Methods for Mapping Forest Disturbance and Degradation from Optical Earth Observation Data: a Review

Manuela Hirschmugl*, Heinz Gallaun, M. Dees, P. Datta, Janik Deutscher, N. Koutsias, Mathias Schardt

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Purpose of Review
This paper presents a review of the current state of the art in remote sensing-based monitoring of forest disturbances and forest degradation from optical Earth Observation data. Part one comprises an overview and tabular description of currently available optical remote sensing sensors, which can be used for forest disturbance and degradation mapping. Part two reviews the two main categories of existing mapping approaches: first, classical image-to-image change detection and second, time series analysis.
Recent Findings
With the launch of the Sentinel-2a satellite and available Landsat imagery, time series analysis has become the most promising but also most demanding category of degradation mapping approaches. Four time series classification methods are distinguished. The methods are explained and their benefits and drawbacks are discussed. A separate chapter presents a number of recent forest degradation mapping studies for two different ecosystems: temperate forests with a geographical focus on Europe and tropical forests with a geographical focus on Africa.
The review revealed that a wide variety of methods for the detection of forest degradation is already available. Today, the main challenge is to transfer these approaches to high-resolution time series data from multiple sensors. Future research should also focus on the classification of disturbance types and the development of robust up-scalable methods to enable near real-time disturbance mapping in support of operational reactive measures.
Original languageEnglish
Pages (from-to)32-45
JournalCurrent Forestry Reports
Issue number1
Publication statusPublished - 2017

Fields of Expertise

  • Sustainable Systems


Dive into the research topics of 'Methods for Mapping Forest Disturbance and Degradation from Optical Earth Observation Data: a Review'. Together they form a unique fingerprint.

Cite this