The Ocean and Land Colour Instrument (OLCI) on-board Sentinel-3 (2016–present) was designed with similar mechanical and optical characteristics to the Envisat Medium Resolution Imaging Spectrometer ...(MERIS) (2002–2012) to ensure continuity with a number of land and marine biophysical products. The Sentinel-3 OLCI Terrestrial Chlorophyll Index (OTCI) is an indicator of canopy chlorophyll content and is intended to continue the legacy of the Envisat MERIS Terrestrial Chlorophyll Index (MTCI). Despite spectral similarities, validation and verification of consistency is essential to inform the user community about the product’s accuracy, uncertainty, and fitness for purpose. This paper aims to: (i) describe the theoretical basis of the Sentinel-3 OTCI and (ii) evaluate the spatiotemporal consistency between the Sentinel-3 OTCI and the Envisat MTCI. Two approaches were used to conduct the evaluation. Firstly, agreement between the Sentinel-3 OTCI and the Envisat MTCI archive was assessed over the Committee for Earth Observation Satellites (CEOS) Land Product Validation (LPV) core validation sites, enabling the temporal consistency of the two products to be investigated. Secondly, intercomparison of monthly Level-3 Sentinel-3 OTCI and Envisat MTCI composites was carried out to evaluate the spatial distribution of differences across the globe. In both cases, the agreement was quantified with statistical metrics (R2, NRMSD, bias) using an Envisat MTCI climatology based on the MERIS archive as the reference. Our results demonstrate strong agreement between the products. Specifically, high 1:1 correspondence (R2 >0.88), low global mean percentage difference (−1.86 to 0.61), low absolute bias (<0.1), and minimal error (NRMSD ~0.1) are observed. The temporal profiles reveal consistency in the expected range of values, amplitudes, and seasonal trajectories. Biases and discrepancies may be attributed to changes in land management practices, land cover change, and extreme climatic events occurred during the time gap between the missions; however, this requires further investigation. This research confirms that Sentinel-3 OTCI dataset can be used along with the Envisat MTCI to provide a data coverage over the last 20 years.
Having already shown its potential of deriving the vector fields representing the ocean-surface advection from sequential 1.1-km-resolution local area coverage (LAC) Advanced Very High Resolution ...Radiometer (AVHRR) images, the maximum cross-correlation (MCC) technique here is applied to four 4.4-km-resolution global area coverage (GAC) AVHRR images. The resulting three vector fields are compared to the vector fields obtained from the LAC imagery corresponding to the same satellite passages. To quantify the reduction in accuracy inevitable when applying the method to the lower resolution imagery, the LAC vector fields were assumed to be error free. The deviation of the GAC vectors from the LAC vectors is expressed as percentage errors of the signal variance of meridional u and zonal v velocity components, and they are 16%/30%, respectively, for the best case and 62%/117% and 92%/111% for the other two cases. These results indicate that, in its present state, the GAC data do not allow the MCC technique to extract reliable current-vector information from it
We present the first extended validation of a new SYNERGY global aerosol product (SY_2_AOD), which is based on synergistic use of data from the Ocean and Land Color Instrument (OLCI) and the Sea and ...Land Surface Temperature Radiometer (SLSTR) sensors aboard the Copernicus Sentinel-3A (S3A) and Sentinel-3B (S3B) satellites. Validation covers period from 14 January 2020 to 30 September 2021. Several approaches, including statistical analysis, time series analysis, and comparison with similar aerosol products from the other spaceborne sensor, the Moderate Resolution Imaging Spectroradiometer (MODIS), were applied for validation and evaluation of S3A and S3B SY_2 aerosol products, including aerosol optical depth (AOD) provided at different wavelengths, AOD pixel-level uncertainties, fine-mode AOD, and Angström exponent. The regional analysis of the Angström exponent, which relates to the aerosol size distribution, shows spatial correlation with expected sources. For 40 % of the matchups with AERONET in the Northern Hemisphere (NH) and for 60 % of the matchups in the Southern Hemisphere (SH), which fit into the AE size range of 1, 1.8, an offset between SY_2 AE (syAE) and AERONET AE (aAE) is within ±0.25. General overestimation of low ( 0.5) syAE and underestimation of high ( 1.8) syAE results in high (0.94, globally) overall bias.
A bio-optical model coupled with the radiative transfer model Hydrolight was used to create 18,000 synthetic ocean colour spectra corresponding to open ocean and coastal waters. The bio-optical model ...took into account the optical properties of the three oceanic constituents, chlorophyll-a, suspended non-chlorophyllous particles and coloured dissolved organic matter (CDOM) as well as of normal seawater. The resulting spectra were input into multilayer perceptron neural network algorithms with the aim of computing the original concentrations of chlorophyll-a, non-chlorophyllous particles and CDOM initially input into the bio-optical model. The process of training the neural networks is essential for the accuracy of the inversion the neural net performs on the coupled bio-optical and radiative transfer models. The objective of this paper is to investigate the performance difference of a neural network trained with untransformed as opposed to logarithmically transformed data.
