E-TRAINEE Course

EnMAP-Box

E-TRAINEE Course

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Prerequisites
Module 1
Module 1
Module 2
Module 2
- Overview
- Principles of multispectral imaging
  Principles of multispectral imaging
  - Lesson
  - Exercise
- Temporal information in satellite data
  Temporal information in satellite data
  - Lesson
  - Exercise
- Image processing
  Image processing
  - Lesson
  - Exercise
- Multitemporal classification
  Multitemporal classification
  - Lesson
  - Exercise
- Vegetation change and disturbance detection
  Vegetation change and disturbance detection
  - Lesson
  - Exercise
- Case studies
  Case studies
Module 3
Module 3
- Overview
- Principles of 3D/4D geographic point clouds
  Principles of 3D/4D geographic point clouds
  - Lesson
  - Exercise
- Programming for point cloud analysis with Python
  Programming for point cloud analysis with Python
  - Lesson
  - Exercise
- Principles and basic algorithms of 3D change detection and analysis
  Principles and basic algorithms of 3D change detection and analysis
  - Lesson
  - Exercise
- Time series analysis of 3D point clouds
  Time series analysis of 3D point clouds
  - Lesson
  - Exercise
- Machine learning-based 3D/4D point cloud analysis
  Machine learning-based 3D/4D point cloud analysis
  - Lesson
- Case studies
  Case studies
  - Multitemporal 3D change analysis at an active rock glacier
  - Time series-based change analysis of sandy beach dynamics
Module 4
Module 4
- Overview
- Principles of imaging and laboratory spectroscopy
  Principles of imaging and laboratory spectroscopy
  - Lesson
  - Exercise
- Airborne hyperspectral data acquisition and pre-processing
  Airborne hyperspectral data acquisition and pre-processing
  - Lesson
  - Exercise
- In situ and laboratory spectroscopy of vegetation
  In situ and laboratory spectroscopy of vegetation
  - Lesson
  - Exercise
- Machine learning in imaging spectroscopy
  Machine learning in imaging spectroscopy
  - Lesson
  - Exercise
- Temporal vs. spatial and spectral resolution
  Temporal vs. spatial and spectral resolution
  - Lesson
- Case studies
  Case studies
Software
Software
- CloudCompare
- EnMAP-Box EnMAP-Box
  Table of contents
  - Download and installation
  - Getting started / external material
- Python
- QGIS
- R
- Google Earth Engine
Use Cases and Data
Use Cases and Data
About the project
Feedback form

EnMAP-Box

EnMAP-box is a QGIS plugin for working with imaging spectroscopy remote sensing data:
https://www.enmap.org/data_tools/enmapbox/

It is a free and open source software released under the GNU General Public License.

Download and installation

Follow the instructions for installing the EnMAP-box QGIS plugin Manual for installing the plugin

You need to install QGIS and required Python packages first.

Getting started / external material

Introduction to the EnMAP-box and how to handle spectral Iibraries can be found on the EnMAP-box workshop tutorial website. Description of the specific software functions can be found in the User Manual.