Ziwei Wang

Effects of Sensor Noise in Spectral Measurements on Chlorophyll-a Retrieval in Nanhu Lake of Changchun, China

We present an algorithm from spectral measurements of upwelling water light to estimate the concentration of optically active material (OAM) such as chlorophyll-a (chl-a). The problem of chla concentration retrieval is modelled using a simulated hyperspectral sensor based on spectral measurements. Sensor noise is taken into account during the algorithm development for the best linear estimation of concentration mean and residual variance. In addition, it requires the joint distribution of radiance spectra and chl-a concentration in the algorithm development. This distribution can be obtained by simulation using water-leaving radiance models. The result shows that sensor noise greatly decreases the accuracy of chla concentration retrieval. But the accuracy can also be improved if a priori information concerning observation conditions is known and included in the algorithm. The effects of sensor noise in spectral measurements on retrieval of chl-a concentration are analysed and assessed in the study.This method is applied to the optical properties of the eutrophic water in Nanhu Lake of Changchun, China. The eutrophic water of Nanhu Lake is mainly impacted by the input from rivers and drainage systems from the area of Changchun, which discharge a high concentration of nutrients, mineral suspended solids, and dissolved organic matter (DOM or referred to yellow substance). We measured reflectance spectra (400–900 nm) of Nanhu Lake using the ASD-field spectroradiometer from April to October in 2004. The application of this algorithm shows that neglecting the sensor noise greatly underestimates the accuracy of chl-a retrieval in the study.

A PolSAR ship detector based on a multi-polarimetric-feature combination using visual attention

Ship detection can be significantly improved by using polarimetric synthetic aperture radar (PolSAR) imaging. In this article, we propose a PolSAR ship detection method based on the use of multi-featured polarization by using the visual attention model. Three polarimetric features, namely, the polarimetric contrast, the polarimetric scattering, and the polarimetric phase, are selected as the early features, and the pros and cons for each feature are discussed. The visual attention model is a framework that rapidly combines multiple features into one feature, which is improved according to the relationship of the selected features. Validation of the method is performed by analysing the multi-resolution process, the improved multi-feature process, the threshold strategy, the sensibility to the incidence angle of the sensors, and the performance of moving ship detection, which are analysed by Radarsat-2 fine quad images with automatic identification system data. Additionally, the false alarm/non-detection analysis and the computation cost analysis are also considered. In contrast to other ship detectors, the proposed detector is more effective and robust.

The Optical Properties of the Eutrophic Water: A Case Study of Nanhu Lake in Changchun, China

In this study, we present the optical properties of the eutrophic water in Nanhu Lake of Changchun, China, as a case study done in September 2003 and April 2004. The lake water in Nanhu Lake is optically dominated by scattering from suspended matter, and the lake water is dominated by absorption from phytoplankton (CHL-a), total suspended matter (TSM) and yellow substance (or so-called CDOM). The main reason is that the Nanhu Lake is highly affected by the input from rivers and drainage systems from the city of Changchun which discharges a high concentration of CDOM, nutrients, and suspended mineral solids. We measured the spectral characteristics (400–900 nm) of Nanhu Lake using the ASD-field spectrometer and analyzed the optical properties of the eutrophic water. The spectral measurements will be continued during the period of 2004–2005. Further studies are still needed to refine the method for determining the optical properties of inland waters under study.

SAR-based ship detection in sea areas containing small islands

Using synthetic aperture radar (SAR) for ship detection is a significant application for maritime monitoring and security. Ship detectors depress the disturbance from the sea surface such that the background consistently shows the sea pixels. However, in addition to water, the vast sea also contains other real objects, of which small islands are the most common. In this paper, we investigated the detection of ships in a sea area containing small islands. Based on the most widely used ship detector-constant false alarm rate (CFAR), three aspects were selected to investigate the island appearance effect, namely, image resolution, polarization, and incidence angle. As the result, an output strategy is provided when an island exists, and a ship-island enhance operator is proposed.

