: Throughput scripting in bash and python.