Section: Classification and Feature Extraction | Remote Sensing and Image Analysis

Section: Classification and Feature Extraction | Remote Sensing and Image Analysis | Z_GIS

Main course page

General
- Introduction Forum
- Development feedback Forum
  
  Please post all suggestions and corrections for this module. Refer to specific sections whenever your posting applies to content of a specific section.
- Learning objectives (module level):
  
  appreciate the value of remote sensing imagery as a core element for a(ny) Digital Earth
  
  explain and communicate the fundamentals of remote sensing including physical principles and characteristics of platforms and sensors
  
  gain experience with at least two different cloud platforms for remore sensing image analysis - e.g. Sentinel Hub and ArcGIS Image for ArcGIS Online
  
  modify multi-band image display according to information needs and application domains
  
  visually integrate imagery with geospatial displays, products and apps
  
  access, manage, explore and integrate remote sensing imagery into geospatial workflows and products
  
  understand and adequately apply simple classification methods, starting from indices
  
  work with raster analysis methods, including pre- and post-processing
  
  implement simple change detection and monitoring tools
  
  be aware of advanced topics of remote sensing data management and analysis in general terms

Classification and Feature Extraction

Classification and Feature Extraction
- Learning objectives:
  
  know the basics of image classification, understand and apply multivariate image classification models, i.e. unsupervised vs. supervised classification
  
  assess the quality and accuracy of image classification results
  
  visualize and share thematic image processing outputs
  
  understand and apply (pre-configured) basic machine learning approaches
  
  interpret results from object-based image analysis (OBIA) feature extraction
- Section overview
  
  Pop out | Video
- Image Classification using ArcGIS URL
  
  Learning path based on ArcGIS Pro - recommended if this platform is readily available.
- Esri Academy: Introduction to Image Classification (Web Course) URL
  
  Supervised pixel classification - Unsupervised pixel classification - OBIA
- Classification: Decision Trees URL
  
  EO4GEO Lecture on this popular non-parametric classifier (advanced topic). >Presentation
- Classification: Random Forests URL
  
  EO4GEO Lecture introducing a machine learning classifier with a capability to obtain good classification results with a relatively low number of training samples and reliance on a reduced number of user-defined parameters (advanced topic). >Presentation
- Object-based Image Analysis – An Introduction URL
  
  EO4GEO Lecture providíng an introduction to concepts and methods of Object-based image analysis. >Presentation
- Artificial Intelligence for Earth Observation URL
  
  A webinar addressing the use of AI algorithms in EO applications. Introducing AI concepts, from machine to deep learning, from unsupervised to supervised methods. Furthermore, applications in object detection, semantic segmentation, classification, clustering, and data augmentation will be showed.
- Activities: Page
  
  Tasks to complete this section
- Assessment: Page
  
  Check out these questions and exercises

Section: Classification and Feature Extraction | Remote Sensing and Image Analysis | Z_GIS

General

Classification and Feature Extraction

Classification and Feature Extraction