4.5 Article

Radar Satellite Imagery for Detecting Bark Beetle Outbreaks in Forests

期刊

CURRENT FORESTRY REPORTS
卷 5, 期 4, 页码 240-250

出版社

SPRINGER INTERNATIONAL PUBLISHING AG
DOI: 10.1007/s40725-019-00098-z

关键词

Forest; SAR; Time series; Damages; Monitoring; Bark beetle

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资金

  1. TU Wien (TUW)
  2. Living Planet Fellowship from the European Space Agency [4000125441/18/I-NS]

向作者/读者索取更多资源

Purpose of ReviewThe overall objective of this paper is to review the state of knowledge on the application of radar data for detecting bark beetle attacks in forests. Due to the increased availability of high spatial and temporal resolution radar data (e.g. Sentinel-1 (S1)), the question is how this time series data can support operational forest management with respect to forest insect damage prevention. Furthermore, available radar systems will be listed and their potential for detecting bark beetle attacks will be discussed. To increase the understanding of the potential of radar time series for detecting bark beetle outbreaks, a theoretical background about the interaction of the radar signals with the forest canopy is given. Finally, gaps in the available knowledge are identified and future research questions are formulated which could advance our understanding of using radar data for detecting forest bark beetle attacks.Recent FindingsFew studies already demonstrate the high potential of S1 time series data for forest disturbance mapping in general. It was demonstrated that multi-temporal S1 data provide an excellent data source of describing the phenological characteristics of forests, which provide the basic knowledge for detecting bark beetle induced forest damages. It has been found that the optimal time for data acquisition is April to June for the pre-event and August to October for the post-event acquisitions.SummaryFor detecting bark beetle induced forest damages, the literature review shows that mono-temporal radar data are of limited use, that shorter wavelength (e.g. C-band; X-band) have a higher potential than longer wavelength such as L-band and that the current S1 time series data have a high potential for operational applications.

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