16 resultados para the Fuzzy Colour Segmentation Algorithm

em Plymouth Marine Science Electronic Archive (PlyMSEA)


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Satellite-derived remote-sensing reflectance (Rrs) can be used for mapping biogeochemically relevant variables, such as the chlorophyll concentration and the Inherent Optical Properties (IOPs) of the water, at global scale for use in climate-change studies. Prior to generating such products, suitable algorithms have to be selected that are appropriate for the purpose. Algorithm selection needs to account for both qualitative and quantitative requirements. In this paper we develop an objective methodology designed to rank the quantitative performance of a suite of bio-optical models. The objective classification is applied using the NASA bio-Optical Marine Algorithm Dataset (NOMAD). Using in situRrs as input to the models, the performance of eleven semi-analytical models, as well as five empirical chlorophyll algorithms and an empirical diffuse attenuation coefficient algorithm, is ranked for spectrally-resolved IOPs, chlorophyll concentration and the diffuse attenuation coefficient at 489 nm. The sensitivity of the objective classification and the uncertainty in the ranking are tested using a Monte-Carlo approach (bootstrapping). Results indicate that the performance of the semi-analytical models varies depending on the product and wavelength of interest. For chlorophyll retrieval, empirical algorithms perform better than semi-analytical models, in general. The performance of these empirical models reflects either their immunity to scale errors or instrument noise in Rrs data, or simply that the data used for model parameterisation were not independent of NOMAD. Nonetheless, uncertainty in the classification suggests that the performance of some semi-analytical algorithms at retrieving chlorophyll is comparable with the empirical algorithms. For phytoplankton absorption at 443 nm, some semi-analytical models also perform with similar accuracy to an empirical model. We discuss the potential biases, limitations and uncertainty in the approach, as well as additional qualitative considerations for algorithm selection for climate-change studies. Our classification has the potential to be routinely implemented, such that the performance of emerging algorithms can be compared with existing algorithms as they become available. In the long-term, such an approach will further aid algorithm development for ocean-colour studies.

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Phytoplankton abundance in the NW Atlantic was measured by continuous plankton recorder (CPR) sampling along tracks between Iceland and the western Scotian Shelf from 1998 to 2006, when sea-surface chlorophyll (SSChl) measurements were also being made by ocean colour satellite imagery using the SeaWiFS sensor. Seasonal and inter-annual changes in phytoplankton abundance were examined using data collected by both techniques, averaged over each of four shelf regions and four deep ocean regions. CPR sampling had gaps (missing months) in all regions and in the four deep ocean regions satellite observations were too sparse between November and February to be of use. Average seasonal cycles of SSChl were similar to those of total diatom abundance in seven regions, to those of the phytoplankton colour index in six regions, but were not similar to those of total dinoflagellate abundance anywhere. Large inter-annual changes in spring bloom dynamics were captured by both samplers in shelf regions. Changes in annual (or 8 months) averages of SSChl did not generally follow those of the CPR indices within regions and multi-year averages of SSChl, and the three CPR indices were generally higher in shelf than in deep ocean regions. Remote sensing and CPR sampling provide complementary ways of monitoring phytoplankton in the ocean: the former has superior temporal and spatial coverage and temporal resolution, and the latter provides better taxonomic information.

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Changes in phytoplankton dynamics influence marine biogeochemical cycles, climate processes, and food webs, with substantial social and economic consequences. Large-scale estimation of phytoplankton biomass was possible via ocean colour measurements from two remote sensing satellites – the Coastal Zone Color Scanner (CZCS, 1979-1986) and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS, 1998-2010). Due to the large gap between the two satellite eras and differences in sensor characteristics, comparison of the absolute values retrieved from the two instruments remains challenging. Using a unique in situ ocean colour dataset that spans more than half a century, the two satellite-derived chlorophyll-a (Chl-a) eras are linked to assess concurrent changes in phytoplankton variability and bloom timing over the Northeast Atlantic Ocean and North Sea. Results from this unique re-analysis reflect a clear increasing pattern of Chl-a, a merging of the two seasonal phytoplankton blooms producing a longer growing season and higher seasonal biomass, since the mid-1980s. The broader climate plays a key role in Chl-a variability as the ocean colour anomalies parallel the oscillations of the Northern Hemisphere Temperature (NHT) since 1948.

