Influence of the macrotidal environment on the source to sink pathways of suspended flux in the Gulf of Kachchh,India: evidence from the Ocean Colour Monitor (IRS‐P4)

A series of tide‐synchronous satellite images, obtained from the Ocean Colour Monitor (OCM) onboard the Indian Remote Sensing Satellite (IRS‐P4), in situ measurements and hydrodynamic model simulations were used to describe dispersal pathways and sources of total suspended matter (TSM) in the Gulf of Kachchh, a macrotidal system with insignificant freshwater inputs. Strong alongshore currents are prevalent at the mouth that move in (out) clockwise during flood (ebb) and undergo cyclic, dynamic changes with the tidal phases. The Gulf, unlike other regions of the Indian coastline, has dynamic turbidity that is zonal (very high in the outer Gulf and in the creeks of the Gulf), particularly during flooding, and reduced in the central region throughout the entire tidal cycle. From this dynamic turbidity with regard to the prevalent currents, it is deduced that inland amplifying flood currents draw in TSM‐rich offshore waters into the Gulf, and are the major source of turbidity in the outer regions of the Gulf. In the inner Gulf, because of these high‐magnitude currents, scouring of the creek bed leads to resuspension to create higher turbidity. Most of the scoured flux sinks off the mouths of these creeks because of the fanning out of ebbing flows from the narrow creeks into the wider Gulf. The areas under specific influence of different sources of turbidity are delineated schematically.     

Remote sensing for the identification of coastal plumes: case studies of Delaware Bay

Two Delaware coastal plume events are studied using various remote sensing data. Satellite images obtained from the Advanced Very High Resolution Radiometer (AVHRR), the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Sea‐viewing Wide Field‐of‐view Sensor (SeaWiFS) are processed and enhanced to identify coastal plumes from Delaware Bay. Both visible band and infrared sensors give similar results in terms of the plume boundary. The gradient images of both types of sensors show the twin‐front structure near Cape Henlopen, which is also captured in a Synthetic Aperture Radar (SAR) image. Six consecutive SST images are used to track plume variability due to tidal forcing and the features of the plume front are found to be different between ebb and flood tides. Five consecutive SST images taken during a pronounced upwelling‐favourable wind event show the plume widened and separated offshore, while cooler water upwelled onshore of the separated plume.     

SAR imaging of a topography-induced current front in a tidal channel

A quasi-linear dark-bright feature was observed on a TerraSAR-X synthetic aperture radar (SAR) image acquired in the area of Pearl River Estuary (PRE), China, on 25 October 2010. Examining the detailed local bathymetry chart, we find that the feature is collocated with major axis of Lingding Channel in the waterway of PRE. In the study, we first run a 3-D hydrodynamic model to simulate the tidal currents within PRE, and then used the simulated current and local wind data as input to run a radar simulation model to calculate the variation of normalized radar cross section induced by these parameters. Ocean model simulation shows that surface currents were parallel to the major axis of the channel at the satellite overpass time. Radar model simulation results show good agreement between the simulated and actual SAR images. The quasi-linear dark-bright feature on the SAR image was found to be due to the surface current convergence and divergence caused by the bathymetry-induced tidal current variation.     

Coastal morphology: a case study of the Gulf of Khambhat (Cambay)

Geomorphic processes greatly influence the industrial, commercial and recreational activities in the Gulf of Khambhat (Cambay). LANDSAT data with their synoptic and repetitive coverage have been used in studying the distribution of suspended sediments, currents and fronts and for mapping shoreline configuration and wetlands. Visual interpretation of LANDSAT Multispectral Scanner (MSS) band 6 and 7 images and diazo colour overlays was carried out for the above purpose. Colour density slicing was performed on all four MSS images for the qualitative estimation of suspended sediments. The observation of suspended sediments suggests that during the monsoon many sediments brought in by various rivers remain in suspension and start settling down with the onset of the winter season. Tides also play an important role in the movement of the suspended sediments and fronts. The concentration of the suspended sediments is high on the mainland side during the flood tide and in the centre of the Gulf during the ebb tide. The fronts are located along the mainland side during the flood tide and on the Saurashlra side during the ebb tide. The currents in the Gulf are observed to be mainly influenced by the tides. Seasonal variation in the currents are mainly due to riverine discharge. The mapping of shoreline changes and geomorphic mapping has shown significant changes taking place in the Mahi and the Narmada estuaries. These changes have threatened the cooling pond of the Dhuvaran thermal power station in the Mahi estuary.     

