Delu Pan

Atmospheric correction of satellite ocean color imagery using the ultraviolet wavelength for highly turbid waters

Instead of the conventionally atmospheric correction algorithms using the near-infrared and shortwave infrared wavelengths, an alternative practical atmospheric correction algorithm using the ultraviolet wavelength for turbid waters (named UV-AC) is proposed for satellite ocean color imagery in the paper. The principle of the algorithm is based on the fact that the water-leaving radiance at ultraviolet wavelengths can be neglected as compared with that at the visible light wavelengths or even near-infrared wavelengths in most cases of highly turbid waters due to the strong absorption by detritus and colored dissolved organic matter. The UV-AC algorithm uses the ultraviolet band to estimate the aerosol scattering radiance empirically, and it does not need any assumption of the waters optical properties. Validations by both of the simulated data and in situ data show that the algorithm is appropriate for the retrieval of the water-leaving radiance in turbid waters. The UV-AC algorithm can be used for all the current satellite ocean color sensors, and it is especially useful for those ocean color sensors lacking the shortwave infrared bands. Moreover, the algorithm can be used for any turbid waters with negligible water-leaving radiance at ultraviolet wavelength. Based on our work, we recommend the future satellite ocean color remote sensors setting the ultraviolet band to perform the atmospheric correction in turbid waters.

Image‐object detectable in multiscale analysis on high‐resolution remotely sensed imagery

Landscapes are complex systems composed of a large number of heterogeneous components as well as explicit homogeneous regions that have similar spectral character on high‐resolution remote sensing imagery. The multiscale analysis method is considered an effective way to study the remotely sensed images of complex landscape systems. However, there remain some difficulties in identifying perfect image‐objects that tally with the actual ground‐object figures from their hierarchical presentation results. Therefore, to overcome the shortcomings in applications of multiresolution segmentation, some concepts and a four‐step approach are introduced for homogeneous image‐object detection. The spectral mean distance and standard deviation of neighbouring object candidates are used to distinguish between two adjacent candidates in one segmentation. The distinguishing value is used in composing the distinctive feature curve (DFC) with object candidate evolution in a multiresolution segmentation procedure. The scale order of pixels is built up by calculating a series of conditional relative extrema of each curve based on the class separability measure. This is helpful in determining the various optimal scales for diverse ground‐objects in image segmentation and the potential meaningful image‐objects fitting the intrinsic scale of the dominant landscape objects. Finally, the feasibility is analysed on the assumption that the homogeneous regions obey a Gaussian distribution. Satisfactory results were obtained in applications to high‐resolution remote sensing imageries of anthropo‐directed areas.

Using long time series of Landsat data to monitor impervious surface dynamics: a case study in the Zhoushan Islands

Abstract Islands are an important part of the marine ecosystem. Increasing impervious surfaces in the Zhoushan Islands due to new development and increased population have an ecological impact on the runoff and water quality. Based on time-series classification and the complement of vegetation fraction in urban regions, Landsat thematic mapper and other high-resolution satellite images were applied to monitor the dynamics of impervious surface area (ISA) in the Zhoushan Islands from 1986 to 2011. Landsat-derived ISA results were validated by the high-resolution Worldview-2 and aerial photographs. The validation shows that mean relative errors of these ISA maps are < 15   % . The results reveal that the ISA in the Zhoushan Islands increased from 19.2     km 2 in 1986 to 86.5     km 2 in 2011, and the period from 2006 to 2011 had the fastest expansion rate of 5.59     km 2 per year. The major land conversions to high densities of ISA were from the tidal zone and arable lands. The expansions of ISA were unevenly distributed and most of them were located along the periphery of these islands. Time-series maps revealed that ISA expansions happened continuously over the last 25 years. Our analysis indicated that the policy and the topography were the dominant factors controlling the spatial patterns of ISA and its expansions in the Zhoushan Islands. With continuous urbanization processes, the rapid ISA expansions may not be stopped in the near feature.

