| publications-2121 |
Peer reviewed articles |
2022 |
Stefan G. H. Simis; Peter D. Hunter; Mark W. Matthews; Evangelos Spyrakos; Andrew Tyler; Diana Vaičiūté |
Improved hyperspectral inversion of aquatic reflectance under non-uniform vertical mixing |
Optics express |
10.1364/oe.450374 |
Simulation & Modeling |
Irrigation Systems |
|
Estimating the concentration of water constituents by optical remote sensing assumes absorption and scattering processes to be uniform over the observation depth. Using hyperspectral reflectance, we present a method to direct the retrieval of the backscattering coefficient (bb(λ)) from reflectance (> 600 nm) towards wavebands where absorption by water dominates the reflectance curve. Two experiments demonstrate the impact of hyperspectral inversion in the selected band set. First, optical simulations show that the resulting distribution of bb(λ) is sensitive to particle mixing conditions, although a robust indicator of non-uniformity was not found for all scenarios of stratification. Second, in the absence of spectral backscattering profiles from in situ data sets, it is shown how substituting the median of bb(λ) into a near infra-red / red band ratio algorithm improved chlorophyll-a estimates (root mean square error 75.45 mg m−3 became 44.13 mg m−3). This approach also allows propagation of the uncertainty in bb estimates to water constituent concentrations. |
776480 |
|
|
|
| publications-2122 |
Peer reviewed articles |
2022 |
Gavin H. Tilstone, Silvia Pardo, Stefan G. H. Simis, Ping Qin, Nick Selmes, David Dessailly and Ewa Kwiatkowska |
Consistency between Satellite Ocean Colour Products under High Coloured Dissolved Organic Matter Absorption in the Baltic Sea |
Remote Sensing |
10.3390/rs14010089 |
Simulation & Modeling |
Precipitation & Ecological Systems |
|
Ocean colour (OC) remote sensing is an important tool for monitoring phytoplankton in the global ocean. In optically complex waters such as the Baltic Sea, relatively efficient light absorption by substances other than phytoplankton increases product uncertainty. Sentinel-3 OLCI-A, Suomi-NPP VIIRS and MODIS-Aqua OC radiometric products were assessed using Baltic Sea in situ remote sensing reflectance (Rrs) from ferry tracks (Alg@line) and at two Aerosol Robotic Network for Ocean Colour (AERONET-OC) sites from April 2016 to September 2018. A range of atmospheric correction (AC) processors for OLCI-A were evaluated. POLYMER performed best with <23 relative % difference at 443, 490 and 560 nm compared to in situ Rrs and 28% at 665 nm, suggesting that using this AC for deriving Chl a will be the most accurate. Suomi-VIIRS and MODIS-Aqua underestimated Rrs by 35, 29, 22 and 39% and 34, 22, 17 and 33% at 442, 486, 560 and 671 nm, respectively. The consistency between different AC processors for OLCI-A and MODIS-Aqua and VIIRS products was relatively poor. Applying the POLYMER AC to OLCI-A, MODIS-Aqua and VIIRS may produce the most accurate Rrs and Chl a products and OC time series for the Baltic Sea. |
776480 |
|
|
|
| publications-2123 |
Peer reviewed articles |
2022 |
Mortimer Werther, Daniel Odermatt, Stefan G.H.Simis, Daniela Gurlind, Daniel S.F. Jorgee, Hubert Loisele, Peter D.Hunter, Andrew N.Tylera, Evangelos Spyrakos |
Characterising retrieval uncertainty of chlorophyll-a algorithms in oligotrophic and mesotrophic lakes and reservoirs. |
ISPRS Journal of Photogrammetry and Remote Sensing |
10.1016/j.isprsjprs.2022.06.015 |
Simulation & Modeling |
Irrigation Systems |
|
No abstract available |
776480 |
|
|
|
| publications-2124 |
Peer reviewed articles |
2019 |
Olivier Burggraaff, Norbert Schmidt, Jaime Zamorano, Klaas Pauly, Sergio Pascual, Carlos Tapia, Evangelos Spyrakos, Frans Snik |
Standardized spectral and radiometric calibration of consumer cameras |
Optics Express |
10.1364/oe.27.019075 |
Data Management & Analytics |
Precipitation & Ecological Systems |
|
No abstract available |
776480 |
|
|
|
| publications-2125 |
Peer reviewed articles |
2021 |
Nima Pahlevan; Antoine Mangin; Sundarabalan V. Balasubramanian; Brandon I Smith; Krista Alikas; Kohei Arai; Claudio Clemente Faria Barbosa; Simon Bélanger; Caren Binding; Mariano Bresciani; Claudia Giardino; Daniela Gurlin; Yongzhen Fan; Tristan Harmel; Peter D. Hunter; Joji Ishikaza; Susanne Kratzer; Moritz K. Lehmann; Martin Ligi; Ronghua Ma; François Régis Martin-Lauzer; Leif G. Olmanson; Na |
ACIX-Aqua: A global assessment of atmospheric correction methods for Landsat-8 and Sentinel-2 over lakes, rivers, and coastal waters |
https://hal.inrae.fr/hal-03318738 |
10.1016/j.rse.2021.112366 |
Uncategorized |
Precipitation & Ecological Systems |
|
No abstract available |
776480 |
|
|
|
| publications-2126 |
Peer reviewed articles |
2021 |
Mortimer Werther, Evangelos Spyrakos, Stefan G.H.Simis, Daniel Odermatt, Kerstin Stelzer, Harald Krawczyk, Oberon Berlage, Peter Hunter, Andrew Tyler |
Meta-classification of remote sensing reflectance to estimate trophic status of inland and nearshore waters |
ISPRS Journal of Photogrammetry and Remote Sensing |
10.1016/j.isprsjprs.2021.04.003 |
Uncategorized |
Irrigation Systems |
|
No abstract available |
776480 |
|
|
|
| publications-2127 |
Peer reviewed articles |
2022 |
Thomas M. Jordan 1, Stefan G. H. Simis, Philipp M. M. Grötsch, John Wood |
Incorporating a Hyperspectral Direct-Diffuse Pyranometer in an Above-Water Reflectance Algorithm |
Remote Sens |
10.3390/rs14102491 |
AI & Machine Learning |
Groundwater |
|
