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Google Earth Engine for Machine Learning & Change Detection

Google Earth Engine for Machine Learning & Change Detection

Google Earth Engine for Machine Learning & Change Detection | Udemy Coupon ED

Become Expert in Geospatial analysis & Remote Sensing for machine learning in land use/land cover in Google Earth Engine Getting Started Udemy
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What you'll learn

  • Students will gain access to and a thorough knowledge of the Google Earth Engine platform
  • Implement machine learning algorithms on geospatial (satellite images) data in Earth Engine for LULC mapping
  • Get introduced and advance JavaScript skills on Google Earth Engine platform
  • Fully understand the main types of Machine Learning (supervised and unsupervised learning)
  • Learn how to apply supervised and unsupervised Machine Learning algorithms in Google Earth Engine
  • Learn how to obtain satellite data, apply image preprocessing, create training and validation data in Google Earth Engine
  • Implement calculation of change detection (pre and post-event detection) based on spectral indices
  • You'll have a copy of the codes used in the course for your reference

Requirements

  • A working computer with internet connection
  • An interest in working with geospatial data

Description

Land Use/Land Cover mapping and change detection with Machine Learning in Google Earth Engine
This course is designed to take users who use GIS for basic geospatial data/GIS/Remote Sensing analysis to perform more advanced geospatial analysis tasks using a variety of different data and applying Machine Learning state of the art algorithms. In addition to improving your skills in JavaScript, this course will make you proficient in Google Earth Engine for land use and land cover (LULC) mapping and change detection. As a result, you will be introduced to the exciting capabilities of Google Earth Engine which is a global leader for cloud computing in Geosciences!
I'm very excited that you found my Google Earth En gine course. This course is designed to equip you with the practical knowledge of unsupervised and supervised classification strategies for Land Use and Land Cover (LULC) mapping, which is one of the core skills for any Geographic Information Systems (GIS) and Remote Sensing analyst. By the end of the course, you will feel confident and completely understand and apply advanced Geospatial analysis including performing Machine Learning algorithms for land use and land cover mapping and spectral indices calculation and change detection. All this you will be able to carry out on the real (and open) data in Google Earth Engine.
This course is different from other training resources. Each lecture seeks to enhance your GIS and Remote Sensing skills in a demonstrable and easy-to-follow manner and provide you with practically implementable solutions. You’ll be able to start analyzing spatial data for your own projects, and gain appreciation from your future employers with your advances GIS skills and knowledge of the cutting edge LULC techniques.
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