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A massive floating green macroalgae bloom (GMB) has occurred for several years consecutively in the Yellow Sea since 2007. In view of the rapid growth of green macroalgae, early detection of its patches at first appearance by satellite imagery is of importance, and the central issue is the selection of appropriate satellite data. As a first step towards this goal, based on quasi-synchronous satellite images of HJ-1A/B (China Small Satellite Constellation for Environment and Disaster Monitoring and Forecasting) charge-coupled devices (CCDs), Environmental Satellite (ENVISAT) Advanced Synthetic Aperture Radar (ASAR) and TERRA Moderate Resolution Imaging Spectroradiometer (MODIS), GMB monitoring abilities by these data were compared. The average percentage difference (APD) of the GMB areas derived by ASAR and CCD was less than 15%, which may be partly attributed to the inability of synthetic aperture radar (SAR) data to detect macroalgae suspended beneath the sea surface. The macroalgae area extracted by MODIS was over two times of that extracted by CCD, which was mainly explained by the difference in their spatial resolutions (250 vs 30 m). The effects of the configuration of sensor bands and the aerosol optical properties on the comparison result were found to be negligible, and the underlying reason is analysed by atmosphere radiative transfer modelling. With satellite images, the drifting velocity of macroalgae patches was estimated to be about 0.21 m s -1 , which was in agreement with the surface current field numerically simulated by the Hybrid Coordinate Ocean Model (HYCOM). It indicates that numerical modelling can aid in deduction of the situation of the patches when satellite data are not available, and on the other hand, satellite data can be used to estimate sea-surface currents through monitoring the movement of green algae. By a comprehensive comparison of available satellite data in operation, for the early detection of macroalgae patches and warning of a massive bloom, CCD data from the HJ-1A/B constellation was preferred, with 30 m spatial resolution, 700 km swath width and 2 day revisiting period. SAR data may be an effective supplement, which can avoid the effects of bad weather (cloud, fog and haze) on optical satellite monitoring.

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Spectral CT imaging parameters (IC, NIC, and λ ) in AP provide improved accuracy for evaluating the degrees of differentiation in colon cancer than CT number at 70 keV.

Hai Yang-2 (HY-2) satellite altimeter measurements of significant wave height () are analyzed over the period from 1 October 2011 to 6 December 2014. They are calibrated and validated against in situ buoys and other concurrently operating altimeters: Jason-2, CryoSat-2, and Satellite with Argos and ALtiKa (SARAL). In general, the HY-2 altimeter measurements agree well with buoy measurements, with a bias of −0.22 m and a root-mean-square error (RMSE) of 0.30 m. When the reduced major axis (RMA) regression procedure was applied to the entire period, the RMSE was reduced by 33% to 0.2 m. A further comparison with other satellite altimeters, however, revealed two additional features of HY-2 estimates over this period. First, a noticeable mismatch is present between HY-2 and the other satellite altimeters for high seas ( > 6 m). Second, a jump increase in HY-2 values was detected starting in April 2013, which was associated with the switch to backup status of the HY-2 sensors and the subsequent update of its data processing software. Although reported by previous studies, these two deficiencies had not been accounted for in calibrations. Therefore, the HY-2 wave height records are now subdivided into two phases (time periods pre- and post-April 2013) and a two-branched calibration is proposed for each phase. These revised calibrations, validated throughout the range of significant wave heights of 1–9 m, are expected to improve the practical applicability of HY-2 measurements significantly.

Both ASiR and ASiR-V improved the objective and subjective image quality for routine liver CT compared with FBP. ASiR-V provided further image quality improvement with higher acceptable percentage than ASiR, and ASiR-V60% had the highest image quality score. Advances in knowledge: (1) Both ASiR and ASiR-V significantly reduce image noise compared with conventional FBP reconstruction. (2) ASiR-V with 60 blending percentage provides the highest image quality score in routine liver CT.