In situ hyperspectral remote-sensing reflectance (Rrs(λ)) is used to derive water quality products and perform autonomous monitoring of aquatic ecosystems. Conventionally, above-water Rrs(λ) is estimated from three spectroradiometers which measure downwelling planar irradiance (Ed(λ)), sky radiance (Ls(λ)), and total upwelling radiance (Lt(λ)), with a scaling of Ls(λ)/Ed(λ) used to correct for surface-reflected radiance. Here, we incorporate direct and diffuse irradiance, (Edd(λ)) and Eds(λ)), from a hyperspectral pyranometer (HSP) in an Rrs(λ) processing algorithm from a solar-tracking radiometry platform (So-Rad). HSP measurements of sun and sky glint (scaled Edd(λ)/Ed(λ) and Eds(λ)/Ed(λ)) replace model-optimized terms in the 3C (three-glint component) Rrs(λ) algorithm, which estimates Rrs(λ) via spectral optimization of modelled atmospheric and water properties with respect to measured radiometric quantities. We refer to the HSP-enabled method as DD (direct-diffuse) and compare differences in Rrs(λ) and Rrs(λ) variability (assessed over 20 min measurement cycles) between 3C and DD as a function of atmospheric optical state using data from three ports in the Western Channel. The greatest divergence between the algorithms occurs in the blue part of the spectrum where DD has significantly lower Rrs(λ) variability than 3C in clearer sky conditions. We also consider Rrs(λ) processing from a hypothetical two-sensor configuration (using only the Lt(λ) spectroradiometer and the HSP and referred to as DD2) as a potential lower-cost measurement solution, which is shown to have comparable Rrs(λ) and Rrs(λ) variability to DD in clearer sky conditions. Our results support that the HSP sensor can fulfil a dual role in aquatic ecosystem monitoring by improving precision in Rrs(λ) alongside its primary function to characterize aerosols. |
776480 |
|
|
|
| publications-2128 |
Peer reviewed articles |
2020 |
Olivier Burggraaff |
Biases from incorrect reflectance convolution |
Optics Express |
10.1364/oe.391470 |
Digital twin |
Irrigation Systems |
|
Reflectance, a crucial earth observation variable, is converted from hyperspectral to multispectral through convolution. This is done to combine time series, validate instruments, and apply retrieval algorithms. However, convolution is often done incorrectly, with reflectance itself convolved rather than the underlying (ir)radiances. Here, the resulting error is quantified for simulated and real multispectral instruments, using 18 radiometric data sets (N = 1799 spectra). Biases up to 5% are found, the exact value depending on the spectrum and band response. This significantly affects extended time series and instrument validation, and is similar in magnitude to errors seen in previous validation studies. Post-hoc correction is impossible, but correctly convolving (ir)radiances prevents this error entirely. This requires publication of original data alongside reflectance. |
776480 |
|
|
|
| publications-2129 |
Peer reviewed articles |
2022 |
Moshi H, Kimirei I, Shilla D, O'reilly C, Wehrli B, Ehrenfels B, Loiselle S. |
Citizen scientist monitoring accurately reveals nutrient pollution dynamics in Lake Tanganyika coastal waters |
Environmental Monitoring and Assessment |
10.1007/s10661-022-10354-8 |
AI & Machine Learning |
Precipitation & Ecological Systems |
|
AbstractSeveral studies in Lake Tanganyika have effectively employed traditional methods to explore changes in water quality in open waters; however, coastal monitoring has been restricted and sporadic, relying on costly sample and analytical methods that require skilled technical staff. This study aims in validating citizen science water quality collected data (nitrate, phosphate and turbidity) with those collected and measured by professional scientists in the laboratory. A second objective of the study is to use citizen scientist data to identify the patterns of seasonal and spatial variations in nutrient conditions and forecast potential changes based on expected changes in population and climate (to 2050). The results showed that the concentrations of nitrate and phosphate measured by citizen scientists nearly matched those established by professional scientists, with overall accuracy of 91% and 74%, respectively. For total suspended solids measured by professional and turbidity measured by citizen scientists, results show that, using 14 NTU as a cut-off, citizen scientist measurements of Secchi tube depth to identify lake TSS below 7.0 mg/L showed an accuracy of 88%. In both laboratory and citizen scientist-based studies, all measured water quality variables were significantly higher during the wet season compared to the dry season. Climate factors were discovered to have a major impact on the likelihood of exceeding water quality restrictions in the next decades (2050), which could deteriorate lake conditions. Upscaling citizen science to more communities on the lake and other African Great Lakes would raise environmental awareness, inform management and mitigation activities, and aid long-term decision-making. |
776480 |
|
|
|
| publications-2130 |
Peer reviewed articles |
2021 |
Mark A.Warren, Stefan G.H.Simis, NickSelmes |
Complementary water quality observations from high and medium resolution Sentinel sensors by aligning chlorophyll-a and turbidity algorithms. |
Remote Sensing of Environment |
10.1016/j.rse.2021.112651 |
Uncategorized |
Irrigation Systems |
|
No abstract available |
776480 |
|
|
|
