Assessment of moisture content in sandy beach environments from multispectral satellite imagery

Abstract

A framework for estimating moisture content from satellite-based multispectral imagery of sandy beaches was tested under various site conditions and sensors. It utilizes the reflectance of dry soil and an empirical factor c relating reflectance and moisture content for a specific sediment. Here, c was derived two ways: first, from in situ measurements of moisture content and average NIR image reflectance; and second, from laboratory-based measurements of moisture content and spectrometer reflectance. The proposed method was tested at four sandy beaches: Duck, North Carolina; and Cannon Beach, Ocean Cape, and Point Carrew, Yakutat, Alaska. Both measured and estimated moisture content profiles were impacted by site geomorphology. For profiles with uniform slopes, moisture contents ranged from 3.0% to 8.0% (zone 1) and from 8.0% to 23.0% (zone 2). Compared to field measurements, the moisture contents estimated using c calibrated from in situ and laboratory data resulted in percent error of 3.6%–44.7% and 2.7%–58.6%, respectively. The highest percent error occurred at the transition from zone 1 to zone 2. Generally, moisture contents were overestimated in zone 1 and underestimated in zone 2, but followed the expected trends based on field measurements. When estimated moisture contents in zone 1 exceeded 10%, surface roughness, debris, geomorphology, and weather conditions were considered.

Document Details

Document Type
Pub Defense Publication
Publication Date
Feb 01, 2022
Source ID
10.1139/cgj-2020-0624

Entities

People

  • Hans C. Graber
  • Heidi Wadman
  • Jesse E. Mcninch
  • Julie Paprocki
  • Nina Stark

Organizations

  • United States Army Corps of Engineers
  • University of Miami
  • Virginia Tech

Tags

Fields of Study

  • Agricultural and Food sciences

Readers

  • Atmospheric Remote Sensing.
  • Geotechnical Engineering.
  • Mathematics or Statistics

Technology Areas

  • Space