长江感潮河段溢油风险评价体系构建及应用

长江感潮河段水动力条件复杂,对该水域溢油事故缺少相应的风险评价指标体系。为科学评价长江感潮河段溢油风险,从溢油事故对上游水体、敏感点、敏感区影响 3 个要素出发,构建风险评价指标体系,包括危害区特征、危害期特征共 23 个指标。应用该指标体系,基于 EFDC 二维水动力-油粒子模型,以长江南京段水域某码头溢油事故为研究对象,开展溢油风险评价,模拟计算涨急、落急、涨憩、落憩 4 种典型事故发生工况下的风险评价指标值。结果表明;事故发生在落急或涨憩时刻时不会对上游水域产生影响,发生在落憩时刻时对事故点上游水域影响距离最远,发生在落急时刻时将最快影响到下游的敏感点和敏感区,持续时间与水动力特性密切相关。建立的评价指标体系可以较为全面地刻画溢油风险影响特征,为长江感潮河段溢油风险评价提供量化指标和评价工具。     

Submarine groundwater discharge in tidal flats revealed by space-borne synthetic aperture radar

Most space-borne sensors cannot detect subsurface features. Groundwater is a typical subsurface feature, and its discharge to coastal ocean waters plays an important role in transporting terrestrial chemical constituents and providing habitats for various species of fauna and flora. This is the first paper to report observational evidence for submarine groundwater discharge (SGD) in tidal flats using space-borne synthetic aperture radar (SAR). Tidal flats are composed of high-moisture-saturated sediments and water puddles. These shallow water puddles were imaged effectively by using SAR systems. The presence of water puddles is usually indicated by low radar backscatter in SAR images due to specular reflections on the water surface. This effect was proved by comparing radar backscattering coefficients obtained from two space-borne SAR systems, TerraSAR-X and RADARSAT-2, with those obtained from two theoretical scattering models, IEM and Oh model. We observed relatively large, widely distributed water puddles in belt shape along the upper parts of the tidal flat, which were confirmed to be related to the discharge of groundwater. The results of this research suggest that SAR can be a powerful tool for observing and determining the areal distributions of possible groundwater discharge in large tidal flats, which is normally difficult to detect with traditional measurement tools or survey techniques for groundwater discharge. We firmly believe that this technique can reduce significantly the efforts of field work to confirm SGD in tidal flats.     

Applicability of the SIFT operator to geometric SAR image registration

The SIFT operator's success for computer vision applications makes it an attractive alternative to the intricate feature based SAR image registration problem. The SIFT operator processing chain is capable of detecting and matching scale and affine invariant features. For SAR images, the operator is expected to detect stable features at lower scales where speckle influence diminishes. To adapt the operator performance to SAR images we analyse the impact of image filtering and of skipping features detected at the highest scales. We present our analysis based on multisensor, multitemporal and different viewpoint SAR images. The operator shows potential to become a robust alternative for point feature based registration of SAR images as subpixel registration consistency was achieved for most of the tested datasets. Our findings indicate that operator performance in terms of repeatability and matching capability is affected by an increase in acquisition differences within the imagery. We also show that the proposed adaptations result in a significant speed-up compared to the original SIFT operator.     

Mesoscale surface current fields in the Baltic Sea derived from multi-sensor satellite data

We demonstrate the use of multi-sensor satellite images for the computation of mesoscale surface currents in the Northern and Southern Baltic Proper by enhancing and combining image-processing techniques. The sequential satellite images were acquired by the Thematic Mapper (TM), the ERS-2 Synthetic Aperture Radar (SAR), the Wide-Field Scanner (WiFS) and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) during extensive cyanobacterial blooms in July 1997 and in July/August 1999. We also used a pair of Advanced SAR (ASAR) images from May 2005 showing imprints of singular oil spills in the Southern Baltic Proper. Different marine surface films and accumulated algae at the water surface were taken as tracers for the local motion of the sea surface. Data from sensors working at different electromagnetic bands (e.g. TM and SAR) were used to apply high-speed feature-matching (cross-correlation) techniques for motion detection. The sufficiently short time lags between the multiple image acquisitions (from less than 1 h to approximately 1 day) and the high spatial coverage allowed for the calculation of optical flow (i.e. surface motion) fields, which include small-scale turbulent structures that are not resolved by operational numerical models. Our computed surface currents range from 4 to 35 cm s^?1 and are generally larger than those provided by the numerical models for the same dates and areas. We attribute this difference to local wind forcing, causing higher drift velocities at the very sea surface, which is seen from space, but which is not resolved by the numerical models.     