Ship surveillance with Radarsat-2 ScanSAR

Ship detection is a significant application of maritime monitoring and security. To fully explore the potential of wide coverage of synthetic aperture radar (SAR) image, the ScanSAR Wide image for ship detection is investigated in this paper. The Radarsat-2 ScanSAR Wide mode image is used as the image source due to its huge coverage and constant false alarm rate (CFAR) with Gamma distribution is selected as the core detector. Two problems of ScanSAR ship detection, the unbalanced phenomenon and false alarms of islands, are investigated and solved by a compensation step and Hessian matrix respectively. For more aspects, the detector also concerns the polarization channel selection and distribution fitting. Finally, a whole flow chart of ScanSAR ship detection is presented. As test cases, the experimental image is used to show the efficiency of our method.

A PolSAR ship detector using full combination of polarimetric channel

Polarimetric Synthetic Aperture Radar (PolSAR) is an advanced sensor which can achieve echoes from the ship in four different polarization channels. Given a proper weighting vector of each channel in a combination process, the contrast between ships and background can be enhanced which is a huge benefit. In this paper, a new ship detector is proposed based on an automatic way to evaluate the right weighting vector. In order to speed up the algorithm, a simulated annealing particle swarm optimization (SA-PSO) is used to search the optimal solution in the complex space. Finally, a Fine Quad Radarsat-2 image is used between PWF and the proposed method, which proves the effectiveness and availability of the proposed method.

‘Scatter coherence’ suppression for TomoSAR in urban areas

Synthetic aperture radar tomography (TomoSAR) is typically used to retrieve elevation, deformation, and other key information by separating scattering points of the same slant range in multiple baseline SAR images. ‘Scatter coherence’ (SC), which refers to the coherent relationship between scattering points in cells of the same resolution (e.g. the layover pixel), is always ignored in traditional TomoSAR. This neglect sometimes leads to unexpected inversions, e.g. the mixture of the signal subspace and noise subspace. In this paper, the electromagnetic expressions of a single bounce off the ground and the wall are first analysed to demonstrate the SC. An effective SC suppression method is proposed based on virtual baseline transformation (VBT) and spatial smoothing (SS) technologies. The SS method is used for smoothing across the baseline direction and for maintaining the separation between the signal and the noise. The VBT method meets the requirements of a uniform baseline of SS using a pre-whitening process. To verify the suppression effect, six Radarsat-2 Quad Fine images are used. The experimental results show that the side lobe of the spectrum is suppressed and that false alarms are excluded in the proposed method. The experiments of the ‘non-coherence problem’ in the cross-polarization channel and dense urban environment demonstrate the effectiveness of this method. In the 4D-TomoSAR experiment, the SC suppression also helps optimize the spectrum.

Ambiguities analysis in SAR tomography

Synthetic aperture radar tomography (TomoSAR) is typically used to retrieve elevation, deformation, and other key information by separating scatters of the same slant range in multiple baseline SAR images. In this paper, we investigate two kinds of ambiguities for TomoSAR. Rank-1 ambiguity, as the first one we concerned, is due to the baseline distribution of the SAR image dataset which makes the steering matrix out of full rank. It will result in false alarms appearing in a permanent distance. However, an example using the TomoSAR imaging parameters shows this ambiguity makes no sense in most cases. The second ambiguity refers to the coherence of scatters contained in one pixel. In simulation experiment, the coherence will enhance the side lobes of the spectrum, even make the real peaks fused.

A new algorithm for microwave radiometer remote sensing of sea surface salinity without influence of wind

The microwave radiation of the sea surface, which is denoted by the sea surface brightness temperature, is not only related with sea surface salinity (SSS) and temperature (SST), but also influenced by sea surface wind. The errors of wind detected by satellite sensor have significant influences on the accuracy of SSS retrieval. The effect of sea surface wind on sea surface brightness temperature, i.e. ΔTh,v , and the relations among ΔTh,v , wind speed, sea surface temperature, sea surface salinity and incidence angle of observation are investigated. Based on the investigations, a new algorithm depending on the design of a single radiometer with dual polarizations and multi‐incidence angles is proposed. The algorithm excludes the influence of sea surface wind on SSS retrieval, and provides a new method for remote sensing of SSS.