Spatial Data Analysis with Earth Engine Python API


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MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + .srt | Duration: 23 lectures (2h 15m) | Size: 937.2 MB

Export geospatial Data including rasters and vectors.​

Learn machine learning, big data analysis, GIS, remote sensing with Earth Ee Python API and Jupyter Notebook

Students will access and sign up the Google Earth Ee Python API platform

Access satellite data in Earth Ee

Access images and image collections from the Earth Ee cloud data library

Perform cloud masking of various satellite images

Visualize and analyze various satellite data including, MODIS, Sentinel and Landsat

Visualize series images

Run machine learning algorithms using big Earth Observation data

and Install Anaconda and Jupyter Notebook

Basic understanding of GIS and Remote Sensing

Access to the Google Earth Ee API

Do you want to access satellite sensors using Earth Ee Python API and Jupyter Notebook?

Do you want to learn the spatial data science on the cloud?

Do you want to become a spatial data scientist?

Enroll in my new course to Spatial Data Analysis with Earth Ee Ee Python API.

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 Ee Python API.

What makes me qualified to teach you?

I am Dr. Alemayehu Midekisa, PhD. I am a geospatial data scientist, instructor and author. I have over 15 plus years of experience in processing and analyzing real big Earth observation data from various sources including Landsat, MODIS, Sentinel-2, SRTM and other remote sensing products. I am also the recipient of one the prestigious NASA Earth and Space Science Fellowship. I teach over 10,000 students on Udemy.

In this Spatial Data Analysis with Earth Ee Python API course, I will help you get up and running on the Earth Ee Python API and Jupyter Notebook. By the end of this course, you will have access to all example script and data such that you will be able to accessing, ing, visualizing big data, and extracting information.

In this course we will cover the following topics:

Introduction to Earth Ee Python API

Install the Anaconda and Jupyter Notebook

Set Up a Python 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

Advanced digital image processing

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 Ee Python API and Jupyter Notebook. All sample data and script will be provided to you as an added bonus throughout the course.

Jump in right now and enroll.


Dr. Alemayehu Midekisa, PhD

This course is meant for professionals who want to harness the power Google Earth Ee Python API and Jupyter Notebook

People who want to understand various satellite image processing techniques using Python and Jupyter Notebook

Anyone who wants to learn accessing and extracting information from Earth Observation data

Anyone who wants to apply for a spatial data scientist job position