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The phytoplankton colour index (PCI) of the Continuous Plankton Recorder (CPR) survey is an in situ measure of ocean colour, which is considered a proxy of the phytoplankton biomass. PCI has been extensively used to describe the major spatiotemporal patterns of phytoplankton in the North Atlantic Ocean and North Sea since 1931. Regardless of its wide application, the lack of an adequate evaluation to test the PCI's quantitative nature is an important limitation. To address this concern, a field trial over the main production season has been undertaken to assess the numerical values assigned by previous investigations for each category of the greenness of the PCI. CPRs were towed across the English Channel from Roscoff to Plymouth consecutively for each of 8 months producing 76 standard CPR samples, each representing 10 nautical miles of tow. The results of this experiment test and update the PCI methodology, and confirm the validity of this long-term in situ ocean colour data set. In addition, using a 60-year time series of the PCI of the western English Channel, a comparison is made between the previous and the current revised experimental calculations of PCI.

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The heterogeneity in phytoplankton production in the North Atlantic after the spring bloom is poorly understood. We analysed merged microwave and infrared satellite sea surface temperature (SST) data and ocean colour phytoplankton size class biomass, primary production (PP) and new production (ExP) derived from SeaWiFS data, to assess the spatial and temporal frequency of surface thermal fronts and areas of enhanced PP and ExP. Strong and persistent surface thermal fronts occurred at the Reykjanes Ridge (RR) and sub-polar front (SPF), which sustain high PP and ExP and, outside of the spring bloom, account for 9% and 15% of the total production in the North Atlantic. When normalised by area, PP at the SPF is four times higher than the RR. Analysis of 13 years of satellite ocean colour data from SeaWiFS, and compared with MODIS-Aqua and MERIS, showed that there was no increase in Chla from 1998 to 2002, which then decreased in all areas from 2002 to 2007 and was most pronounced in the RR. These time series also illustrated that the SPF exhibited the highest PP and the lowest variation in Chla over the ocean colour record. This implies that the SPF provides a high and consistent supply of carbon to the benthos irrespective of fluctuations in the North Atlantic Oscillation.

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Satellite-based remote sensing of active fires is the only practical way to consistently and continuously monitor diurnal fluctuations in biomass burning from regional, to continental, to global scales. Failure to understand, quantify, and communicate the performance of an active fire detection algorithm, however, can lead to improper interpretations of the spatiotemporal distribution of biomass burning, and flawed estimates of fuel consumption and trace gas and aerosol emissions. This work evaluates the performance of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) Fire Thermal Anomaly (FTA) detection algorithm using seven months of active fire pixels detected by the Moderate Resolution Imaging Spectroradiometer (MODIS) across the Central African Republic (CAR). Results indicate that the omission rate of the SEVIRI FTA detection algorithm relative to MODIS varies spatially across the CAR, ranging from 25% in the south to 74% in the east. In the absence of confounding artifacts such as sunglint, uncertainties in the background thermal characterization, and cloud cover, the regional variation in SEVIRI's omission rate can be attributed to a coupling between SEVIRI's low spatial resolution detection bias (i.e., the inability to detect fires below a certain size and intensity) and a strong geographic gradient in active fire characteristics across the CAR. SEVIRI's commission rate relative to MODIS increases from 9% when evaluated near MODIS nadir to 53% near the MODIS scene edges, indicating that SEVIRI errors of commission at the MODIS scene edges may not be false alarms but rather true fires that MODIS failed to detect as a result of larger pixel sizes at extreme MODIS scan angles. Results from this work are expected to facilitate (i) future improvements to the SEVIRI FTA detection algorithm; (ii) the assimilation of the SEVIRI and MODIS active fire products; and (iii) the potential inclusion of SEVIRI into a network of geostationary sensors designed to achieve global diurnal active fire monitoring.

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Sampling by the Continuous Plankton Recorder (CPR) over the NW Atlantic from 1960 to 2000 has enabled long-term studies of the larger components of the phytoplankton community, highlighting various changes, particularly during the 1990s. Analysis of an index of phytoplankton biomass, the Phytoplankton Colour Index (PCI) has revealed an increase over the past decade, most marked during the winter (December to February) months. Examination of the structure of the community using multiple linear-regression models indicates that the winter phytoplankton community composition has changed markedly in the 1990s compared to the 1960s. One phytoplankter, the dinoflagellate Ceratium arcticum (Cleve), has undergone dramatic changes in abundance during this period, with pronounced large winter blooms and decreased autumnal levels, and its contribution to the Phytoplankton Colour index values has increased significantly. Other dominant species in the phytoplankton community, both diatoms and dinoflagellates, did not show the same variations over the examined time period. It is suggested that the response of C. arcticum is probably a result of previously reported changes in stratification in the NW Atlantic, due to dynamic hydro-climatic (freshening and cooling) events.

