How Satellite-Based Spectroscopy is Transforming Inland Water Quality Monitoring

Satellite-based spectroscopy depicting high-resolution image of Earth showcasing vibrant green rainforests, winding rivers, and deep blue oceans © TANAKORN-chronicles-stock.adobe.com

Satellites Take the Lead in Water Quality Surveillance

Inland water bodies like lakes, rivers, and reservoirs are vital to both ecosystems and human societies. Yet, industrial discharge, agricultural runoff, and weather have significantly deteriorated their quality. In response, a team of Chinese researchers has conducted a comprehensive review of recent advancements in using remote sensing for inland water monitoring, published in the journal Remote Sensing (1).

The study, titled “The Application of Remote Sensing Technology in Inland Water Quality Monitoring and Water Environment Science: Recent Progress and Perspectives,”, was authored by Lei Chen, Leizhen Liu, Shasha Liu, Zhenyu Shi, and Chunhong Shi. The researchers are affiliated with the School of Energy and Environmental Engineering at the University of Science and Technology Beijing and the College of Grassland Science and Technology at China Agricultural University (1)

Spectroscopic Techniques and Satellite Platforms for Water Quality Monitoring

Satellite-based remote sensing uses multispectral and hyperspectral imaging spectrometers to detect subtle changes in light reflected from water surfaces, key to assessing water quality. These instruments measure water-leaving radiance and surface reflectance across visible, near-infrared (NIR), and shortwave infrared (SWIR) wavelengths, which correspond to specific water quality indicators. For example, chlorophyll-a causes a reflectance peak near 700 nm, suspended sediments increase reflectance in the red and NIR bands, and colored dissolved organic matter (CDOM) absorbs strongly in the blue region. Key satellites equipped with these sensors include Sentinel-2A/B (with the MultiSpectral Instrument, MSI), Landsat 8 and 9 (with the Operational Land Imager, OLI), Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra and Aqua satellites, and Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (NPP) and NOAA-20 platforms. Hyperspectral sensors like those on the Chinese GF-5 and Italian PRecursore IperSpettrale della Missione Applicativa (PRISMA) satellites enable finer spectral resolution, supporting advanced retrieval algorithms that differentiate overlapping spectral signatures of multiple water constituents (1–5).

Mapping Water Health with Spectral Precision

The review emphasizes the essential role of remote sensing in monitoring both optically active and inactive water constituents. Using satellite-borne sensors, researchers can track water quality indicators such as chlorophyll-a, total suspended solids, colored dissolved organic matter, total nitrogen, phosphorus, and chemical oxygen demand (1).

The strength of this approach lies in spectroscopy, specifically, analyzing water-leaving radiance and reflectance signatures. These reflectance signals are influenced by the inherent optical properties (IOPs) of water, such as absorption and scattering, and are shaped by interactions between sunlight, the water’s surface, and suspended materials. With modern spectrometers like Sentinel-2’s MSI and Landsat 8/9’s OLI, high-resolution data now enables large-scale, near-real-time environmental assessments (1).

From Reflectance to Real-Time Pollution Insights

Spectroscopic analysis plays a key role in translating spectral data into meaningful environmental insights. For instance, the presence of chlorophyll causes a reflectance peak in the near-infrared band, while suspended sediments increase visible light reflectance due to scattering. These changes, when interpreted correctly, reveal not only current pollution levels but also trends over time, offering early warnings for environmental degradation (1–5).

To extract accurate information, researchers rely on atmospheric correction algorithms to minimize interference from aerosols and cloud cover. Traditional methods, like the dark pixel assumption, have proven insufficient for complex inland waters. Newer approaches use the shortwave infrared (SWIR) spectrum and advanced radiative transfer models such as MODTRAN, 6S, and FLAASH to improve accuracy, although challenges remain (1).

Tracking Pollution, Climate Impact, and Carbon Budgets

Beyond water quality, remote sensing also enables broader environmental applications. The reviewed literature details how spatial and temporal datasets help identify pollution sources, track carbon fluxes, and understand climate-related changes in water bodies. By analyzing long-term satellite data, scientists can model carbon stocks and assess inland waters' role in the global carbon cycle—essential knowledge for shaping climate policy (1–5).

Pollution source tracking is another area where remote sensing excels. Whether it’s industrial discharge, algal blooms, or agricultural runoff, combining remote sensing with inversion algorithms and indices allows precise localization of contamination hotspots, providing critical guidance for remediation and regulatory actions (1).

Global Research Trends Show Explosive Growth

A bibliometric analysis included in the study reveals a dramatic rise in remote sensing research for water environments, with 2,838 articles published between 2000 and 2024. The number peaked in 2023 with 377 papers. Leading contributors include China, the US, and Italy, with the Chinese Academy of Sciences topping the list at 353 publications (1).

Hotspots in keyword analysis highlight a sustained focus on water quality, algorithm development, and optically active constituents. Major journals publishing in this domain include Remote Sensing, Science of the Total Environment, and Remote Sensing of Environment (1).

Challenges and the Road Ahead

Despite these advances, the study acknowledges several hurdles. The optical complexity of inland waters, limitations in current satellite sensor capabilities, and the reliance on empirical models restrict current applications. The authors recommend that future research focus on refining atmospheric correction methods, enhancing multi-source data fusion, and developing robust models for non-optically active constituents (1).

By deepening scientific understanding and improving analytical precision, remote sensing is poised to play an even greater role in safeguarding inland water resources.

References

(1) Chen, L.; Liu, L.; Liu, S.; Shi, Z.; Shi, C. The Application of Remote Sensing Technology in Inland Water Quality Monitoring and Water Environment Science: Recent Progress and Perspectives. Remote Sens. 2025, 17 (4), 667. DOI: 10.3390/rs17040667

(2) Justice, C. O.; Giglio, L.; Korontzi, S.; Owens, J.; Morisette, J. T.; Roy, D.; Descloitres, J.; Alleaume, S.; Petitcolin, F.; Kaufman, Y. The MODIS Fire Products. Remote Sens. Environ. 2002, 83 (1–2), 244–262. DOI: 10.1016/S0034-4257(02)00076-7

(3) Hillger, D. W.; Kopp, T. J.; Lee, J.; Lindsey, D. T.; Seaman, C. J.; Miller, S. D.; Solbrig, J. E.; Riishojgaard, L. P.; Kidder, S. Q. First-Light Imagery from Suomi NPP VIIRS. Bull. Am. Meteorol. Soc. 2013, 94 (7), 1019–1029. DOI: 10.1175/BAMS-D-12-00097.1

(4) Liu, Y. N.; Sun, D. X.; Hu, X. N.; Ye, X.; Li, Y. D.; Liu, S. F.; Cao, K. Q.; Chai, M. Y.; Zhang, J.; Zhang, Y.; Sun, W. W. The Advanced Hyperspectral Imager: Aboard China's GaoFen-5 Satellite. IEEE Geosci. Remote Sens. Mag. 2019, 7 (4), 23–32. DOI: 10.1109/MGRS.2019.2927687

(5) Loizzo, R.; Guarini, R.; Longo, F.; Scopa, T.; Formaro, R.; Facchinetti, C.; Varacalli, G. PRISMA: The Italian Hyperspectral Mission. In IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium; IEEE: Valencia, Spain, 2018; pp 175–178. DOI: 10.1109/IGARSS.2018.8518512