Course: Remote Sensing and Image Analysis

Course: Remote Sensing and Image Analysis | Z_GIS

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
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Instructions: Clicking on the section name will show / hide the section.

Exploring and integrating remotely sensed imagery
- Learning objectives:
  
  develop and demonstrate skills in visual image interpretation
  
  understand and explain the importance of remote sensing image display and analytics in Digital Earth contexts
  
  continue to build experience in visual rs image interpretation and explanation of underlying factors and processes
  
  decide when and where to apply remote sensing imagery for visual interpretation, enhancement and as data source for geospatial workflows
- Section overview
  
  Pop out | Video
- Glossaries and Dictionaries URL
  
  Glossary of remote sensing and image processing terms
- ArcGIS Earth URL
  
  Get started with downloading and installing ArcGIS Earth - a virtual globe based on a satellite image view of Earth, enabling 'all' your ArcGIS Online data to be superimposed and interpreted in a global image map context.
  
  Set a bookmark on your hometown and your favourite holiday spot, explore the area around and then share your bookmarks (right click on My Data / Bookmarks) with your module folder in ArcGIS Online.
  
  Learn how to use ArcGIS Earth ...
- Getting started with ArcGIS Image for ArcGIS Online Page
  
  As one element of the ArcGIS Online 'ecosystem', this extension supports fundamental (as well as advanced) methods of image management, visualisation, analysis and feature extraction. Make sure you build a basic understanding and skills in working with this functionality.
- Sentinel Hub EO Browser Page
  
  This is an openly available cloud (online) platform for working with (not only) Sentinel data. Make sure you build a basic familiarity with its capabilities, as it will be used across the following sections in this course.
- The New Age of Imagery (eBook) File
  
  Collection of case studies illustrating the scope of remote sensing imagery application domains
- The ArcGIS Imagery Book URL
  
  Explore how imagery and remote sensing power modern GIS. Use this web site and the companion Instructional Guide for The ArcGIS Imagery Book and Learn ArcGIS lessons to quickly begin putting imagery to smarter, more skillful use with your GIS. Get an overview of the content of this eBook, we will focus on specific chapters later in this module.
- MOOC: Imagery in Action URL
  
  Make sure you complete this MOOC before, during or after taking this course, the sooner the better! Be aware that this MOOC is offered on a fixed schedule 1 or 2 times a year and not synchronized with academic years or semester schedules.
- Activities: Page
  
  Tasks to complete this section
- Assessment: Page
  
  Check out these questions and exercises
Fundamentals: from physics to visuals
- Learning objectives:
  
  understand the physical principles and laws determining electromagnetic (em) radiation and its spectral characteristics
  
  explain the difference between passive and active remote sensing systems, their respective application contexts and the impact of atmospheric modification
  
  understand the interaction of em radiation with the Earth's surface and and adequately visualize resulting spectral reflectance properties of land cover
- Section overview
  
  Pop out | Video
- Perceiving the Imperceptive: ArcGIS Imagery Book ch.4 URL
- Fundaments of Optical Remote Sensing URL
  
  EO4GEO Lecture on the physical (and other) scientific foundations in the important domain of passive, optical Earth Observation (teachers will provide guidance to essentials). >Presentation
- Introductory exercise course to remote sensing URL
  
  EO4GEO Lecture introducing some basic principles of remote sensing, and introducing data sources, Copernicus services as well as application domains. >Presentation
- Fundamentals of Remote Sensing File
  
  Presentation slides from the Worldbank Open Learning Campus Fundamentals of Aquatic Remote Sensing course.
- Take a picture and experiment with RBG de/composition URL
- RGB Color Mixer URL
- Landsat Viewer - multispectral visualisation & indices URL
- Activities: Page
  
  Tasks to complete this section
- Sentinel EO Browser - Visualisation Page
  
  Explore multiband visualisation and visual enhancement of imagery
- Sentinel Explorer - check out spectral signatures Page
  
  Explore the characteristic patterns of reflectance values across image bands
- Sentinel Explorer - create and interpret scatter plots Page
  
  Check the distribution and correlation of pairs of spectral bands
- Sentinel Explorer - identify land cover 'classes' Page
  
