Mapping forest disturbance due to selective logging in the congo basin with radarsat-2 time series

Oleg Antropov*, Yrjö Rauste, Jaan Praks, Frank Martin Seifert, Tuomas Häme

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

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Abstract

Dense time series of stripmap RADARSAT-2 data acquired in the Multilook Fine mode were used for detecting and mapping the extent of selective logging operations in the tropical forest area in the northern part of the Republic of the Congo. Due to limited radiometric sensitivity to forest biomass variation at C-band, basic multitemporal change detection approach was supplemented by spatial texture analysis to separate disturbed forest from intact. The developed technique primarily uses multi-temporal aggregation of orthorectified synthetic aperture radar (SAR) imagery that are acquired before and after the logging operations. The actual change analysis is based on textural features of the log-ratio image calculated using two SAR temporal composites compiled of SAR scenes acquired before and after the logging operations. Multitemporal aggregation and filtering of SAR scenes decreased speckle and made the extracted textural features more prominent. The overall detection accuracy was around 80%, with some underestimation of the area of forest disturbance compared to reference based on optical data. The user’s accuracy for disturbed forest varied from 76.7% to 94.9% depending on the accuracy assessment approach. We conclude that change detection utilizing RADARSAT-2 time series represents a useful instrument to locate areas of selective logging in tropical forests.

Original languageEnglish
Article number740
Pages (from-to)1-16
Number of pages16
JournalRemote Sensing
Volume13
Issue number4
DOIs
Publication statusPublished - 2 Feb 2021
MoE publication typeA1 Journal article-refereed

Keywords

  • C-band
  • Satellite image time series
  • Selective logging
  • Synthetic aperture radar
  • Tropical forest

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