Field Intercomparison of Radiometer Measurements for Ocean Colour Validation

A field intercomparison was conducted at the Acqua Alta Oceanographic Tower (AAOT) in the northern Adriatic Sea, from 9 to 19 July 2018 to assess differences in the accuracy of in- and above-water radiometer measurements used for the validation of ocean colour products. Ten measurement systems were compared. Prior to the intercomparison, the absolute radiometric calibration of all sensors was carried out using the same standards and methods at the same reference laboratory. Measurements were performed under clear sky conditions, relatively low sun zenith angles, moderately low sea state and on the same deployment platform and frame (except in-water systems). The weighted average of five above-water measurements was used as baseline reference for comparisons. For downwelling irradiance (), there was generally good agreement between sensors with differences of <6% for most of the sensors over the spectral range 400 nm–665 nm. One sensor exhibited a systematic bias, of up to 11%, due to poor cosine response. For sky radiance () the spectrally averaged difference between optical systems was <2.5% with a root mean square error (RMS) <0.01 mWm−2 nm−1 sr−1. For total above-water upwelling radiance (), the difference was <3.5% with an RMS <0.009 mWm−2 nm−1 sr−1. For remote-sensing reflectance (), the differences between above-water TriOS RAMSES were <3.5% and <2.5% at 443 and 560 nm, respectively, and were <7.5% for some systems at 665 nm. Seabird HyperSAS sensors were on average within 3.5% at 443 nm, 1% at 560 nm, and 3% at 665 nm. The differences between the weighted mean of the above-water and in-water systems was <15.8% across visible bands. A sensitivity analysis showed that accounted for the largest fraction of the variance in , which suggests that minimizing the errors arising from this measurement is the most important variable in reducing the inter-group differences in . The differences may also be due, in part, to using five of the above-water systems as a reference. To avoid this, in situ normalized water-leaving radiance () was therefore compared to AERONET-OC SeaPRiSM as an alternative reference measurement. For the TriOS-RAMSES and Seabird-Hyperspectral Surface Acquisition System (HyperSAS) sensors the differences were similar across the visible spectra with 4.7% and 4.9%, respectively. The difference between SeaPRiSM and two in-water systems at blue, green and red bands was 11.8%. This was partly due to temporal and spatial differences in sampling between the in-water and above-water systems and possibly due to uncertainties in instrument self-shading for one of the in-water measurements

Effect of simplicity and attractiveness on route selection for different journey types

This study investigated the effects of six attributes, associated with simplicity or attractiveness, on route preference for three pedestrian journey types (everyday, leisure and tourist). Using stated choice preference experiments with computer generated scenes, participants were asked to choose one of a pair of routes showing either two levels of the same attribute (experiment 1) or different attributes (experiment 2). Contrary to predictions, vegetation was the most influential for both everyday and leisure journeys, and land use ranked much lower than expected in both cases. Turns ranked higher than decision points for everyday journeys as predicted, but the positions of both were lowered by initially unranked attributes. As anticipated, points of interest were most important for tourist trips, with the initially unranked attributes having less influence. This is the first time so many attributes have been compared directly, providing new information about the importance of the attributes for different journeys. © 2014 Springer International Publishing

Susceptibility of optimal train schedules to stochastic disturbances of process times

This work focuses on the stochastic evaluation of train schedules computed by a microscopic scheduler of railway operations based on deterministic information. The research question is to assess the degree of sensitivity of various rescheduling algorithms to variations in process times (running and dwell times). In fact, the objective of railway traffic management is to reduce delay propagation and to increase disturbance robustness of train schedules at a network scale. We present a quantitative study of traffic disturbances and their effects on the schedules computed by simple and advanced rescheduling algorithms. Computational results are based on a complex and densely occupied Dutch railway area; train delays are computed based on accepted statistical distributions, and dwell and running times of trains are subject to additional stochastic variations. From the results obtained on a real case study, an advanced branch and bound algorithm, on average, outperforms a First In First Out scheduling rule both in deterministic and stochastic traffic scenarios. However, the characteristic of the stochastic processes and the way a stochastic instance is handled turn out to have a serious impact on the scheduler performance