Artificial radiance sets were used as inputs to Multi-layer Perceptron and multilinear regression algorithms to study their retrieval capabilities for optically active constituents in sea water. The ...radiative transfer model Hydrolight was used to produce 18,000 artificial reflectance spectra representing various case 1 and case 2 water conditions. The remote sensing reflectances were generated at the Medium Resolution Imaging Spectrometer (MERIS) wavebands 412, 442, 490, 510, 560, 620, 665 and 682 nm from randomly generated triplet combinations of chlorophyll a, non-chlorophyllous particles and CDOM (Coloured Dissolved Organic Matter) concentrations. These reflectances were contaminated with different noise terms, before they were used to assess the performance of multilayer perceptron and multilinear regression algorithms. The potential of both algorithms for retrieving optically active constituents was demonstrated with the neural network showing more accurate results for case 2 scenarios.
Towards increased intelligence and automatic improvement in industrial vision systems Semeniuta, Oleksandr; Dransfeld, Sebastian; Martinsen, Kristian ...
11th CIRP International Conference on Intelligent Computation in Manufacturing Engineering, CIRP ICME 2017, Ischia, Naples, Italy,
2018, 2018-00-00, Letnik:
67
Journal Article, Conference Proceeding
Recenzirano
Odprti dostop
Robots and in-process inspection systems equipped with machine vision solutions are used for increased flexibility and quality in automated manufacturing. Although vision systems have found wide ...industrial use, there are still problems regarding optimization of vision system robustness and capabilities. This paper presents a comprehensive case study of vision system functions, techniques and capabilities in an automotive 1-tiers supplier. Based on the study, the paper further describes a method for systematic improvement of industrial vision systems on a continuous basis. This is proposed to be done by establishing a data store and data analysis system, based on training machine learning models in an off-line mode using the historical data, as well as on on-line stream processing.
The radiative transfer model Hydrolight was used to produce 18 000 artificial reflectance spectra representing case 1 and case 2 water conditions. Remote sensing reflectances were generated at the ...MERIS wavebands 412, 442, 490, 510, 560, 620, 665 and 682 nm from randomly generated triplet combinations of chlorophyll a, non-chlorophyllous particles and coloured dissolved organic matter concentrations. These spectra were used to train multilayer perceptron neural network algorithms to perform the inversion from input reflectances to these three optically active substances. A method is proposed that establishes the neural network output error sensitivity towards changes in the individual input reflectance channels. From the output error produced for each reflectance change, a hypothesis about the importance of each band can be made. Results suggest a strong weight associated to the 620 nm band for the estimation of all three substances.
Artificial radiance sets, generated with the use of a biooptical and radiative transfer modelHydrolight, corresponding to Case 1 and Case 2 waters, are used as inputs to Multi-layer Perceptronand ...K-NN algorithms to study the algorithm’s retrieval capabilities for optically active constituentsin the water. The radiative transfer model Hydrolight has been used to produce 18,000 artificialreflectance spectra representing various Case 1 and Case 2 water conditions. The remote sensingreflectances were generated at the MERIS wavebands 412, 442, 490, 510, 560, 620, 665 and 682nm from randomly generated triplet combinations of phytoplankton, non-chlorophyllous particlesand CDOM concentrations. These reflectances were then used to assess the performance of the KNearestNeighbour and the Multilayer Perceptron algorithms, which were compared to some moretraditional band ratio regression algorithms that had been a popular choice for CZCS and SeaWiFSimagery. The objective of the work was to establish the best kind of algorithm for this type ofapplication.
As part of the Copernicus program of the European Commission, the European Space Agency (ESA) developed and operated the Sentinel-2 constellation (S2A, S2B); and in cooperation with the EUMETSAT, ...they are operating the Sentinel-3 constellation (S3A, S3B). Both are Earth Observation optical missions, where the MultiSpectral Instruments (MSI) is carried on board Sentinel-2 mission and the Ocean and Land Colour Instrument (OLCI) and Sea Land Surface Temperature Radiometer (SLSTR) are on board Sentinel-3 mission. In the framework of the Copernicus Optical Mission Performance Cluster (OPT-MPC), we use the Database for Imaging Multispectral Instruments and Tools for Radiometric Inter-comparison (DIMITRI) to perform the radiometry intercomparison of the Level-1 products. The aims of this presentation are 1) to assess the quality of the data product; 2) to monitor the temporal evolution of the radiometry of the instruments MSI, OLCI and SLSTR for both unites A and B.The results of the intercomparison show a good stability of the sensors, although SLSTR-A & B show slight positive trend. MSI and SLST pairs A & B show good agreement better than 1% while OLCI constellation displays slight discrepancy up to 2-3%. While MSI-A, MSI-B, OLCI-B gain coefficients are within the missions' requirements, OLCI-A, SLSTR-A and SLSTR-B ones are slightly higher of the mission requirements.
The use of vision systems for industrial robot guidance and quality control becomes much harder when the manufactured products and their components are small and possess reflective surface. To assure ...an effective automated visual inspection of such components, novel solutions are required, able to perform more advanced image analysis and tackle noise and uncertainty. This paper proposes a concept of multi-camera/multi-pose inspection station for star washers inspection, and presents the first results of a functional prototype implementation of it in a robotic cell. The processes of vision-guided part picking from a flexible feeder and close-range inspection in a dedicated rig are described. Solutions for the vision-based tasks of parts identification, machine learning-based classification, circular objects image analysis and star washer teeth segmentation are presented, and further directions are outlined.
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