  Use bivariate scatter plots to find similar areas in an image
- Assessment: Page
  
  Check out these questions and exercises
Platforms, sensors and data
- Learning objectives:
  
  explain and assess the impact of satellite characteristics such as orbits and sensors on satisfying application requirements
  
  discuss the usability of imagery from a spatial, spectral, radiometric, and temporal resolutions perspective
  
  be able to access and navigate imagery portals with a focus an Sentinel and Landsat
  
  access and use imagery from these portals and through other spatial data infrastructures
  
  understand the relevance of image data characteristics in generic terms, in order to properly handle visualisation and analysis tools
- Section overview
  
  Pop out | Video
- Stuff in Space URL
  
  Explore and discover different types of (EO) satellites, orbits and live positions over Earth.
- The Sentinel family URL
- Sentinel-2 Global Coverage URL
- Sentinel 2A/B - right now! URL
- SatelliteXplorer URL
  
  Exploring Earth's artificial satellites: compare orbits and number of satellites for Localization - Communication - Earth Observation - Space Observation
- Landsat Storymaps URL
- Landsat acquisition schedule URL
  
  Check e.g. today's acquisition schedule ...
  Landsat pending acquisition tool
  Landsat swath animation >https://www.youtube.com/watch?v=xBhorGs8uy8
- EarthNow! Landsat Image Viewer URL
- planet - constellation and coverage URL
- Modes of acquisition (Coursera, 10min video) URL
- Activities: Page
  
  Tasks to complete this section
  
  Case Study (Author: Artak Piloyan)
- Assessment: Page
  
  Check out these questions and exercises
Imagery to thematic layers
- Learning objectives:
  
  navigate the path from the spectral to semantic dimensions
  
  understand the logic behind spectral image indices
  
  gain an overview of indices such as MSAVI, NDVI, PVI, and SAVI; select and use index indices appropriate for specific needs
  
  identify semantic categories using simple techniques like thresholding
- Section overview
  
  Pop out | Video
- Note: include task for survey123 ground truth app
- Analyzing imagery with ArcGIS Image for ArcGIS Online URL
  
  This document provides a concise overview of image analysis across the AGO platform, offering links to resources for further exploration.
- Sentinel Hub Index Tool File
  
  Follow this guide (>link) to creating and visualizing satellite image indices by choosing your individual topic and study area.
- Sentinel-2 data and vegetation indices URL
  
  EO4GEO Lecture on the principles and applications of spectral indices in optical remote sensing. >Presentation
- Preprocessing of EO data URL
  
  EO4GEO Lecture providing a brief overview across some typical pre-processing steps. >Presentation
- Unlock Earth's Secrets - explore satellite imagery collections URL
  
  EO Explorer - Sentinel Explorer - Landsat Explorer
- Landsat Lens - imagery in time and space URL
- From image interpretation to image classification
  
  ... >full window
- Activities: Page
  
  Tasks to complete this section
- Sentinel Explorer - Index Based Selection Page
  
  Use this simple tool to explore the extraction of single feature classes based on spectral indices
- Assessment: Page
  
  Check out these questions and exercises
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
Terrain and surface / feature analysis
Monitoring and detecting change
- Learning objectives:
  
  explain and communicate basics of monitoring and change detection
  
  implement visual interpretation tools for change detection (swipe, flicker, fade, ...)
  
  apply and interpret change matrices of multitemporal image classifications
  
  visually present and discuss change maps and related statistics
- Section overview
  
  Pop out | Video
- Compare Land Cover Change URL
- World Imagery Wayback URL
- How to Make the Perfect Time-Lapse of the Earth URL
  
  A guide in the Sentinel hub blog, covering various examples on making animations from satellite imagery.
- Monitoring changing ice with Sentinel-1 URL
- Global Forest Watch URL
- Vegetation Change Mapping URL
- Future Land Cover Change URL
- MOL - Map of Life URL
- Activities: Page
  
  Tasks to complete this section
- Practical NSDI Ararat File
- Assessment: Page
  
  Check out these questions and exercises

Course: Remote Sensing and Image Analysis | Z_GIS

General

Open all

Close all

Exploring and integrating remotely sensed imagery

Fundamentals: from physics to visuals

Platforms, sensors and data

Imagery to thematic layers

Classification and Feature Extraction

Terrain and surface / feature analysis

Monitoring and detecting change