[ FreeCourseWeb ] Udemy - Forest Mapping in Earth Engine Python API and Colab

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[ FreeCourseWeb ] Udemy - Forest Mapping in Earth Engine Python API and Colab (Size: 323.9 MB)
  1. Forest Cover for Gabon.mp4 48.5 MB
  1. Forest Cover for Gabon.srt 5.9 KB
  1. Global Forest Non-Forest Cover Mapping.mp4 37.6 MB
  1. Global Forest Non-Forest Cover Mapping.srt 4.7 KB
  1. Google Colab.mp4 25.9 MB
  1. Google Colab.srt 5 KB
  1. MODIS Burned Area.mp4 49.4 MB
  1. MODIS Burned Area.srt 4.9 KB
  2. Earth Engine Python API.mp4 38 MB
  2. Earth Engine Python API.srt 3.2 KB
  2. Forest Cover Gain and Loss for Gabon.jpeg 196.6 KB
  2. Forest Cover Gain and Loss for Gabon.mp4 73.1 MB
  2. Forest Cover Gain and Loss for Gabon.srt 6.5 KB
  2. Global Forest Cover.mp4 51 MB
  2. Global Forest Cover.srt 5.2 KB
  Bonus Resources.txt 307.2 B
  Get Bonus Downloads Here.url 204.8 B
  ▲ 17 total files

Description


Forest Mapping in Earth Engine Python API and Colab

Created by Dr. Alemayehu Midekisa, Spatial eLearning | Last updated 7/2021
Duration: 36m | 6 sections | 9 lectures | Video: 1280x720, 44 KHz | 324 MB
Genre: eLearning | Language: English + Sub
Learn satellite remote sensing, google earth engine python and forest cover monitoring and mapping

What you'll learn
Download, process and visualize various satellite data for forest monitoring application
Understand the advantages of using satellites for forest monitoring
Calculate Forest cover gain and loss using satellite data
Map global forest cover using SAR data

Requirements
This course has no requirement.
Description
Welcome to the Forest Mapping in Google Earth Engine Python API and Colab course.
This Earth Engine course is without a doubt the most comprehensive course for anyone who wants to apply remote sensing in forest cover mapping and monitoring. Even if you have zero programming experience, this course will take you from beginner to mastery.
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Here's why:
The course is taught by an experienced spatial data scientist and former NASA fellow.
The course has been updated to be 2021 ready and you'll be learning the latest tools available on the cloud.
We've taught over 16,000 students how to code and apply spatial data science and cloud computing.
You will have access to example data and sample scripts.

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