4.75 (10 reviews)
☑ Students will gain access to and a thorough knowledge of the QGIS, TrendsEarth and Google Earth Engine platform
☑ To apply a range of environmental & time series analysis in QGIS and Earth Engine
☑ Implement land degradation mapping, flood monitoring, land cover analyis and more on the cloud
☑ Learn basics of Remote Sensing and how to apply Remote Sensing analysis in open-source tools
☑ You'll have a copy of the codes used in the course for your reference
☑ Complete your independent environmental application project using geospatial approaches in QGIS and Google Earth Engine
QGIS & Google Earth Engine for Environmental & Land Applications
This course is designed to take users who use GIS for basic geospatial data/GIS/Remote Sensing analysis to perform environmental analysis (land degradation monitoring, floods mapping, land cover change monitoring, land productivity, etc) with Big Data on the cloud using both QGIS capabilities and Google Earth Engine! The course will also focus on introducing you to sustainable development goals (SDG) indicators computation using the TrendsEarth plugin in QGIS. I will also introduce you to user-intuitive cloud computing using EO-browser!
This course provides you with all the necessary knowledge to start and advance your skills with Geospatial analysis and includes more than 5 hours of video content, plenty of practical analysis, and downloadable materials. After taking this course, you will be able to implement PRACTICAL, real-life spatial geospatial analysis for environmental applications, and tasks with the Big Data on the cloud and in QGIS.
This course is designed to equip you with the theoretical and practical knowledge of applied geospatial analysis, namely Remote Sensing and some Geographic Information Systems (GIS). This course emphasizes the importance of understanding:
- Foundation of Remote Sensing in open-source tools (QGIS, Google Earth Engine)
- Working with the open-source GIS software & tools (QGIS, Google Earth Engine, Trends. Earth, Semi-Automated classification Plugin)
- Learning how to conduct GIS / Remote Sensing analysis for environmental applications (such as land degradation monitoring, floods mapping, land cover change monitoring, and so on)
One important part of the course is the practical exercises. You will be given some precise instructions, codes, and datasets to create for geospatial analysis in Google Earth Engine.
INCLUDED IN THE COURSE: You will have access to all the data used in the course, along with the scripts. You will also have access to future resources. Enroll in the course today & take advantage of these special materials!
Course Motivation - Sustainable Development Agenda
EO for environmental applications and sustainable development
Introduction to software used in this course: QGIS and Google Earth Engine
About open-source QGIS software
Lab 1: QGIS installation
Trends.Earth Plugin for QGIS
Installation of Trends.Earth Plugin
Why to work with Google Earth Engine?
Lab: Sign up for Google Earth Engine
Remote Sensing Crash Course
Introduction to satellite images
Sensors and Platforms
How to work with the Remote Sensing images: preprocessing
Installation of Semi-Automated LCassification PlugIn
Lab 2: Layerstacking, True and False Colour composites
Lab 3: Image preprocessing - atmospheric correction
Sources of Remote Sensing images for LULC mapping
QGIS for Land Applications & Indicators assessment
Introduction to sustainable agenda and Land Degradation
Register in Trends.Earth Plugin
Downloading geospatial data with Trends.Earth Plugin -Example of Land Cover Data
How to load downloaded data to QGIS - Example of Land Cover Product from ESA
Where to get help on Trends.Earth
Lab: Land degradation assessment in QGIS with Trends.Earth - Hands-On
Computation of SDG 15.3.1 Land Degradation Indicator, statistics & reporting
Time series trend analysis with NDVI MODIS data in QGIS
Your Independent Project
Basics of Jave Scrips for Google Earth Engine and first steps in image analysis
Interface of Google Earth Engine: Code Editor & Explorer
Lab: Mapping and Reducing Collection - Landsat Example
Lab: Working with image collections and image visualization
Lab: Image Calculations - Create a composite and calculate NDVI
Lab: Short introduction to functions - Maximum NDVI Example
Lab: Export image data from Google Earth Engine
Environmental Applications on the cloud: Google Earth Engine & EO browser
Using EO browser for image download, spectral indices & land cover analysis
Working with spatial data and remote sensing images - repeat
Floods mapping Part 1 - Image preprocessing
Using NDWI for flood monitoring
Flood Mapping Part 2: NDWI
Assignment: Flood Mapping
Great content, I learned a lot about both QGIS and Google Earth Engine. This definitely will help me in my studies at the Uni.
Very informative course on Remote Sensing applications. I loved that it is made in the newest QGIS version and up to date!
That’s another brand new and amazing course from the instructor. It covers the part of the application, showing how geospatial analysis could be done in QGIS and Earth Engine! Very exciting content.