Spatial Data Analysis in Google Earth Engine Python & Colab
What you'll learn
- Students will access and sign up the Google Earth Engine Python API
- Access and visualize satellite data in Earth Engine Python API
- Export geospatial data including raster and vector data formats
- Access images and image collections from the Earth Engine API
- Apply various machine learning algorithms on the Earth Engine Python API and Colab
Requirements
- This course has no requirements.
Description
Do you want to access satellite sensors using Earth Engine Python API and Google Colab?
Do you want to learn spatial data science on the cloud?
Do you want to become a geospatial data scientist?
Enroll in my new course Spatial Data Analysis in Google Earth Engine Python & Colab.
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 Anaconda and Jupyter Notebook. Then, you will have access to satellite data using the Earth Engine Python API and Google Colab.
In this Spatial Data Analysis with Earth Engine Python API and Colab course, I will help you get up and running on the Earth Engine Python API and Google Colab. 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 and Colab
Set Up a Google Colab Environment
Raster Data Visualization
Vector Data Visualization
Load Landsat Satellite Data
Cloud Masking Algorithm
Calculate NDVI
Export images and videos
Process image collections
Machine Learning Algorithms
One of the common problems with learning image processing is the high cost of software. In this course, I entirely use open-source software including the Google Earth Engine Python API and Colab. All sample data and scripts will be provided to you as an added bonus throughout the course.
Jump in right now and enroll.
Who this course is for:
- This course is meant for professionals who want to manipulate big spatial data on the cloud using Earth Engine and Google Colab
- Anyone who wants to learn accessing and extracting information from satellite data
- Anyone who wants to apply for a spatial data scientist job position
Instructor
- 3.9 Instructor Rating
- 1,635 Reviews
- 20,180 Students
- 18 Courses
I am a geospatial data scientist with 15 plus years of experience. I am a former NASA Earth and Space Science fellow. My research interests include remote sensing, big data and environmental change. More specifically, I am interested in applying big geospatial data, cloud computing and machine learning to solve complex environmental problems, especially land cover change, climate change, water resource, agriculture, and public health.