Spatial Data Analysis in Google Earth Engine Python API

Spatial Data Analysis in Google Earth Engine Python API, available at $49.99, has an average rating of 3.6, with 24 lectures, based on 86 reviews, and has 476 subscribers.

You will learn about Students will access and sign up the Google Earth Engine Python API platform Access satellite data in Earth Engine Export geospatial Data including rasters and vectors Access images and image collections from the Earth Engine cloud data library Perform cloud masking of various satellite images Visualize and analyze various satellite data including, MODIS, Sentinel and Landsat Visualize time series images Run machine learning algorithms using big Earth Observation data This course is ideal for individuals who are This course is meant for professionals who want to harness the power Google Earth Engine Python API and Jupyter Notebook or People who want to understand various satellite image processing techniques using Python and Jupyter Notebook or Anyone who wants to learn accessing and extracting information from Earth Observation data or Anyone who wants to apply for a spatial data scientist job position It is particularly useful for This course is meant for professionals who want to harness the power Google Earth Engine Python API and Jupyter Notebook or People who want to understand various satellite image processing techniques using Python and Jupyter Notebook or Anyone who wants to learn accessing and extracting information from Earth Observation data or Anyone who wants to apply for a spatial data scientist job position.

Enroll now: Spatial Data Analysis in Google Earth Engine Python API

Summary

Title: Spatial Data Analysis in Google Earth Engine Python API

Price: $49.99

Average Rating: 3.6

Number of Lectures: 24

Number of Published Lectures: 24

Number of Curriculum Items: 24

Number of Published Curriculum Objects: 24

Original Price: $49.99

Quality Status: approved

Status: Live

What You Will Learn

Students will access and sign up the Google Earth Engine Python API platform
Access satellite data in Earth Engine
Export geospatial Data including rasters and vectors
Access images and image collections from the Earth Engine cloud data library
Perform cloud masking of various satellite images
Visualize and analyze various satellite data including, MODIS, Sentinel and Landsat
Visualize time series images
Run machine learning algorithms using big Earth Observation data

Who Should Attend

This course is meant for professionals who want to harness the power Google Earth Engine 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

Target Audiences

This course is meant for professionals who want to harness the power Google Earth Engine 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

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

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

Do you want to become a spatial data scientist?

Enroll in my new course Spatial Data Analysis in Google Earth Engine 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 Engine Python API.

In this Spatial Data Analysis with Earth Engine Python APIcourse, I will help you get up and running on the Earth Engine Python API and Jupyter Notebook. 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 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 Engine Python API and Jupyter Notebook. All sample data and scripts will be provided to you as an added bonus throughout the course.

Jump in right now and enroll.

Course Curriculum

Chapter 1: Introduction to Earth Engine Python API

Lecture 1: Welcome

Lecture 2: Install Anaconda

Lecture 3: Set Up Python Environment

Lecture 4: Sign Up on Earth Engine

Lecture 5: Install Earth Engine Python API

Lecture 6: Load Landsat Images

Chapter 2: Raster Data Visualization

Lecture 1: Landsat Visualization

Lecture 2: MODIS Land Cover

Lecture 3: NLCD Land Cover

Lecture 4: NDVI Visualization

Chapter 3: Vector Data Visualization

Lecture 1: US States

Lecture 2: USA Counties

Lecture 3: International Boundary

Chapter 4: Raster Data Analysis: Images

Lecture 1: Clipping

Lecture 2: Image Metadata

Lecture 3: Band Math

Lecture 4: Calculate MODIS NDVI

Chapter 5: Raster Data Analysis: Image Collection

Lecture 1: Clip Image Collection

Lecture 2: Landsat Simple Composite

Lecture 3: Filter by Calendar Day of Year

Chapter 6: Machine Learning: Unsupervised and Supervised Classification

Lecture 1: Clustering: Unsupervised Classification

Lecture 2: CART: Supervised Classification

Lecture 3: SVM: Supervised Classification

Chapter 7: Bonus Lectures

Lecture 1: Bonus

Instructors

Dr. Alemayehu Midekisa
Geospatial Data Scientist

Rating Distribution

1 stars: 3 votes
2 stars: 6 votes
3 stars: 16 votes
4 stars: 26 votes
5 stars: 35 votes

Frequently Asked Questions

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You can view and review the lecture materials indefinitely, like an on-demand channel.

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