Application of a new algorithm using Doppler information to retrieve complex wind fields over the Black Sea from ENVISAT SAR images

Several algorithms have been proposed to retrieve near-surface wind fields from C-band synthetic aperture radar (SAR) images acquired over the ocean. They mainly differ in the way they retrieve the wind direction. Conventionally, the wind direction is taken from atmospheric models or is extracted from the linear features sometimes visible in SAR images. Recently, a new wind retrieval algorithm has been proposed, which also includes the Doppler shift induced by motions of the sea surface. In this article, we apply three wind retrieval algorithms, including the one using Doppler information, to three complex wind events encountered over the Black Sea and compare the SAR-derived wind fields with model wind fields calculated using the high-resolution weather research and forecasting (WRF) model. It is shown that the new algorithm is very efficient in resolving the 180° ambiguity in the wind direction, which is often a problem in the streak-based wind retrieval algorithms. However, the Doppler-based algorithm only yields good results for wind directions that have a significant component in the look direction of the SAR antenna. Furthermore, it is dependent on good separation of the contributions to the Doppler shift induced by surface currents and wind-related effects (wind drift and wind-sea components of the ocean wave spectrum). We conclude that an optimum wind retrieval algorithm should consist of a combination of the algorithms based on linear features and Doppler information.     

Surface currents from hourly variations of suspended particulate matter from Geostationary Ocean Color Imager data

Surface currents in Korean coastal regions were obtained using the maximum cross-correlation method applied to hourly suspended particulate matter images from the Geostationary Ocean Color Imager. Preliminary current vectors were filtered out by applying a series of quality-control procedures. The current vectors resulting from the tests were compared with the currents from a numerical model with tide and wind field. It was found that the estimated currents were more similarly to the currents caused by both tide and wind. A high degree of discrepancy was detected in regions of strong tidal currents, where the fundamental assumption of horizontal movement was limited due to the dominant vertical tidal mixing in the shallow region. The hourly rotations of the current vectors within a day were clarified by a comparison of the time-varying orientation angles of tidal ellipses. This study emphasized how to understand the short-term surface flows from hourly high-resolution geostationary satellite images.     

A note on the observed and predicted flow patterns around islands— Flat Holm,the Bristol Channel

Abstract

Multispectral scanner (MSS) data from the Natural Environment Research Councils (NERC) aircraft flown over the island of Flat Holm in the Bristol Channel, U.K. have been used in association with a System Probatoire d'Observation de la Terre, high-resolution visible scanner (SPOT HRV) image of the same area to identify the major surface water flow patterns around the island. Theoretical scaling parameters for shallow water flows are used to predict wake form and compared with the MSS and SPOT HRV images. Initial results indicate that the mathematical approach gives a useful approximation to the observed flow patterns though additional information on tidal currents throughout the tidal cycle and detailed bathymetry in the area are required to further the predictive model.     

The study of ERS-1 SAR and Landsat TM synergism for land use classification

This work presents a comparative analysis of ERS-1 Synthetic Aperture Radar (SAR) and Landsat-5 Thematic Mapper (TM) images used for land use classification. The study area of 361 km² is located in the City of Campinas, Sao Paulo State, Brazil, and contains several classes of land use, including urban, agricultural and forests. The TM and SAR images were registered and transformed using the principal components transformation. SAR images were also filtered using an average filter. The principal components derived from SAR filtered, SAR, TM and coregistered TM/SAR and TM/SAR filtered images were classified using the maximum likelihood approach. Tests of 'goodness of fit' were also made to assess the statistical properties of the images. The results, confirmed by Kappa statistics, show a significant improvement when classifying the principal components of filtered SAR and TM images for urban, pasture and forest classes.     

