A framework for estimating forest disturbance intensity from successive remotely sensed biomass maps: Moving beyond average biomass loss estimates

T. C. Hill*, C. M. Ryan, M. Williams

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Background: The success of satellites in mapping deforestation has been invaluable for improving our understanding of the impacts and nature of land cover change and carbon balance. However, current satellite approaches struggle to quantify the intensity of forest disturbance, i.e. whether the average rate of biomass loss for a region arises from heavy disturbance focused in a few locations, or the less severe disturbance of a wider area. The ability to distinguish between these, very different, disturbance regimes remains critical for forest managers and ecologists. Results: We put forward a framework for describing all intensities of forest disturbance, from deforestation, to widespread low intensity disturbance. By grouping satellite observations into ensembles with a common disturbance regime, the framework is able to mitigate the impacts of poor signal-to-noise ratio that limits current satellite observations. Using an observation system simulation experiment we demonstrate that the framework can be applied to provide estimates of the mean biomass loss rate, as well as distinguish the intensity of the disturbance. The approach is robust despite the large random and systematic errors typical of biomass maps derived from radar. The best accuracies are achieved with ensembles of ≥1600 pixels (≥1 km2 with 25 by 25 m pixels). Summary: The framework we describe provides a novel way to describe and quantify the intensity of forest disturbance, which could help to provide information on the causes of both natural and anthropogenic forest loss-such information is vital for effective forest and climate policy formulation.

Original languageEnglish
Article number27
JournalCarbon Balance and Management
Volume10
Issue number1
DOIs
Publication statusPublished - 2 Dec 2015

Keywords

  • Biomass
  • Carbon
  • Deforestation
  • Degradation
  • Disturbance
  • Forest
  • Intensity
  • REDD
  • Remote sensing
  • Satellite

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