Spatio-temporal variations of CDOM in shallow inland waters from a semi-analytical inversion of Landsat-8

Jiwei Li, Qian Yu, Yong Q. Tian, Brian L. Becker, Paul Siqueira, Nathan Torbick

Research output: Contribution to journalArticlepeer-review

40 Scopus citations

Abstract

Bottom reflectance is often the main cause of high uncertainty in Colored Dissolved Organic Matter (CDOM) estimation for optically shallow waters. This study presents a Landsat-8 based Shallow Water Bio-optical Properties (SBOP) algorithm to overcome bottom effects so as to successfully observe spatial and temporal CDOM dynamics in inland waters. We evaluated the algorithm via 58 images and a large set of field measurements collected across seasons of multiple years in the Saginaw Bay, Lake Huron. Results showed that the SBOP algorithm reduced estimation errors by as much as 4 times (RMSE = 0.17 and R2 = 0.87 in the Saginaw Bay) when compared to the QAA-CDOM algorithm that did not take into account bottom reflectance. These improvements in CDOM estimation are consistent and robust across broad range CDOM absorption. Our analysis revealed: 1) the proposed remote sensing algorithm resulted in significant improvements in tracing spatial-temporal CDOM inputs from terrestrial environments to lakes, 2) CDOM distribution captured with high resolution land-viewing satellite is useful in revealing the impacts of terrestrial ecosystems on the aquatic environment, and 3) Landsat-8 OLI, with its 16 days revisit time, provides valuable time series data for studying CDOM seasonal variations at land-water interface and has the potential to reveal its relationship to adjacent terrestrial biogeography and hydrology. The study presents a shallow water algorithm for studying freshwater or coastal ecology, as well as carbon cycling science.

Original languageEnglish (US)
Pages (from-to)189-200
Number of pages12
JournalRemote Sensing of Environment
Volume218
DOIs
StatePublished - Dec 1 2018
Externally publishedYes

Keywords

  • CDOM
  • Carbon cycle
  • Carbon flux
  • Hydrology
  • Landsat
  • Optically shallow waters
  • SBOP

ASJC Scopus subject areas

  • Soil Science
  • Geology
  • Computers in Earth Sciences

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