Introduction to remote sensing and GIS for ecological applications (IRMS01)
21 May 2018 - 25 May 2018£260.00 - £490
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.
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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 firstname.lastname@example.org 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.
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Meet at SCENE field station approx. 18:30 (Download directions PDF)
Monday 21st – 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.
MODULE 1: Introduction to GIS This module will be devoted to the introduction to GIS concepts; reference systems; data types; main GIS analysis tool
MODULE 2: Introduction to Remote Sensing An introduction to remote sensing concepts; main data handling through R packages
Tuesday 22nd – Classes from 09:00 to 17:00
Day 2: GRASS GIS: Introduction to the GRASS GIS software; Open source coding; main GIS analysis possibilities.
MODULE 3: GRASS GIS introduction This session will show the basics of GRASS GIS, it will be an intuitive mix of theoretical and hands-on sections. In the former, we will introduce the participants to some specific concepts of GRASS GIS, like its database structure, location, mapset and region and will show how simple the approach really is. During the hands-on part, the participants will learn how to use common geographical data formats in GRASS GIS, starting from simple actions like adding data into the GRASS GIS environment and displaying it
MODULE 4: GRASS GIS analysis Different basic GIS operations will be carried out using raster (like DTM analysis, reclassification, map algebra) and vector (buffering, overlay, database operation). During this session we will use different GRASS GIS interfaces, the Graphical and the command line
Wednesday 23rd – Classes from 09:00 to 17:00
Day 3: Spatial Ecology and application of RS algorithms to solve ecological issues.
MODULE 5: Spatial Ecology and application of RS algorithms to solve ecological issues Main tools to perform RS data analysis from an ecological perspective; remote sensing data handling; band combination through indices; multivariate analysis of remote sensing data; analysis of the heterogeneity of the landscape
Thursday 24th – Classes from 09:00 to 17:00
Day 4: Use the GRASS GIS temporal framework to analyse big data.
MODULE 6: Temporal GRASS GIS
Since GRASS GIS version 7.0 a new framework to handle time series data. The temporal framework (TGRASS) enabled GRASS introduces three new data types, and they can be managed, analyzed and processed with temporal modules that are based on the GRASS GIS temporal framework.
Friday 25th – Classes from 09:00 to 16:00
Day 5: Throughput scripting in bash and python.
MODULE 7: Bash scripting
MODULE 8: Python scripting Since GRASS GIS version 7.0 there are two main Python libraries included, during this session you will use most of Python GRASS GIS capabilities.