Advancements in Satellite Observations of Inland and Coastal Waters: Building Towards a Global Validation Network

Avouris, Dulcinea M.; Maciel, Fernanda; Sharp, Samantha L.; Craig, Susanne E.; Dekker, Arnold G.; Vittorio, Courtney A.; Gardner, John R.; Goldsmith, Emma; Greb, Steven R.; Smail, Emily A.; Wang, Menghua

doi:10.3390/rs17244008

i

Advancements in Satellite Observations of Inland and Coastal Waters: Building Towards a Global Validation Network

Supporting Files

2025
By Avouris, Dulcinea M. ; Maciel, Fernanda ; Sharp, Samantha L. ; ...

Details

Journal Title:

Remote Sensing
Personal Author:

Avouris, Dulcinea M. ; Maciel, Fernanda ; Sharp, Samantha L. ; Craig, Susanne E. ; Dekker, Arnold G. ; Vittorio, Courtney A. ; Gardner, John R. ; Goldsmith, Emma ; Greb, Steven R. ; Smail, Emily A. ; Wang, Menghua
NOAA Program & Office:

NESDIS (National Environmental Satellite, Data, and Information Service) ; STAR (Center for Satellite Applications and Research) ; OSPO (Office of Satellite and Product Operations) ; CIMSS (Cooperative Institute for Meteorological Satellite Studies)
Description:

The use of satellite-based remote sensing imagery for water quality monitoring of inland and coastal waters has become widespread over the last few decades, with the expansion of, and investment in, operational Earth-observing missions. Satellite-based sensors are uniquely suited to provide synoptic, system-wide water quality parameter estimates that supplement traditional field-based sampling methods. The remote sensing of water quality parameter estimates is particularly valuable in systems with high temporal and spatial variability, as well as in areas that are difficult to access, or where agencies lack funding for routine monitoring. However, optically complex inland and coastal waters pose additional challenges for developing robust remote sensing retrieval models for optical properties and water quality parameters. One of the biggest challenges is collecting high quality field measurements that are used to calibrate and validate the retrieval algorithms. Here, we present the current status of satellite missions, field methods that include instruments used and commonly measured parameters, and repositories of historical field data that are relevant to inland and coastal water studies. We then present data requirements for model validation and highlight gaps in validation coverage. Finally, we provide considerations for future field campaigns to improve coordination with remote sensing data collection and ensure that field data is well suited for use in model or algorithm development.
Keywords:

Remote Sensing Water Quality Remote Sensing Water Quality Field Measurements Monitoring Validation
Source:

Remote Sens.2025, 17(24), 4008
DOI:

https://doi.org/10.3390/rs17244008
Format:

PDF
Document Type:

Journal Article
License:

https://creativecommons.org/publicdomain/zero/1.0/
Rights Information:

CC BY
Compliance:

Submitted
Main Document Checksum:

urn:sha-512:2f4d1c5cb22ee0cbd55e3353b654151459d0b712540c3cfc5faff247d6aba556c726c2703220bcb86a2034d5a161fd7349d2db16c19eb088d1357595b23524df
Download URL:

https://repository.library.noaa.gov/view/noaa/73391/noaa_73391_DS1.pdf
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[PDF - 3.91 MB ]

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