~Get Your Files Here !/1. Introduction/1. Introduction.mp436.34MB
~Get Your Files Here !/1. Introduction/2. What is R and RStudio.mp412.22MB
~Get Your Files Here !/1. Introduction/3. How to install R and RStudio in 2021.mp416.66MB
~Get Your Files Here !/1. Introduction/4. Lab Install R and RStudio in 2021.mp438.72MB
~Get Your Files Here !/1. Introduction/5. Lab Installing QGIS and install SCP.mp486.71MB
~Get Your Files Here !/2. Machine Learning for image classification theory overview/1. Introduction to Machine Learning.mp493.46MB
~Get Your Files Here !/2. Machine Learning for image classification theory overview/2. Basics of machine learning for classification analysis.mp471.46MB
~Get Your Files Here !/2. Machine Learning for image classification theory overview/3. Common algorithms of image classification.mp4112.93MB
~Get Your Files Here !/3. Introduction to R-Studio and R crash course/1. Lab Introduction to RStudio Interface.mp447.69MB
~Get Your Files Here !/3. Introduction to R-Studio and R crash course/10. Functions in R - overview.mp432.24MB
~Get Your Files Here !/3. Introduction to R-Studio and R crash course/11. For Loops in R.mp424.85MB
~Get Your Files Here !/3. Introduction to R-Studio and R crash course/12. Read Data into R.mp431.91MB
~Get Your Files Here !/3. Introduction to R-Studio and R crash course/2. Lab Installing Packages and Package Management in R.mp424.14MB
~Get Your Files Here !/3. Introduction to R-Studio and R crash course/3. Variables in R and assigning Variables in R.mp48.97MB
~Get Your Files Here !/3. Introduction to R-Studio and R crash course/4. Lab Variables in R and assigning Variables in R.mp47.65MB
~Get Your Files Here !/3. Introduction to R-Studio and R crash course/5. Overview of data types and data structures in R.mp427.2MB
~Get Your Files Here !/3. Introduction to R-Studio and R crash course/6. Lab data types and data structures in R.mp448.1MB
~Get Your Files Here !/3. Introduction to R-Studio and R crash course/7. Vectors' operations in R.mp435.95MB
~Get Your Files Here !/3. Introduction to R-Studio and R crash course/8. Data types and data structures Factors.mp49.33MB
~Get Your Files Here !/3. Introduction to R-Studio and R crash course/9. Dataframes overview in R.mp416.67MB
~Get Your Files Here !/4. Basics of Remote Sensing for LULC mapping theory overview/1. Introduction to digital image.mp458.38MB
~Get Your Files Here !/4. Basics of Remote Sensing for LULC mapping theory overview/2. Sensors and Platforms.mp418.28MB
~Get Your Files Here !/4. Basics of Remote Sensing for LULC mapping theory overview/3. Understanding Remote Sensing for LULC mapping.mp463.32MB
~Get Your Files Here !/4. Basics of Remote Sensing for LULC mapping theory overview/4. Stages of LULC supervised classification.mp472.76MB
~Get Your Files Here !/5. Satellite image preparation in R for Land use land cover (LULC) analysis in R/1. Data used for analysis Landsat images.mp432.94MB
~Get Your Files Here !/5. Satellite image preparation in R for Land use land cover (LULC) analysis in R/2. Preprocessing of satellite image data.mp429.2MB
~Get Your Files Here !/5. Satellite image preparation in R for Land use land cover (LULC) analysis in R/3. Overview of processing steps in R for Landsat images.mp414.92MB
~Get Your Files Here !/5. Satellite image preparation in R for Land use land cover (LULC) analysis in R/4. Lab Image load in R.mp449.75MB
~Get Your Files Here !/5. Satellite image preparation in R for Land use land cover (LULC) analysis in R/5. Lab Image Layerstacks in R.mp495.67MB
~Get Your Files Here !/5. Satellite image preparation in R for Land use land cover (LULC) analysis in R/6. Lab Batch Processing in R unzipp, laerstack of LAndsat images.mp457.19MB
~Get Your Files Here !/5. Satellite image preparation in R for Land use land cover (LULC) analysis in R/7. Visualize images in R.mp464.45MB
~Get Your Files Here !/6. Training data Preparation in R for Machine Learning image classification/1. Data used for analysis Sentinel images.mp437.49MB
~Get Your Files Here !/6. Training data Preparation in R for Machine Learning image classification/2. Training data requirements for classification and training data selection.mp435.11MB
~Get Your Files Here !/6. Training data Preparation in R for Machine Learning image classification/3. Lab Prepare training data in R - part 1.mp460.43MB
~Get Your Files Here !/6. Training data Preparation in R for Machine Learning image classification/4. Lab Prepare training data in R - part 2.mp4121.54MB
~Get Your Files Here !/6. Training data Preparation in R for Machine Learning image classification/5. Plotting spectral signatures in R.mp424.73MB
~Get Your Files Here !/7. Land UseLand Cover Image Classification using Machine Learning algorithms in R/1. Image Classification in R with Random Forest in R.mp493.7MB
~Get Your Files Here !/7. Land UseLand Cover Image Classification using Machine Learning algorithms in R/2. Image Classification in R with Support Vector Machines (SVM) in R.mp474.83MB
~Get Your Files Here !/7. Land UseLand Cover Image Classification using Machine Learning algorithms in R/3. Accuracy assessment of image classification.mp450.97MB
~Get Your Files Here !/7. Land UseLand Cover Image Classification using Machine Learning algorithms in R/4. Lab Accuracy Assessment (validation) of classification in R.mp4110.37MB
~Get Your Files Here !/7. Land UseLand Cover Image Classification using Machine Learning algorithms in R/5. Independent Task Accuracy assessment for SVM-based classification.mp45.65MB