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Sensitivity analysis of the dark spectrum fitting atmospheric correction for metre- and decametre-scale satellite imagery using autonomous hyperspectral radiometry
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The performance of the dark spectrum fitting (DSF) atmospheric correction algorithm is evaluated using matchups between metre- and decametre-scale satellite imagery as processed with ACOLITE and measurements from autonomous PANTHYR hyperspectral radiometer systems deployed in the Adriatic and North Sea. Imagery from the operational land imager (OLI) on Landsat 8, the multispectral instrument (MSI) on Sentinel-2 A and B, and the PlanetScope CubeSat constellation was processed for both sites using a fixed atmospheric path reflectance in a small region of interest around the system&\#x2019;s deployment location, using a number of processing settings, including a new sky reflectance correction. The mean absolute relative differences (MARD) between in situ and satellite measured reflectances reach <20&\#x0025; in the Blue and 11&\#x0025; in the Green bands around 490 and 560 nm for the best performing configuration for MSI and OLI. Higher relative errors are found for the shortest Blue bands around 440 nm (30&\#x2013;100&\#x0025; MARD), and in the Red-Edge and near-infrared bands (35&\#x2013;100&\#x0025; MARD), largely influenced by the lower absolute data range in the observations. Root mean squared differences (RMSD) increase from 0.005 in the NIR to about 0.015&\#x2013;0.020 in the Blue band, consistent with increasing atmospheric path reflectance. Validation of the Red-Edge and NIR bands on Sentinel-2 is presented, as well as for the first time, the Panchromatic band (17&\#x2013;26&\#x0025; MARD) on Landsat 8, and the derived Orange contra-band (8&\#x2013;33&\#x0025; MARD for waters in the algorithm domain, and around 40&\#x2013;80&\#x0025; MARD overall). For Sentinel-2, excluding the SWIR bands from the DSF gave better performances, likely due to calibration issues of MSI at longer wavelengths. Excluding the SWIR on Landsat 8 gave good performance as well, indicating robustness of the DSF to the available band set. The DSF performance was found to be rather insensitive to (1) the wavelength spacing in the lookup tables used for the atmospheric correction, (2) the use of default or ancillary information on gas concentration and atmospheric pressure, and (3) the size of the ROI over which the path reflectance is estimated. The performance of the PlanetScope constellation is found to be similar to previously published results, with the standard DSF giving the best results in the visible bands in terms of MARD (24&\#x2013;40&\#x0025; overall, and 18&\#x2013;29&\#x0025; for the turbid site). The new sky reflectance correction gave mixed results, although it reduced the mean biases for certain configurations and improved results for the processing excluding the SWIR bands, giving lower RMSD and MARD especially at longer wavelengths (>600 nm). The results presented in this article should serve as guidelines for general use of ACOLITE and the DSF.
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RBINS Staff Publications 2020
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Combined land surface emissivity and temperature estimation from Landsat 8 OLI and TIRS
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Remote sensing of Land Surface Temperature (LST) generally requires atmospheric parameters and the emissivity (∊) of the target to be estimated. The atmospheric up- and downwelling radiances and transmittance can be accurately modelled using radiative transfer models and profiles of relative humidity and temperature, either measured by radiosonde probes or retrieved from assimilating weather models. The estimation of ∊ is a large source of uncertainty in the resulting LST product, and there are various approaches using multi-angle observations, multispectral optical or multispectral thermal infrared imagery. In this paper, the estimation of LST from the Thermal InfraRed Sensor (TIRS) on board Landsat 8 is evaluated using more than 6 years of in situ temperature measurements from a network of 14 Autonomous Weather Stations (AWS) in Belgium. ∊ is estimated from concomitant atmospherically corrected imagery from the Operational Land Imager (OLI) using two new neural network approaches trained on ECOSTRESS spectra, and an established NDVI based method. Results are compared to using ∊=1 and the ASTER Global Emissivity Dataset. LST retrievals from L8/TIRS perform well for all emissivity data sources for 500 matchups with AWS subsoil temperature measurements: Mean Differences 0.8–3.7 K and unbiased Root Mean Squared Differences of 2.9–3.5 K for both B10 and B11. The use of unity emissivity gives the best results in terms of MD (0.8 K) and unb-RMSD (3 K). Similar ranges of unb-RMSD are found for 500 matchups with broadband radiometer temperatures (2.6–3.1 K), that have lower absolute MD values (−2.2–0.6 K). For the radiometer temperatures, both the neural net approaches gave lowest MD, in the best case ±0.1 K. The present investigation can hence recommend the neural nets to derive ∊ for the retrieval of LST over the AWS in Belgium. Using published matchup results from other authors however, no single source of ∊ data performed better than ∊=1, but this could be due to their low number of matchups. Further efforts for estimating representative pixel average emissivities are needed, and establishing a denser in situ measurement network over varied land use, with rather homogeneous land cover within a TIRS pixel, may aid further validation of a per pixel and per scene ∊ estimates from multispectral imagery. AWS data seems valuable for evaluation of satellite LST, with the advantage of a much lower cost and higher potential matchup density compared to conventional radiometers.