Evaluation of the aerosol models for SeaWiFS and MODIS by AERONET data over open oceans

The operational atmospheric correction algorithm for Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS) uses the predefined aerosol models to retrieve aerosol optical properties, and their accuracy depends on how well the aerosol models can represent the real aerosol optical properties. In this paper, we developed a method to evaluate the aerosol models (combined with the model selection methodology) by simulating the aerosol retrieval using the Aerosol Robotic Network (AERONET) data. Our method can evaluate the ability of aerosol models themselves, independent of the sensor performance. Two types of aerosol models for SeaWiFS and MODIS operational atmospheric correction algorithms are evaluated over global open oceans, namely the GW1994 models and Ahmad2010 models. The results show that GW1994 models significantly overestimate the aerosol optical thicknesses and underestimate the Ångström exponent, which is caused by the underestimation of the scattering phase function. However, Ahmad2010 models can significantly reduce the overestimation of the aerosol optical thickness and the underestimation of the Ångström exponent as a whole, but this improvement depends on the backscattering angle. Ahmad2010 models have a significant improvement in the retrieval of the aerosol optical thickness at a backscattering angle less than 140°. For a backscattering angle larger than 140°, GW1994 models are better at retrieving the aerosol optical thickness than the Ahmad2010 models.

Automatic registration of SeaWiFS and AVHRR imagery

An automatic approach for integrating images from multitemporal and multisensor remote sensing is outlined based on coastlines derived from satellite images. One point on a coastline is taken as a candidate point of ground control points (GCPs). A correlation-relaxation (CR) technique is used to search for the corresponding point in the second image. A decision rule is used to guarantee the correctness of GCPs which are used to compute a polynomial equation for registering two images. The relationship between the accuracy of registration and the number of GCPs indicates that a large number of GCPs will lead to more accurate image registration. The correctness of GCPs can also improve the accuracy of geometric registration. The approach can be used particularly well to register images of coastal areas. Examples are given for registration of SeaWiFS and AVHRR imagery.

The satellite reversion of dissolved organic carbon （DOC） based on the analysis of the mixing behavior of DOC and colored dissolved organic matter： the East China Sea as an example

The retrieval of dissolved organic carbon (DOC) distribution by remote sensing is mainly based on the empirical relationship of DOC concentration and colored dissolved organic matter (CDOM) concentration in many literatures. To investigate the nature of this relationship, the distributions and mixing behaviors of DOC and CDOM are reviewed in the world’s major estuaries and bays. It is found that, generally, the CDOM concentration is well correlated with the salinity in most estuaries, while DOC usually shows a nonconservative behavior which leads to a weak correlation between the DOC concentration and the CDOM concentration. To establish a good satellite reversion of the DOC concentration, the East China Sea(ECS) was taken as an example, and the mixing behavior of DOC and CDOM as well as the influence of biogeochemical processes were analyzed except for the physical mixing process with the data from late autumn (November, 2010) and winter (December, 2009) cruises. In the two ECS cruises, the CDOM concentration was found to be tightly correlated with the salinity, influenced little by the photochemical or biological processes. The data from the winter cruise show that DOC followed a conservative mixing along the salinity gradient, while in the late autumn cruise it was significantly affected by the biological activities, resulting in a poor correlation between the DOC and the CDOM. Accordingly, an improvedDOC algorithm(CSDM) was proposed: when the biological influence was significant (Chl a greater than 0.8 µg/dm3), DOC was retrieved by the conservative and biologicalmodel, and if the conservativemixing was dominant (Chl a less than 0.8 µg/dm3), the direct DOC concentration and CDOM concentration relationship was used. Based on the proposed algorithm, a reasonable DOC distribution for the ECS from satellite was obtained in this study, and the proposedmethod can be applied to the other large river-dominantmarginal sea.

Detecting changes in high-resolution satellite coastal imagery using an image object detection approach

This article presents a spatial contrast-enhanced image object-based change detection approach (SICA) to identify changed areas using shape differences between bi-temporal high-resolution satellite images. Each image was segmented and intrinsic image objects were extracted from their hierarchic candidates by the proposed image object detection approach (IODA). Then, the dominant image object (DIO) presentation was labelled from the results of optimal segmentation. Comparing the form and the distribution of bi-temporal DIOs by using the raster overlay function, ground objects were recognized as being spatially changed where the corresponding image objects were detected as merged or split into geometric shapes. The result of typical spectrum-based change detection between two images was enhanced by using changed spatial information of image objects. The result showed that the change detection accuracies of the pixels with both attribute and shape changes were improved from 84% to 94% for the strong attribute pixel, and from 36% to 81% for the weak attribute pixel in study area. The proposed approach worked well on high-resolution satellite coastal images.

