Hyperspectral Image Transects during Transient Events in Rivers (HITTER): Framework development and application to a tracer experiment on the Missouri River, USA

Remote Sensing
By: , and 

Links

Abstract

Rivers convey a broad range of materials, such as sediment, nutrients, and contaminants. Much of this transport can occur during or immediately after an episodic, pulsed event like a flood or an oil spill. Understanding the flow processes that influence the motion of these substances is important for managing water resources and conserving aquatic ecosystems. This study introduces a new remote sensing framework for characterizing dynamic phenomena at the scale of a channel cross-section: Hyperspectral Image Transects during Transient Events in Rivers (HITTER). We present a workflow that uses repeated hyperspectral scan lines acquired from a hovering uncrewed aircraft system (UAS) to quantify how a water attribute of interest varies laterally across the river and evolves over time. Data from a tracer experiment on the Missouri River are used to illustrate the components of the end-to-end processing chain we used to quantify the passage of a visible dye. The framework is intended to be flexible and could be applied in a number of different contexts. The results of this initial proof-of-concept investigation suggest that HITTER could potentially provide insight regarding the dispersion of a range of materials in rivers, which would facilitate ecological and geomorphic studies and help inform management.

Publication type Article
Publication Subtype Journal Article
Title Hyperspectral Image Transects during Transient Events in Rivers (HITTER): Framework development and application to a tracer experiment on the Missouri River, USA
Series title Remote Sensing
DOI 10.3390/rs16193743
Volume 19
Issue 16
Year Published 2024
Language English
Publisher MDPI
Contributing office(s) Columbia Environmental Research Center, Geosciences and Environmental Change Science Center, WMA - Observing Systems Division
Description 3743, 33 p.
Google Analytic Metrics Metrics page
Additional publication details