Machine Learning in R: Land Use Land Cover Image Analysis
Learn supervised machine learning for Remote Sensing R & R-Studio, image classification, land use and land cover mapping
4.45 (118 reviews)
492
students
5.5 hours
content
Nov 2024
last update
$13.99
regular price
What you will learn
Learn supervised machine learning for image classification using R-programming language in R-Studio
Learn theoretical background of Machine Learning
Apply machine learning based algorithms (random forest, SVM) for image classification analysis in R and R-Studio
Learn R-programming from scratch: R crash course is included that you could start R-programming for machine learning
Fully understand the basics of Land use and Land Cover (LULC) Mapping based on satellite image classification
Get an introduction and fully understand to Remote Sensing relevant for LULC mapping
Pre-process and analyze Remote Sensing images in R
Learn how to create training and validation data for image classification in QGIS
Build machine learning based image classification models for LUCL analysis and test their robustness in R
Implement Machine Learning algorithms, such as Random Forests, SVM in R
Apply accuracy assessment for Machine Learning based image classification in R
You'll have a copy of the scripts and step-by-step manuals used in the course for your reference to use in your analysis.
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3920796
udemy ID
17/03/2021
course created date
09/09/2021
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