Shallow coastal water turbidity monitoring using Planet Dove satellites. Issue 4 (9th March 2022)

• Record Type: Journal Article
• Authors: Li, Jiwei; Carlson, Rachel R.; Knapp, David E.; Asner, Gregory P.
• Editors: Scales, Kylie; Jones, Alice
• Is Part Of: Remote sensing in ecology and conservation. Volume 8:Issue 4(2022)
• Page Start: 521
• Page End: 535
• Publication Date: 2022-03-09
• Subjects: Benthic -- coastal water -- coral reef -- Planet Dove -- shallow water -- turbidity; Remote sensing -- Periodicals; Ecology -- Research -- Periodicals; Ecology -- Methodology -- Periodicals; Ecology -- Remote sensing -- Periodicals; Nature conservation -- Methodology -- Periodicals; 577.0723
• DOI: 10.1002/rse2.259
• Languages: English
• ISSNs: 2056-3485

Abstract

Abstract: Turbidity monitoring in shallow coastal waters is fundamental to marine ecosystem research, management and protection. Satellite‐based water turbidity monitoring can be conducted at a greater spatial extent and higher temporal frequency than field measurements. The new Planet Dove satellite constellation has a daily revisit frequency and higher spatial resolution than Sentinel or Landsat satellites, allowing Planet Dove to track water turbidity dynamics in greater detail when suitable atmospheric correction is provided. We developed a new shallow coastal water turbidity estimation algorithm for Planet Dove and similar multi‐spectral satellites. Our algorithm accounts for bottom reflectance in total water‐leaving radiance to derive turbidity values in shallow coastal waters. We tested the algorithm with data from 235 Dove satellite images at five sites with different water conditions (Pelekane Bay, Big Island, Hawai'i; Hilo Bay, Big Island, Hawai'i; Kilo Nalu and Ala Wai, O'ahu, Hawai'i; Fagatele Bay, American Samoa; Vieques Island, Puerto Rico). We then validated satellite‐derived turbidity results (RMSE = 0.79–1.12 FNU [Formazin Nephelometric Unit]) using 75 days of field‐measured data, ranging in turbidity from 0.1 to 11.6 FNU in the five sites. Results show that our algorithm accurately detects turbidity in critical nearshore environments. In Hawai'i, we used ~6700 Dove images to support a weekly turbidity monitoring study at a large geographic scale. We found this new, shallow‐water algorithm can be effectively applied to Dove satellite data to monitor water turbidity at high temporal resolution. Abstract : Turbidity monitoring in shallow coastal waters is fundamental to marine ecosystem research, management, and protection. We developed a new shallow coastal water turbidity estimation algorithm for Planet Dove and similar multi‐spectral satellites. Results show that our algorithm more accurately detects turbidity in critical nearshore environments than a commonly used, deep‐water algorithm when benthic habitats are known. In Hawai'i, we used 6, 700 Dove images to support a weekly turbidity monitoring study at a large geographic scale. We found this new, shallow‐water algorithm can be effectively applied to Dove satellite data to monitor water turbidity at high temporal resolution.