SAR图象中道路网络提取算法研究

提出了一种利用遗传算法从高分辨率SAR图象中提取道路网络的方法。高分辨率SAR图象中目标背景复杂,同时由于受相干斑噪声的影响,很难直接从原始图象数据中提取道路特征。首先利用模糊C均值对滤波后的图象进行聚类,将道路类象素从图象中分离出来;根据聚类结果及道路特征建立数学模型,利用遗传算法搜索全局最优道路。实验结果表明该方法可以很好地从SAR图象中提取道路网络。     

Comparative flood area analysis of C-band VH,VV, and L-band HH polarizations SAR data

The role of synthetic aperture radar (SAR)-image-based flood area mapping is proved beyond the doubts. It is also well known that different wavelength, polarization SAR reacts in varying ways over the same land-use/land-cover region. In line to this, this article mainly brings out the significance of comparing and analysing different wavelength, polarization SAR data of the same inundated region against the land-use classes of the study area. The C-band ENVISAT advanced synthetic aperture radar data of vertically transmitted horizontally received (VH), vertically transmitted vertically received (VV) polarizations data, and L-band ALOS-1 PALSAR data of horizontally transmitted horizontally received (HH) polarization data has been obtained as both these satellites captured the same flood event of Andhra Pradesh state of India. Initially, the SAR images are classified with the help of digital elevation model of the disaster region which supports in mapping the fully submerged, partially submerged and non-flooded pixels of disaster region. The fully submerged regions includes the natural waterbodies, adjacent flood plain regions which are completely submerged, as well as not accessible, whereas the partially submerged regions are spatially discontinuous and scattered regions which are inundated due to recent disaster but accessible. In this study, much emphasis has been given in comparing and analysing the fully submerged, partially submerged, and non-flooded regions of classified SAR images against each land use of the disaster region by which the response of individual land-use units of the disaster region at different wavelength, polarization has been brought out. From this comparative assessment, it has been observed that the areal extent of fully submerged regions is considerably more in L-band HH image than in the C-band polarization images. It is also been noticed that C-band VH polarization image is able to map and quantify considerable part of the land-use classes as partially submerged regions than the L-band HH polarization image. In addition to this, the proposed technique is able to rectify in classifying mangrove regions as non-flooded regions due to the land-use/land-cover-based approach.     

River extraction of SAR images via active contours driven by adaptive global fitting energies

ABSTRACT

This article proposed a novel active contour model based on adaptive global fitting energies to achieve accurate river extraction of synthetic aperture radar (SAR) images. First, inspired by the mean local fitted image in the local image fitting energy model, the mean global fitted image is defined. Second, to adapt to intensity characteristics of SAR images, we define another median global fitted image which can suppress the effect of interference regions. Then the energy functional of the proposed model is obtained by minimizing the differences between the original image and above two kinds of global fitted images. Moreover, the minimum absolute differences of pixel intensities inside object and background regions are utilized to adaptively adjust energies of object and background regions. The experimental results of river extraction of SAR images demonstrate that the proposed model can extract rivers of SAR images accurately and efficiently and has advantages in extraction performance and extraction efficiency.     

Mapping of flood dynamics and spatial distribution of vegetation in the Amazon floodplain using multitemporal SAR data

This paper presents the use of time series of SAR images to map the flood temporal dynamics and the spatial distribution of vegetation over a large Amazonian floodplain. The region under study (3500 km²) presents a diversity of landscape units with open lakes, bogs, large meadows, savannahs, alluvial forests and terra firma forest, covered by 21 images acquired by J-ERS between 1993 and 1997. Ground data include in situ observations of vegetation structure and flood extent as well as water level records. Image analysis demonstrates that temporal variations of the radar backscatter can be used to monitor efficiently the flood extent regardless of the landscape units. Also, analysis of the backscatter temporal variation greatly reduces the confusion between smooth surfaces (e.g. open water bodies, bare soils) inherent to L-band backscatter. The mapping method is based on decision rules over two decision variables: 1) the mean backscatter coefficient computed over the whole time series; 2) the total change computed using an “Absolute Change” estimator. The first variable provides classification into rough vegetation types while the second variable yields a direct estimate of the intensity of change that is related to flood dynamics. The classifier is first applied to the whole time series to map the maximum and minimum flood extent by defining 3 flood conditions: never flooded (NF); occasionally flooded (OF); permanently flooded (PF). It also furnishes the broad land cover type: open water/bare soils/low vegetation/forest. The accuracy of the flood extent mapping shows a kappa value of 0.82. Then, the classifier is run iteratively on the OF pixels to monitor flood stages during which the occasionally flooded areas get submerged. The mapping accuracy is assessed on one intermediate flood stage, showing a precision in excess of 90%. The importance of the time sampling for flood mapping is discussed along with the influence of SAR backscatter accuracy and the number of images. Then general guidelines for floodplain mapping are presented. By combining water level reports with maps of different flood stages the flooding pattern can be retrieved along with the vegetation succession processes. It is shown that the spatial distribution of vegetation communities is governed by flood stress and can be modelled as a function of the mean annual exposure to floods.     

