Remote sensing of inland waters: Challenges, progress and future directions

Palmer, Stephanie C.; Kutser, Tiit; Hunter, Peter

doi:10.1016/j.rse.2014.09.021

Cited by 551 publications

(306 citation statements)

References 94 publications

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“…Despite all the advantages described above, the success of these physics-based approaches depends on two requirements: (1) remote sensing reflectance spectra must be accurately measured; and (2) model inputs including the depth, bottom reflectance, and water IOPs must be accurate for the sites of interest [9]. While much attention has been paid to collecting coincident measurements of IOPs and AOPs for oceanic systems (e.g., NASA SeaWiFS Bio-optical Archive and Storage System, http://seabass.gsfc.nasa.gov/), inland waters, especially river systems, have been poorly observed, even though what happens in ocean and coastal waters is highly dependent on these systems [16]. It is therefore important and necessary to develop a similar database/archive for bio-optical data of inland waters and make it accessible to the whole scientific community [17].…”

Section: Introductionmentioning

confidence: 99%

Developing a Comprehensive Spectral-Biogeochemical Database of Midwestern Rivers for Water Quality Retrieval Using Remote Sensing Data: A Case Study of the Wabash River and Its Tributary, Indiana

2016

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Abstract:A comprehensive spectral-biogeochemical database was developed for the Wabash River and the Tippecanoe River in Indiana, United States. This database includes spectral measurements of river water, coincident in situ measurements of water quality parameters (chlorophyll (chl), non-algal particles (NAP), and colored dissolved organic matter (CDOM)), nutrients (total nitrogen (TN), total phosphorus (TP), and dissolved organic carbon (DOC)), water-column inherent optical properties (IOPs), water depths, substrate types, and bottom reflectance spectra collected in summer 2014. With this dataset, the temporal variability of water quality observations was first analyzed and studied. Second, radiative transfer models were inverted to retrieve water quality parameters using a look-up table (LUT) based spectrum matching methodology. Results found that the temporal variability of water quality parameters and nutrients in the Wabash River was closely associated with hydrologic conditions. Meanwhile, there were no significant correlations found between these parameters and streamflow for the Tippecanoe River, due to the two upstream reservoirs, which increase the settling of sediment and uptake of nutrients. The poor relationship between CDOM and DOC indicates that most DOC in the rivers was from human sources such as wastewater. It was also found that the source of water (surface runoff or combined sewer overflow (CSO)), water temperature, and nutrients were important factors controlling instream concentrations of phytoplankton. The LUT retrieved NAP concentrations were in good agreement with field measurements with slope close to 1.0 and the average estimation error was 4.1% of independently obtained lab measurements. The error for chl estimation was larger (37.7%), which is attributed to the fact that the specific absorption spectrum of chl was not well represented in this study. The LUT retrievals for CDOM experienced large variability, probably due to the small data range collected in this study and the insensitivity of R rs to CDOM change. It is concluded that the success of the LUT method requires accurate spectral measurements and enough a priori information of the environment to construct a representative database for water quality retrieval. Therefore, future work will focus on continuing data collection in other seasons of the year and better characterization of the study area.

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Section: Introductionmentioning

confidence: 99%

Developing a Comprehensive Spectral-Biogeochemical Database of Midwestern Rivers for Water Quality Retrieval Using Remote Sensing Data: A Case Study of the Wabash River and Its Tributary, Indiana

2016

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“…Global change affects the environmental conditions rapidly. Therefore, Palmer et al [10] recommend more frequent observations of freshwater lakes to detect changes in water quality at an early stage. Remote sensing offers a timeand cost-effective method to support monitoring approaches including those recommended by the WFD.…”

Section: Introductionmentioning

confidence: 99%

“…Due to its capability to deliver information at high spatiotemporal resolution, remote sensing methods offer the potential to observe detailed seasonal changes in macrophyte distribution and water quality [11][12][13][14][15][16][17][18][19]. It can complement hitherto in-situ data collection along transects by divers and is suggested for closing the gap between the snapshots of in-situ mappings of the WFD [10,20]. It is expected that a high revisiting frequency may compensate the information loss compared to in-situ mapping by divers.…”

Section: Introductionmentioning

confidence: 99%

Seasonal Variation in Spectral Response of Submerged Aquatic Macrophytes: A Case Study at Lake Starnberg (Germany)

