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Comparing planetscope to landsat-8 and sentinel-2 for sensing water quality in reservoirs in agricultural watersheds

  • Abubakarr S. Mansaray
  • , Andrew R. Dzialowski
  • , Meghan E. Martin
  • , Kevin L. Wagner
  • , Hamed Gholizadeh
  • , Scott H. Stoodley
  • Oklahoma State University

Research output: Contribution to journalArticlepeer-review

91 Scopus citations

Abstract

Agricultural runoff transports sediments and nutrients that deteriorate water quality erratically, posing a challenge to ground-based monitoring. Satellites provide data at spatial-temporal scales that can be used for water quality monitoring. PlanetScope nanosatellites have spatial (3 m) and temporal (daily) resolutions that may help improve water quality monitoring compared to coarser-resolution satellites. This work compared PlanetScope to Landsat-8 and Sentinel-2 in their ability to detect key water quality parameters. Spectral bands of each satellite were regressed against chlorophyll a, turbidity, and Secchi depth data from 13 reservoirs in Oklahoma over three years (2017–2020). We developed significant regression models for each satellite. Landsat-8 and Sentinel-2 explained more variation in chlorophyll a than PlanetScope, likely because they have more spectral bands. PlanetScope and Sentinel-2 explained relatively similar amounts of variations in turbidity and Secchi Disk data, while Landsat-8 explained less variation in these parameters. Since PlanetScope is a commercial satellite, its application may be limited to cases where the application of coarser-resolution satellites is not feasible. We identified scenarios where PS may be more beneficial than Landsat-8 and Sentinel-2. These include measuring water quality parameters that vary daily, in small ponds and narrow coves of reservoirs, and at reservoir edges.
Original languageEnglish
Article number1847
JournalRemote Sensing
Volume13
Issue number9
DOIs
StatePublished - May 1 2021

Keywords

  • Agricultural runoff
  • Chlorophyll a
  • Landsat-8
  • PlanetScope
  • Reservoirs
  • Secchi depth
  • Sentinel-2
  • Turbidity

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