Imaging spectroscopy of forest ecosystems

Exploiting the Potential of Hyperspectral Data
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Unit Description

This unit introduces the basics of Forest Imaging Spectroscopy. Firstly, the spectral characteristics of vegetation on leaf and canopy level are shown and explained using measured and modelled spectral reflectance characteristics, followed by the basic models of inversion. Typical analyses are described by using example data work flows and include tree species classification, mapping foliar nitrogen content as an example of regression for quantitative mapping, and finally drought stress mapping. Being familiar with the content of the unit “Principles of imaging spectroscopy” prior to this one is mandatory.

This unit was originally published in August 2020. The revised version is accessible since February 2023. Students are advised to go through the units “Principles of imaging spectroscopy” and “Retrieval approaches of vegetation traits from imaging spectroscopy data” before starting with this unit. The tutorial “Regression-based mapping of forest aboveground biomass” offers complemental and practical insights on the possibilities to map forest Aboveground Biomass (AGB) from simulated EnMAP imagery.

How to cite this slide collection: H. Buddenbaum, J. Hill (2020). Imaging Spectroscopy of Forest Ecosystems – Exploiting the Potential of Hyperspectral Data. HYPERedu, EnMAP education initiative, Trier University; originally published August 2020, revised February 2023.

Please help us to further improve the hyperspectral resources and send us your feedback to hyperedu@eo-college.org

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Download Resource

The SAR-EDU material is published under a Creative Commons Licence. This work is licenced under a Attribution-ShareAlike 4.0 International License (CC BY-SA 4.0).

YOU ARE FREE TO:
Share – copy and redistribute the material in any medium or format. Adapt – remix, transform, and built upon the material for any purpose, even commercially.

UNDER THE FOLLOWING TERMS:
Attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. ShareAlike – If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original. The licensor cannot revoke these freedoms as long as you follow the license terms!

Download Resource

The SAR-EDU material is published under a Creative Commons Licence. This work is licenced under a Attribution-ShareAlike 4.0 International License (CC BY-SA 4.0).

YOU ARE FREE TO:
Share – copy and redistribute the material in any medium or format. Adapt – remix, transform, and built upon the material for any purpose, even commercially.

UNDER THE FOLLOWING TERMS:
Attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. ShareAlike – If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original. The licensor cannot revoke these freedoms as long as you follow the license terms!