Machine Learning in GIS : Land Use Land Cover Image Analysis

Become Expert in advanced Remote Sensing and GIS pixel- and object-based image analysis in Google Earth Engine & QGIS

Created by: Kate Alison
GIS & Data Science

What Will I Learn?

• Fully understand advanced methods of Land use and Land Cover (LULC) Mapping in QGIS and Google Earth Engine
• Learn how to perform such advanced methods as object based image analysis (OBIA) and object-based classification using real-world data in QGIS
• Further advanced your skills in the most popular open-source GIS and Remote Sensing software tools (QGIS)
• Learn how to obtain satellite data, apply image pre-processing, create training and validation data for OBIA in QGIS and Google Earth Engine
• Apply advanced Machine Learning image classification algorithms
• Create and download LULC maps for your report
• Explore the power of Google Earth Engine for image analysis
• You'll also have plenty of handy hints and tips will be provided alongside the code to prevent glitches
• You'll have a copy of the labs’ step-by-step manuals used in the course for your reference to use in your analysis.

Requirements

• A vivid interest in working with geospatial data
• Basic knowledge of manipulating spatial (image) data using QGIS
• A working computer with internet connection
• The course will be demonstrated using a QGIS version of Windows PC. Mac and Linux users will have to adapt the instructions to their operating systems.

Target audience

• Geographers, Programmers, geologists, biologists, social scientists, or every other expert who deals with GIS maps in their field