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RBINS Staff Publications 2020
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Automated water surface temperature retrieval from Landsat 8/TIRS
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Satellite remote sensing of Land and Water Surface Temperature (L/WST) has many applications in studies of terrestrial and aquatic ecology. Retrieval of L/WST requires a well calibrated radiometer and an accurate atmospheric correction. In the present study, the performance of the Thermal InfraRed Sensor (TIRS) on board Landsat 8 is evaluated for the retrieval of L/WST. libRadtran is used to retrieve atmospheric correction parameters based on atmospheric profiles of relative humidity and temperature from three global atmospheric models. Performance of single band retrievals is compared to typical MODTRAN results from the Atmospheric Correction Parameter Calculator (ACPC) and a split-window approach. A multi-temporal land masking method using imagery from the Operational Land Imager (OLI) on board Landsat 8 is demonstrated, and is used to automatically classify imagery in the matchup dataset in three classes of cloud cover. Two sources of in situ data covering the Belgian Coastal Zone (BCZ) are used for validation of the L/WST product: (1) fixed locations in the Flemish Banks measurement network and (2) underway data from regular RV Belgica campaigns. In the present study the single band methods outperformed the split-window approach, and consistent retrievals are found for the MODTRAN and libRadtran simulations. Typical single band surface temperature retrievals in quasi cloud-free conditions have Root Mean Squared Differences (RMSD) of 0.7 K and 1 K for Bands 10 and 11 with low bias, depending on the method and atmospheric profile source. For imagery with scattered clouds, RMSD values increase to 1 K and 2 K respectively with an approximately 0.5 K cold bias, likely caused by cloud proximity. The calibration efforts combined into Collection 1 allows for accurate absolute surface temperature retrievals from B10 on Landsat 8/TIRS for homogeneous targets with known emissivity, such as liquid water. The method is adapted to global processing and can be used for Land Surface Temperature retrieval with a suitable source of emissivity data.
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RBINS Staff Publications 2020
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Revalidation of Enteromius alberti and presence of Enteromius cf. mimus (Cypriniformes: Cyprinidae) in the Lake Edward system, East Africa
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RBINS Staff Publications 2020
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Unravelling the evolution of Africa’s drainage basins through a widespread freshwater fish, the African sharptooth catfish Clarias gariepinus
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RBINS Staff Publications 2020
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DNA barcoding echinoderms of the East Coast of South Africa
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RBINS Staff Publications 2017
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DNA barcoding halictine bee species from Europe and Africa
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RBINS Staff Publications 2017
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West African Manatee Trichechus senegalensis (LINK, 1795) in the Estuary of the Congo River (Democratic Republic of the Congo): Review and Update
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RBINS Staff Publications 2017
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Highly polymorphic mitochondrial DNA and deceiving haplotypic differentiation: implications for assessing population genetic differentiation and connectivity
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Background Hyperdiverse mtDNA with more than 5% of variable synonymous nucleotide sites can lead to erroneous interpretations of population genetic differentiation patterns and parameters (φST, DEST). We illustrate this by using hyperdiverse mtDNA markers to infer population genetic differentiation and connectivity in Melarhaphe neritoides, a NE Atlantic (NEA) gastropod with a high dispersal potential. We also provide a recent literature example of how mtDNA hyperdiversity may have misguided the interpretation of genetic connectivity in the crab Opecarcinus hypostegus. Results mtDNA variation surveyed throughout the NEA showed that nearly all M. neritoides specimens had haplotypes private to populations, suggesting at first glance a lack of gene flow and thus a strong population genetic differentiation. Yet, the bush-like haplotype network, though visually misleading, showed no signs of phylogeographic or other haplotype structuring. Coalescent-based gene flow estimates were high throughout the NEA, irrespective of whether or not mtDNA hyperdiversity was reduced by removing hypervariable sites. Conclusions Melarhaphe neritoides seems to be panmictic over the entire NEA, which is consistent with its long-lived pelagic larval stage. With hyperdiverse mtDNA, the apparent lack of shared haplotypes among populations does not necessarily reflect a lack of gene flow and/or population genetic differentiation by fixation of alternative haplotypes (DEST ≈ 1 does not a fortiori imply φST ≈ 1), but may be due to (1) a too low sampling effort to detect shared haplotypes and/or (2) a very high mutation rate that may conceal the signal of gene flow. Hyperdiverse mtDNA can be used to assess connectivity by coalescent-based methods. Yet, the combined use of φST and DEST can provide a reasonable inference of connectivity patterns from hyperdiverse mtDNA, too.
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RBINS Staff Publications 2019
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Fitness-heterozygosity associations differ between male and female winter moths Operophtera brumata L.
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The association between heterozygosity and fitness is positive but weak on average and varies between studies. inbreeding has been invoked as the driving force between the positive heterozygosity-fitness associations, yet in spatio-temporally stable environments a negative correlation is expected. Furthermore, different patterns can arise because of the effects of natural selection on different loci and variation can be expected among groups of individuals that experience different levels of stress. In this paper we report on fitness-heterozygosity associations in the winter moth for six allozyme loci. The relationship is estimated for males and females separately, in four areas differing in their degree of fragmentation, and variation among loci is modelled. We introduce a linear mixed model framework to achieve this analysis. This approach differs from more traditional (multiple) regression analyses and allows testing specific interactions. We show that fitness, as estimated by body size, is negatively correlated with heterozygosity, but only so in females. This association does not vary significantly among loci and the four areas. We speculate that a trade-off between fitness-consequences of inbreeding and outbreeding at different stages of the winter moth life cycle could explain the observed patterns.
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Belgian Journal of Zoology
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Bibliographic References