Diurnal Variability of Turbidity Fronts Observed by Geostationary Satellite Ocean Color Remote Sensing

Monitoring front dynamics is essential for studying the ocean’s physical and biogeochemical processes. However, the diurnal displacement of fronts remains unclear because of limited in situ observations. Using the hourly satellite imageries from the Geostationary Ocean Color Imager (GOCI) with a spatial resolution of 500 m, we investigated the diurnal displacement of turbidity fronts in both the northern Jiangsu shoal water (NJSW) and the southwestern Korean coastal water (SKCW) in the Yellow Sea (YS). The hourly turbidity fronts were retrieved from the GOCI-derived total suspended matter using the entropy-based algorithm. The results showed that the entropy-based algorithm could provide fine structure and clearly temporal evolution of turbidity fronts. Moreover, the diurnal displacement of turbidity fronts in NJSW can be up to 10.3 km in response to the onshore-offshore movements of tidal currents, much larger than it is in SKCW (around 4.7 km). The discrepancy between NJSW and SKCW are mainly caused by tidal current direction relative to the coastlines. Our results revealed the significant diurnal displacement of turbidity fronts, and highlighted the feasibility of using geostationary ocean color remote sensing technique to monitor the short-term frontal variability, which may contribute to understanding of the sediment dynamics and the coupling physical-biogeochemical processes.

Remote Sensing Observation of Particulate Organic Carbon in the Pearl River Estuary

River estuaries are connectors of terrestrial and marine ecosystems. Riverine particulate organic carbon (POC) is discharged into oceans after a series of biogeochemical reactions in estuaries. Satellite monitoring of POC will improve our understanding of the carbon dynamics of these water bodies. Based on in situ data from four seasonal survey cruises, we developed an algorithm for estimating POC concentrations in the Pearl River Estuary (PRE). Reflectance ratios, Rrs(678)/Rrs(488) and Rrs(748)/Rrs(412), were set as inputs to calculate POC concentration in the PRE. The algorithm was then applied to MODIS/AQUA data to inverse POC concentrations in the PRE from 2002 to 2014. Additionally, sources, impact factors, and seasonal distributions of POC were also investigated. Phytoplankton contributed more to POC in off-shore waters than that in in-shore waters in autumn and spring, but showed the opposite pattern in winter. Under the influence of freshwater from the Pearl River, underwater topography, tides, winds, etc., the seasonal POC concentrations along a specific section, vertical to water depth gradient, decreased in different seasons. These decreases could be described by exponential functions (y = aebx, b < 0). The distribution of POC concentrations in the PRE resulted from complex physical and biogeochemical processes, which can change spatially and seasonally.

Evaluation of Coastline Changes under Human Intervention Using Multi-Temporal High-Resolution Images: A Case Study of the Zhoushan Islands, China

Continued sea-level rise and coastal development have led to considerable concerns on coastline changes along inhabited islands. Analysis of long-term coastline changes of islands is however limited due to unavailable data and the cost of field work. In this study, high-resolution images taken from 1970–2011 at an interval of about 10 years and topographic maps were collected to determine coastline changes and their drivers in the Zhoushan Islands, China. Results show that nearly all inhabited islands appeared to have noteworthy seaward expansion during the past four decades. Coastline change rates varied among islands, and the annual change rate of Zhoushan Island (the main island) reached 12.83 ± 0.17 m/year during the same period. Since 2003, the study area has been dominated by artificial coast. The proportion of harbor/port and urban/industrial coast has significantly increased, while rocky coasts and shelter-farm coasts have shrunk greatly. Preliminary analysis of drivers for these coastline changes across the Zhoushan Islands highlights the roles of human policies during different periods as well as location, which were the dominant factors controlling the great spatial and temporal complexity of coastline changes of the major islands. Sediment supply from the Yangtze River decreased after the completion of the Three Gorges Dam in 2003; however, the Zhoushan coast rapidly accreted seaward during the last decade and the artificial siltation, coastal engineering, and harbor dredging materials could be responsible for the observed coastline changes. Pressured by rapid development of the port industry, the Zhoushan coast may face unprecedented challenges in coastal use in the near future. This research provides the basic background information for future studies on coastal protection and management.