Fritz

Schneider

Geist

2017

Water

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Submerged macrophytes are important structural components of freshwater ecosystems that are widely used as long-term bioindicators for the trophic state of freshwater lakes. Climate change and related rising water temperatures are suspected to affect macrophyte growth and species composition as well as the length of the growing season. Alternative to the traditional ground-based monitoring methods, remote sensing is expected to provide fast and effective tools to map submerged macrophytes at short intervals and over large areas. This study analyses interrelations between spectral signature, plant phenology and the length of growing season as influenced by the variable water temperature. During the growing seasons of 2011 and 2015, remote sensing reflectance spectra of macrophytes and sediment were collected systematically in-situ with hyperspectral underwater spectroradiometer at Lake Starnberg, Germany. The established spectral libraries were used to develop reflectance models. The combination of spectral information and phenologic characteristics allows the development of a phenologic fingerprint for each macrophyte species. By inversion, the reflectance models deliver day and daytime specific spectral signatures of the macrophyte populations. The subsequent classification processing chain allowed distinguishing species-specific macrophyte growth at different phenologic stages. The analysis of spectral signatures within the phenologic development indicates that the invasive species Elodea nuttallii is less affected by water temperature oscillations than the native species Chara spp. and Potamogeton perfoliatus.

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“…Ocean color remote sensing offers new operational satellite missions based on medium ground resolution (of the order of 250 m) sensors, like the European Earth Observation Copernicus program Sentinel-3 Ocean and Land Colour Instrument (OLCI) mission, and the US Joint Polar Satellite System program Visible Infrared Imaging Radiometer Suite (VIIRS) sensors. These radiometers are particularly suitable for remote-sensing observations of inland water bodies and estuaries (Palmer et al, 2015;Kwiatkowska et al, 2016). The optical properties of CDOM, abundant in fresh and estuarine waters at high concentrations, shift the spectral maximum of the water transparency to solar radiation and water-leaving radiance towards the longer wavelengths (Darecki et al, 2003;Morel and Gentili, 2009).…”

Section: Introductionmentioning

confidence: 99%

Parameterization of the light absorption properties of chromophoric dissolved organic matter in the Baltic Sea and Pomeranian lakes

et al. 2016

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Abstract. This study presents three alternative models for estimating the absorption properties of chromophoric dissolved organic matter a CDOM (λ). For this analysis we used a database containing 556 absorption spectra measured in 2006-2009 in different regions of the Baltic Sea (open and coastal waters, the Gulf of Gdańsk and the Pomeranian Bay), at river mouths, in the Szczecin Lagoon and also in three lakes in Pomerania (Poland) -Obłęskie, Łebsko and Chotkowskie. The variability range of the chromophoric dissolved organic matter (CDOM) absorption coefficient at 400 nm, a CDOM (400), lay within 0.15-8.85 m −1 . The variability in a CDOM (λ) was parameterized with respect to the variability over 3 orders of magnitude in the chlorophyll a concentration Chl a (0.7-119 mg m −3 ). The chlorophyll a concentration and a CDOM (400) were correlated, and a statistically significant, nonlinear empirical relationship between these parameters was derived (R 2 = 0.83). On the basis of the covariance between these parameters, we derived two empirical mathematical models that enabled us to design the CDOM absorption coefficient dynamics in natural waters and reconstruct the complete CDOM absorption spectrum in the UV and visible spectral domains. The input variable in the first model was the chlorophyll a concentration, and in the second one it was a CDOM (400). Both models were fitted to a power function, and a second-order polynomial function was used as the exponent. Regression coefficients for these formulas were determined for wavelengths from 240 to 700 nm at 5 nm intervals. Both approximations reflected the real shape of the absorption spectra with a low level of uncertainty. Comparison of these approximations with other models of light absorption by CDOM demonstrated that our parameterizations were superior (bias from −1.45 to 62 %, RSME from 22 to 220 %) for estimating CDOM absorption in the optically complex waters of the Baltic Sea and Pomeranian lakes.

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Remote sensing of inland waters: Challenges, progress and future directions

Cited by 551 publications

References 94 publications

Developing a Comprehensive Spectral-Biogeochemical Database of Midwestern Rivers for Water Quality Retrieval Using Remote Sensing Data: A Case Study of the Wabash River and Its Tributary, Indiana

Developing a Comprehensive Spectral-Biogeochemical Database of Midwestern Rivers for Water Quality Retrieval Using Remote Sensing Data: A Case Study of the Wabash River and Its Tributary, Indiana

Seasonal Variation in Spectral Response of Submerged Aquatic Macrophytes: A Case Study at Lake Starnberg (Germany)

Parameterization of the light absorption properties of chromophoric dissolved organic matter in the Baltic Sea and Pomeranian lakes

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