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Updated in [August 21st, 2023]

What skills and knowledge will you acquire during this course?
By taking the course "Geospatial Analyses & Remote Sensing: from Beginner to Pro," learners will acquire the following skills and knowledge:

1. Theoretical and practical understanding of applied geospatial analysis, including Remote Sensing and Geographic Information Systems (GIS).
2. Proficiency in using popular open-source GIS software, specifically QGIS, and its tools such as the Semi-Automated Classification Plugin and Orfeo (OTB) toolbox.
3. Knowledge of machine learning applications in GIS and Remote Sensing technology, including the use of machine learning algorithms for various geospatial tasks such as land use and land cover mapping, object-based image analysis, and change detection.
4. Ability to download and process satellite imagery for analysis.
5. Competence in conducting supervised and unsupervised learning for classification of satellite imagery.
6. Understanding of accuracy assessment techniques for evaluating the quality of geospatial analysis results.
7. Familiarity with cloud computing and big data analysis using Google Earth Engine for geospatial tasks.
8. Practical experience in completing a classification project using machine learning, cloud computing, and big data analysis in QGIS and Google Earth Engine.
9. Confidence in using state-of-the-art machine learning algorithms to create land cover and land use maps in QGIS and Google Earth Engine.
10. Application of practical exercises, including downloadable materials, scripts, and datasets, to enhance understanding and proficiency in geospatial analysis and remote sensing.

How does this course contribute to professional growth?
This course, "Geospatial Analyses & Remote Sensing: from Beginner to Pro," contributes to professional growth by providing theoretical and practical knowledge of applied geospatial analysis, specifically in the areas of Remote Sensing and Geographic Information Systems (GIS). By completing this course, professionals will gain the skills and confidence to implement practical, real-life spatial geospatial analysis and tasks using popular and free software tools. The course covers topics such as land use and land cover mapping, machine learning for GIS, data and map creation, and object-based image analysis. Professionals in fields such as geography, programming, social science, geology, and GIS and Remote Sensing will benefit from this course and gain a deeper understanding of Machine Learning in GIS and Remote Sensing, as well as proficiency in using QGIS software and Google Earth Engine for geospatial analysis. The practical exercises and downloadable materials provided in the course further enhance the learning experience and enable professionals to apply their knowledge in real-world scenarios.

Is this course suitable for preparing further education?
Yes, this course is suitable for preparing further education in geospatial analyses and remote sensing.

Course Syllabus

Introduction to the course, GIS and Remote Sensing

Software used in this course

Basics of GIS

Introduction to Remote Sensing (theory)

Practicals: basics of satellite image analysis (Remote Sensing) in QGIS

Basics of land use and land cover (LULC) mapping (theory)

Practicals: Image CLassification in Semi-Automated Classification Plugin in QGIS

Introduction to change detection in QGIS

Image Classification in Google Earth Engine

Introduction to Machine Learning in GIS

Machine Learning and Object-based Analysis (OBIA) in GIS: part 2

BONUS