Start with Google Earth Engine & Spatial Analysis #Beginners
What you'll learn
- Students will gain access to and a thorough knowledge of the Google Earth Engine platform
- Get introduced to JavaScript skills on Google Earth Engine platform
- Learn how to calculate spectral indices and work with Big data on cloud
- Learn image classification (land cover mapping) basics in Earth Engine Explorer
- Get introduction to Remote Sensing and satellite images
- Understand how to work with satellite images on the desktop computer and on the cloud
Requirements
- A working computer with internet connection
- SOme knowledge of Remote Sensing / GIS would be an advantage
Description
Start with Google Earth Engine & Spatial Analysis #Beginners
This course is designed to take users who use GIS for basic geospatial data/GIS/Remote Sensing analysis to perform geospatial analysis tasks with Big Data on the cloud! This course provides you with all the necessary knowledge to start with Remote Sensing and Geospatial analysis in Google Earth Engine.
We will start with a thorough introduction to the Earth Engine Platform, then move to the basics of satellite image and image analysis (which is essential to understand when you would like to work with Earth Engine) and then move to a comprehensive overview of JavaScript basics for spatial analysis. We will cover essential blocks to equip you with the background knowledge and get you started with your analysis on the cloud.
Please, note: this is an introductory course with the main focus on Google Earth Engine. I do explain some basics of Remote Sensing, but it is not the main topic of this course.
By the end of the course, you will feel confident and understand the basics of JavaScript for spatial analysis with Big Data on Google Earth Engine cloud. This course will also prepare you for using geospatial analysis with open source and free software tools.
Who this course is for:
- Geographers, Programmers, geologists, biologists, social scientists, or every other expert who deals with GIS maps in their field
Course content
- Preview07:27
- Preview03:37
Instructors
![Kate Alison](data:image/svg+xml,%3Csvg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 64 64"%3E%3C/svg%3E){kind=avatar}
- 4.3 Instructor Rating
- 1,737 Reviews
- 61,406 Students
- 31 Courses
I am a passionate data science expert and educator. I do regular teaching and training all over the world. I have many satisfied students! And now I will be glad if I can teach also you these interesting, highly applied, and exciting topics!
For GIS & Remote Sensing students:
Order of how to take my courses:
Option 1: Take all individual courses that contain more details and more labs in the following order:
1. Get started with GIS & Remote Sensing in QGIS #Beginners
2. Remote Sensing in QGIS: Fundamentals of Image Analysis 2020
3. Core GIS: Land Use and Land Cover & Change Detection in QGIS
4. Machine Learning in GIS: Understand the Theory and Practice
5. Machine Learning in GIS: Land Use/Land Cover Image Analysis
6. Machine Learning in ArcGIS: Map Land Use/ Land Cover in GIS
7. Object-based image analysis & classification in QGIS/ArcGIS
8. ArcGIS: Learn Deep Learning in ArcGIS to advance GIS skills
8. Google Earth Engine for Big GeoData Analysis: 3 Courses in 1
10. Google Earth Engine for Machine Learning & Change Detection
11. QGIS & Google Earth Engine for Environmental Applications
12. Advanced Remote Sensing Analysis in QGIS and on cloud
Option 2: Take my combi-courses that contain summarized information from the above courses, though in fewer details (labs, videos):
1. Geospatial Data Analyses & Remote Sensing: 4 Classes in 1
2. Machine Learning in GIS and Remote Sensing: 5 Courses in 1
3. Google Earth Engine for Big GeoData Analysis: 3 Courses in 1
4. Google Earth Engine for Machine Learning & Change Detection
5. Advanced Remote Sensing Analysis in QGIS and on cloud
- 4.3 Instructor Rating
- 485 Reviews
- 30,082 Students
- 10 Courses
Ich bin ein erfahrener Berater und Experte in Data Science. Ich habe mein MSc in Informatik an der TH Köln und MBA an der Universität Durham (UK) erlangt und habe mich später im Fachbereich Informatik promoviert. Als erfahrene Trainer mit mehr als 15 Jahren Berufserfahrung möchte ich meine Leidenschaft, praktische Erfahrungen und Kenntnisse in den Themen Big Data, Data Science, Data Analytics und IT management mit den anderen teilen und die praktische Kompetenzen von meinen Studenten auf ein sehr hohes Niveau bringen.