Skip to main content

Relationships between forest structure and the detection of flood inundation in forested wetlands using C-band SAR

Buy Article:

$63.00 plus tax (Refund Policy)

Abstract:

An important practical application of orbital SAR data is the detection of flood inundation beneath forest canopies. C-band microwaves (especially C-VV) are generally considered inferior to longer wavelengths (especially L-band) for mapping flooded forests. Nevertheless C-band data have been shown to exhibit sensitivity to inundation beneath forest canopies. Because of this, the application and interpretation of C-band images requires identification of the forest conditions under which C-band microwaves detect inundation. Images from ERS-1 and RADARSAT representing nearly identical hydrological conditions were used to classify flooded and nonflooded forests for the Roanoke River floodplain, North Carolina, USA. Flooded forests were detected accurately using RADARSAT, and were distinguishable but not mapped accurately using ERS-1. This poses potential problems for the accurate interpretation of C-VV images (i.e. ERS-1/ERS-2) in such environments. To examine this issue, biophysical data from forest plots were used to assess the effect of forest structure on the ability of ERS-1 to detect flooded forests. Basal area (BA) and height to the bottom of the canopy exhibited statistically significant relationships to the detection of inundation using ERS-1, while leaf area index, canopy height, canopy depth, and crown closure were not statistically significant. The results suggest that forest structure and scattering processes at the trunk layer (due to higher BA and open understories with greater heights to the bottom of the canopy) most strongly influence double-bounce scattering of C-VV microwaves from flooded forests.

Document Type: Research Article

DOI: https://doi.org/10.1080/01431160010014738

Publication date: 2002-02-20

More about this publication?
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more