Spatial Data Analysis in Google Earth Engine Python & Colab

Spatial Data Analysis in Google Earth Engine Python & Colab udemy course

Learn big spatial data, machine learning, GIS and remote sensing with Earth Engine Python API and Google Colab

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.