Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
5 Hour(s) 6 Minute(s)
Language
English
Rating
Course Overview
Applied course exploring practical uses of GIS and remote sensing in environment and wildlife conservation
Building on the foundational knowledge and skills you will have developed in the beginner's course, this course dives into more advanced applications of spatial analysis in wildlife and environment conservation. It's suitable for students who have completed the beginner's course, or who already have an intermediate level of GIS and looking to refresh or enhance their skills applied to the field of conservation.
Developed by Josef Clifford, an experienced GIS & remote sensing specialist, the course curriculum and content was developed in collaboration with scientists from the Wildlife Research and Training Institute (WRTI) in Kenya and the Zoological Society of London (ZSL) to ensure the content is rigorous and relevant.
Real data is used throughout, including GPS tracking data of Kenyan elephants, with hands-on activities to solve real-world problems. In addition, students will have access to a wide range of resources including an indispensable Google Earth Engine conservation code repository which can be easily adapted to conduct a wide range of remote sensing tasks.
We will cover a multitude of applications ranging from harnessing Google Earth Engine to access a range of environmental raster datasets, employing raster processing and analysis tools to develop a weighted habitat suitability map for forest elephants in Gabon, exploring digital elevation models (DEMs), and analysing spatial and temporal trends in climatic and environmental data.
We will introduce the essential theory of remote sensing, explore a range of open source datasets and conduct a variety of analyses such as calculating the Normalised Difference Vegetation Index (NDVI) anomaly to investigate vegetation health and charting trends to analyse the impacts of wildfires in Canada. Finally we will explore some additional workflows including habitat connectivity analysis in Linkage Mapper and home range analysis in R.
The course will primarily utilise QGIS as well as Google Earth Engine, plus R and other tools. Good luck and I hope you enjoy the course!
Course Content
- 6 section(s)
- 44 lecture(s)
- Section 1 Working with Raster Data
- Section 2 More Raster Data and Analysis Techniques
- Section 3 An Introduction to Remote Sensing
- Section 4 Remote Sensing Analysis for Conservation
- Section 5 Further GIS Tools for Conservation
- Section 6 Section 6: Final assignment
What You’ll Learn
- GIS, Remote sensing, Spatial analysis for conservation, Spatial analysis for environmental and ecological applications, Google Earth Engine basics, Remote Sensing analysis in QGIS and R, Master QGIS
Reviews
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SSwagat Sharma
Avery informative and interactive course.
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MMihailo Jovicevic
perfect for me now
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RRansford Hyman
I found that this course was really helpful in solidifying my understanding and practice of working with Remote Sensing. The course provides LOTS of resources for you to dive into on your time. The intro and integration of Google Earth Engine was very nicely done, although I felt some of the more advanced code examples could be broken down a bit more for clarity (i.e. Trend Analysis lecture was pretty dense). But the teacher for this course was very responsive with inquiries which was very nice! In my opinion, the R section was pretty limited and probably could either be expanded or left out. The analysis done in R can be done in QGIS so it didn't really display the usefulness of the R platform (I've used R in the past so I'm aware of the cool things you can do with it, but didn't get that understanding from the lecture videos). I think keeping it to QGIS and GEE is just fine. It's enough to deepen understanding of those technologies in one course. I find myself revisiting the content of this class and the Beginner's class as I continue on my GIS journey.
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AAlexander Gombe Mwazo
Yes... Am learning and eager to to work with GEE
