Use of SAR and Optical Time Series for Tropical Forest Disturbance Mapping

Manuela Hirschmugl*, Janik Deutscher, Carina Sobe, A. Bouvet, S. Mermoz, Mathias Schardt

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Frequent cloud cover and fast regrowth often hamper topical forest disturbance monitoring with optical data. This study aims at overcoming these limitations by combining dense time series of optical (Sentinel-2 and Landsat 8) and SAR data (Sentinel-1) for forest disturbance mapping at test sites in Peru and Gabon. We compare the accuracies of the individual disturbance maps from optical and SAR time series with the accuracies of the combined map. We further evaluate the detection accuracies by disturbance patch size and by an area-based sampling approach. The results show that the individual optical and SAR based forest disturbance detections are highly complementary, and their combination improves all accuracy measures. The overall accuracies increase by about 3% in both areas, producer accuracies of the disturbed forest class increase by up to 25% in Peru when compared to only using one sensor type. The assessment by disturbance patch size shows that the amount of detections of very small disturbances (< 0.2 ha) can almost be doubled by using both data sets: for Gabon 30% as compared to 15.7-17.5%, for Peru 80% as compared to 48.6-65.7%.

Original languageEnglish
Article number727
JournalRemote Sensing
Issue number4
Publication statusPublished - Feb 2020


  • Change detection
  • Disturbance
  • Earth Observation
  • FNF mapping
  • Forest
  • Gabon
  • Monitoring
  • Peru
  • SAR
  • Sentinel

ASJC Scopus subject areas

  • General Earth and Planetary Sciences

Fields of Expertise

  • Sustainable Systems


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