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Sampling by the continuous plankton recorder (CPR) survey over the North Atlantic Ocean and the North Sea has enabled long-term studies of phytoplankton biomass. Analysis of an index of phytoplankton biomass, the phytoplankton colour index (PCI), has previously shown an increase in phytoplankton biomass in the NE Atlantic. In the current study, further investigations were conducted to determine the contribution of diatom and dinoflagellate cell counts to the PCI, their fluctuations over the last 45 yr and their geographical variations in the eastern North Atlantic and the North Sea. An increased contribution of dinoflagellates to the PCI was revealed over the south NE Atlantic and the northern North Sea. In contrast, the contribution of diatoms decreased in the north NE Atlantic and the northern North Sea. No discernible trends were found in the other regions of the North Sea. The relative contributions of diatoms and dinoflagellates to the PCI led to the identification of 3 geographically distinct dynamic regimes in the diatom/dinoflagellate dynamics in the NE Atlantic and the North Sea. Finally, it is stressed that the discrepancy observed in the patterns of PCI and diatom and dinoflagellate cell counts suggests that changes in PCI do not reflect changes in the community structure and that the exclusive use of PCI is not adequate to investigate the long-term trends in the trophic link between phytoplankton and herbivorous zooplankton.

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The North Sea ecosystem has recently undergone dramatic changes, observed as altered biomass of individual species spanning a range of life forms from algae to birds, with evidence for an approximate doubling in the abundance of both phytoplankton and benthos as part of a regime shift after 1987. Remarkably, these changes, in part recorded in the Phytoplankton Colour Index of the Continuous Plankton Recorder (CPR) survey, are notable as episodic shifts occurring in 1988/89 and 1998 imposed on a gradual decadal trend. These biological events are shown to be a response to coincident changes in oceanic input and water temperature. Geostrophic transports have been calculated from a hydrographic section across the Rockall Trough, and a time series of seasurface temperature derived from satellite observations. The 2 pulses of oceanic incursion into the North Sea in circa 1988 and 1998 coincided with strong northward advection of anomalously warm water at the edge of the continental shelf.

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Climate change is unambiguous and its effects are clearly detected in all functional units of the Earth system. This study presents new analyses of sea-surface temperature changes and show that climate change is affecting ecosystems of the North Atlantic. Changes are seen from phytoplankton to zooplankton to fish and are modifying the dominance of species and the structure, the diversity and the functioning of marine ecosystems. Changes also range from phenological to biogeographical shifts and have involved in some regions of the Atlantic abrupt ecosystem shifts. These alterations reflect a response of pelagic ecosystems to a warmer temperature regime. Mechanisms are complex because they are nonlinear exhibiting tipping points and varying in space and time. Sensitivity of organisms to temperature changes is high, implicating that a small temperature modification can have sustained ecosystem effects. Implications of these changes for biogeochemical cycles are discussed. Two observed changes detected in the North Sea that could have opposite effects on carbon cycle are discussed. Increase in phytoplankton, as inferred from the phytoplankton colour index derived from the Continuous Plankton Recorder (CPR) survey, has been detected in the North Sea. This pattern has been accompanied by a reduction in the abundance of the herbivorous species Calanus finmarchicus. This might have reduced the grazing pressure and increase diatomaceous ‘fluff’, therefore carbon export in the North Sea. Therefore, it could be argued that the biological carbon pump might increase in this region with sea warming. In the meantime, however, the mean size of organisms (calanoid copepods) has dropped. Such changes have implications for the turnover time of biogenic carbon in plankton organisms and the mean residence time of particulate carbon they produce. The system characterising the warmer period is more based on recycling and less on export. The increase in the minimum turnover time indicates an increase in the ecosystem metabolism, which can be considered as a response of the pelagic ecosystems to climate warming. This phenomenon could reduce carbon export. These two opposite patterns of change are examples of the diversity of mechanisms and pathways the ecosystems may exhibit with climate change. Oversimplification of current biogeochemical models, often due to lack of data and biological understanding, could lead to wrong projection on the direction ecosystems and therefore some biogeochemical cycles might take in a warmer world.

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Assessing the skill of biogeochemical models to hindcast past variability is challenging, yet vital in order to assess their ability to predict biogeochemical change. However, the validation of decadal variability is limited by the sparsity of consistent, long-term biological datasets. The Phytoplankton Colour Index (PCI) product from the Continuous Plankton Recorder survey, which has been sampling the North Atlantic since 1948, is an example of such a dataset. Converting the PCI to chlorophyll values using SeaWiFS data allows a direct comparison with model output. Here we validate decadal variability in chlorophyll from the GFDL TOPAZ model. The model demonstrates skill at reproducing interannual variability, but cannot simulate the regime shifts evident in the PCI data. Comparison of the model output, data and climate indices highlights under-represented processes that it may be necessary to include in future biogeochemical models in order to accurately simulate decadal variability in ocean ecosystems.