We may earn an affiliate commission when you visit our partners.
Course image

Do you want to access satellite sensors using Earth Engine Python API?

Do you want to learn the QGIS Earth Engine plugin?

Do you want to visualize and analyze satellite data in Python?

Read more

Do you want to access satellite sensors using Earth Engine Python API?

Do you want to learn the QGIS Earth Engine plugin?

Do you want to visualize and analyze satellite data in Python?

Enroll in my new QGIS and Google Earth Engine Python API for Spatial Analysis course.

I will provide you with hands-on training with example data, sample scripts, and real-world applications. By taking this course, you be able to install QGIS and Earth Engine plugins. Then, you will have access to satellite data using the Python API.

In this QGIS and Google Earth Engine Python API for Spatial Analysis course, I will help you get up and running on the Earth Engine Python API and QGIS. By the end of this course, you will have access to all example scripts and data such that you will be able to access, download, visualize big data, and extract information.

In this course, we will cover the following topics:

  • Introduction to Earth Engine Python API

  • Install the QGIS Earth Engine Plugin

  • Load Landsat Satellite Data

  • Cloud Masking Algorithm

  • Calculate NDVI

  • Access Sentinel, Landsat In this course, I entirely use the Google Earth Engine Python API and QGIS open-source tools. All sample data and scripts will be provided to you as an added bonus throughout the course.

    Jump in right now to enroll. To get started click the enroll button.

Enroll now

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Strong reputation of Google Earth Engine as a platform for analyzing satellite data
Develops skills and knowledge relevant to GIS and remote sensing
Taught by an experienced instructor with a background in GIS and remote sensing
Provides hands-on training with example data and scripts
Teaches Python and QGIS, two widely-used tools in the field
Requires learners to have some prior knowledge of Python and QGIS

Save this course

Save QGIS and Google Earth Engine Python API for Spatial Analysis to your list so you can find it easily later:
Save

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in QGIS and Google Earth Engine Python API for Spatial Analysis with these activities:
Read 'Remote Sensing and Image Interpretation' by Thomas M. Lillesand and Ralph W. Kiefer
This book provides a solid foundation in remote sensing concepts and image interpretation techniques, which are essential for understanding the course materials.
Show steps
  • Read Chapter 1: Introduction
  • Read Chapter 2: Fundamentals of Remote Sensing
Organize and review your lecture notes, assignments, and quizzes
Regularly organizing and reviewing your materials will help you retain information and prepare for assessments.
Show steps
  • Create a dedicated folder or notebook for course materials
  • Review materials after each lecture
Familiarize yourself with the basics of Python programming
This course builds heavily on the fundamentals of programming in Python. Refreshing your knowledge through this activity will help you follow along and complete course assignments more easily.
Browse courses on Python Basics
Show steps
  • Review the Python documentation or tutorials
  • Complete online coding exercises or challenges
One other activity
Expand to see all activities and additional details
Show all four activities
Create a Jupyter notebook demonstrating your understanding of the course concepts
Creating a Jupyter notebook will allow you to apply your knowledge in a practical way and demonstrate your understanding of the course concepts.
Browse courses on Jupyter Notebook
Show steps
  • Choose a topic or dataset to analyze
  • Develop a workflow using Earth Engine and QGIS
  • Export your results as a Jupyter notebook