Stochastic models for recognition of occluded targets

Recognition of occluded objects in synthetic aperture radar (SAR) images is a significant problem for automatic target recognition. Stochastic models provide some attractive features for pattern matching and recognition under partial occlusion and noise. In this paper, we present a hidden Markov modeling based approach for recognizing objects in SAR images. We identify the peculiar characteristics of SAR sensors and using these characteristics we develop feature based multiple models for a given SAR image of an object. The models exploiting the relative geometry of feature locations or the amplitude of SAR radar return are based on sequentialization of scattering centers extracted from SAR images. In order to improve performance we integrate these models synergistically using their probabilistic estimates for recognition of a particular target at a specific azimuth. Experimental results are presented using both synthetic and real SAR images.     

综合边界和纹理信息的合成孔径雷达图像目标分割

目的 针对传统Grab Cut算法需要人工交互操作,无法实现合成孔径雷达（SAR）图像的自动分割,且方式单一（仅利用边界或纹理信息中的一种）的问题,提出一种综合利用边界和纹理信息的改进Grab Cut算法,实现对SAR图像目标的自动分割。方法 首先将其他格式的彩色或灰度SAR图像转化为24 bit的位图,采用图形理论对整幅SAR图像建模,根据最大流算法找到描述图的能量函数最小的割集,从而分割出目标区域;然后采用中值滤波抑制相干噪声;最后通过邻域生长算法滤除图像斑点和小目标的干扰,从而达到目标边界的连接,实现自动对SAR图像中的目标进行分割。结果 在64位Window 7环境下采用MATLAB R2014处理平台,对楼房、车库、大树、汽车群等4幅分辨率不同的SAR图像进行目标分割实验,特征目标被自动分割出来,耗时分别为1.69 s、1.58 s、1.84 s和3.09 s,相比Mean-shift和Otsu算法,平均计算效率分别提升150%和3%,并且图像中的背景杂波、目标阴影和干扰小目标均被有效去除。结论 综合利用边界和纹理信息能够有效抑制相干噪声,去除图像斑点和小目标的干扰,从而达到目标边界的连接,实现对SAR图像目标的自动分割。实验结果表明,本文算法可以满足工程化应用要求,自适应性强,分割精度高,且具有较好的鲁棒性。     

Using the Diffusion Hydrodynamic model (DHM) to evaluate flood plain environmental impacts

The two-dimensional Diffusion Hydrodynamic Model or DHM is applied to the evaluation of flood plain depths developed from an overflow of a leveed river. The environmental concerns as to flood protection and high flow velocities can be better studied with the help of the two-dimensional DHM flow model than by use of the standard one-dimensional modeling techniques. In the considered test case, the predicted flood depth differences between the DHM and the standard one-dimensional approach are found to be significant. The approach to using the new DHM to an actual field problem is presented, along with comparative results developed by a sensitivity analysis. Although the DHM develops considerable information, it is straightforward to use and does not require expertise beyond that required for use of the more standard one-dimensional models.     

A two-stage method for oil slick segmentation

In this paper we propose a two-stage algorithm for oil slick segmentation in synthetic aperture radar (SAR) images. In the first stage, we propose a new variational model to reduce speckles in non-textured SAR images. Applications to simulated and real SAR images show that the method is well balanced in the quality of the conventional criteria. Then, in the second stage, we use the fast Chan–Vese (CV) model and the level set method to segment the oil slick in the de-speckled SAR image. The additive operator splitting (AOS) scheme is used in the numerical implementation to improve computational efficiency. Experimental results show that our two-stage algorithm is effective for oil slick segmentation in SAR images.