Vegetation Characterization through the Use of Precipitation-Affected SAR Signals

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Abstract

Current space-based SAR offers unique opportunities to classify vegetation types and to monitor vegetation growth due to its frequent acquisitions and its sensitivity to vegetation geometry. However, SAR signals also experience frequent temporal fluctuations caused by precipitation events, complicating the mapping and monitoring of vegetation. In this paper, we show that the influence of a priori known precipitation events on the signals can be used advantageously for the classification of vegetation conditions. For this, we exploit the change in Sentinel-1 backscatter response between consecutive acquisitions under varying wetness conditions, which we show is dependent on the state of vegetation. The performance further improves when a priori information on the soil type is taken into account.
Original languageEnglish
Pages (from-to)1-17
Number of pages17
JournalRemote Sensing
Volume10
Issue number10
DOIs
Publication statusPublished - 2018

Keywords

  • Incidence angle
  • Precipitation
  • SAR signals
  • Soil type
  • Vegetation classification

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