Career center

Learners who complete QGIS and Google Earth Engine Python API for Spatial Analysis will develop knowledge and skills that may be useful to these careers:
Remote Sensing Analyst
Remote Sensing Analysts use satellite imagery and other remote sensing data to study the Earth's surface. The Google Earth Engine Python API provides access to a vast amount of satellite data, and QGIS is a popular open-source GIS software that can be used to analyze remote sensing data. By taking this course, you will learn how to use QGIS and the Earth Engine Python API to analyze remote sensing data, which is a valuable skill for Remote Sensing Analysts.
Cartographer
Cartographers create maps and other visual representations of geographic data. QGIS is a popular open-source GIS software, and the Google Earth Engine Python API provides access to a vast amount of satellite data. By taking this course, you will learn how to use QGIS and the Earth Engine Python API to create maps and other visual representations of geographic data, which is a valuable skill for Cartographers.
GIS Specialist
GIS Specialists use GIS software to create maps and analyze spatial data. QGIS is a popular open-source GIS software, and the Google Earth Engine Python API provides access to a vast amount of satellite data. By taking this course, you will learn how to use QGIS and the Earth Engine Python API to analyze spatial data, which is a valuable skill for GIS Specialists.
Urban Planner
Urban Planners develop plans and policies for the development of cities and towns. Satellite data is a valuable source of data for Urban Planners, as it can be used to study a wide range of topics such as land use, transportation, and housing. By taking this course, you will learn how to access and analyze satellite data using QGIS and the Earth Engine Python API, which is a valuable skill for Urban Planners.
Research Scientist
Research Scientists conduct research to advance knowledge in a particular field. Satellite data is a valuable source of data for Research Scientists, as it can be used to study a wide range of topics such as climate change, land use, and water quality. By taking this course, you will learn how to access and analyze satellite data using QGIS and the Earth Engine Python API, which is a valuable skill for Research Scientists.
Data Scientist
Data Scientists use data to solve problems and make informed decisions. Satellite data is a valuable source of data for Data Scientists, as it can be used to study a wide range of topics such as land use, water quality, and air pollution. By taking this course, you will learn how to access and analyze satellite data using QGIS and the Earth Engine Python API, which is a valuable skill for Data Scientists.
Geographer
Geographers study the Earth's surface and its human and natural environments. Satellite data is a valuable source of data for Geographers, as it can be used to study a wide range of topics such as land use, water quality, and air pollution. By taking this course, you will learn how to access and analyze satellite data using QGIS and the Earth Engine Python API, which is a valuable skill for Geographers.
Environmental Planner
Environmental Planners develop plans and policies to protect the environment. They use spatial data to analyze environmental issues such as land use, water quality, and air pollution. The ability to access and analyze satellite data using QGIS and the Earth Engine Python API is a valuable skill for Environmental Planners, as it allows them to make informed decisions based on the most up-to-date information.
Oceanographer
Oceanographers study the oceans and their physical, chemical, and biological properties. Satellite data is a valuable source of data for Oceanographers, as it can be used to study a wide range of topics such as ocean currents, sea level rise, and marine ecosystems. By taking this course, you will learn how to access and analyze satellite data using QGIS and the Earth Engine Python API, which is a valuable skill for Oceanographers.
Atmospheric Scientist
Atmospheric Scientists study the Earth's atmosphere and its physical, chemical, and biological properties. Satellite data is a valuable source of data for Atmospheric Scientists, as it can be used to study a wide range of topics such as weather forecasting, climate change, and air pollution. By taking this course, you will learn how to access and analyze satellite data using QGIS and the Earth Engine Python API, which is a valuable skill for Atmospheric Scientists.
Conservation Scientist
Conservation Scientists develop and implement plans to protect and restore natural resources. Satellite data is a valuable source of data for Conservation Scientists, as it can be used to study a wide range of topics such as habitat loss, wildlife populations, and climate change. By taking this course, you will learn how to access and analyze satellite data using QGIS and the Earth Engine Python API, which is a valuable skill for Conservation Scientists.
Geologist
Geologists study the Earth's physical structure and history. Satellite data is a valuable source of data for Geologists, as it can be used to study a wide range of topics such as plate tectonics, mineral resources, and groundwater. By taking this course, you will learn how to access and analyze satellite data using QGIS and the Earth Engine Python API, which is a valuable skill for Geologists.
Environmental Engineer
Environmental Engineers design and implement solutions to environmental problems. Satellite data is a valuable source of data for Environmental Engineers, as it can be used to study a wide range of topics such as water quality, air pollution, and land use. By taking this course, you will learn how to access and analyze satellite data using QGIS and the Earth Engine Python API, which is a valuable skill for Environmental Engineers.
Geospatial Analyst
Geospatial Analysts utilize spatial data, such as satellite imagery and geographic information systems (GIS), to solve problems and make informed decisions. QGIS is a popular open-source GIS software, and the Google Earth Engine Python API provides access to a vast amount of satellite data. By taking this course, you will learn how to use QGIS and the Earth Engine Python API to analyze spatial data, which is a valuable skill for Geospatial Analysts.
Software Engineer
Software Engineers design, develop, and maintain software applications. The Google Earth Engine Python API is an open-source library that provides access to a vast amount of satellite data. By taking this course, you will learn how to use the Earth Engine Python API to develop software applications that can analyze satellite data, which is a valuable skill for Software Engineers.

Reading list

We've selected six books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in QGIS and Google Earth Engine Python API for Spatial Analysis.
Provides a comprehensive overview of the theory and practice of geospatial analysis. It covers the fundamental concepts of geospatial analysis, spatial data structures, spatial analysis techniques, and applications in various fields.
Provides a comprehensive overview of the principles and applications of remote sensing and image interpretation. It covers the fundamental concepts of remote sensing, image acquisition, image processing, and image interpretation techniques.
Provides a comprehensive overview of the theory and practice of spatial data analysis. It covers the fundamental concepts of spatial data analysis, statistical methods, and applications in various fields.
Provides a practical guide to using R for spatial analysis. It covers the basics of R programming, spatial data structures, spatial analysis techniques, and applications in various fields.
Will provide a foundational understanding of data analysis with Python covering the core functionality of the Python programming language, essential data structures, data analysis tools, and visualization techniques.
Provides a practical guide to using QGIS, a free and open-source geospatial software. It covers the basics of QGIS, data management, spatial analysis, and cartography.

Share

Help others find this course page by sharing it with your friends and followers:

Similar courses

Here are nine courses similar to QGIS and Google Earth Engine Python API for Spatial Analysis.
QGIS Mega Course: GIS and Remote Sensing- Beginner to...
Most relevant
Remote Sensing for Land Cover Mapping in Google Earth...
Most relevant
Geospatial APIs For Data Science Applications In Python
Most relevant
Complete Google Earth Engine for Remote Sensing & GIS
Most relevant
Geospatial Data Analyses & Remote Sensing: 5 Courses in 1
Most relevant
[Intermediate] Spatial Data Analysis with R, QGIS & More
Most relevant
Introduction to Geographic Information System in QGIS
Most relevant
The Frozen Frontier: Monitoring the Greenland Ice Sheet...
Most relevant
QGIS 3.10 LTR for GIS Professionals
Most relevant
Our mission

OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.

Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.

Find this site helpful? Tell a friend about us.

Affiliate disclosure

We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.

Your purchases help us maintain our catalog and keep our servers humming without ads.

Thank you for supporting OpenCourser.

© 2016 - 2024 OpenCourser