An Unsupervised Port Detection Method in Polarimetric SAR Images Based on Three-Component Decomposition and Multi-Scale Thresholding Segmentation

It is difficult to detect ports in polarimetric SAR images due to the complicated components, morphology, and coastal environment. This paper proposes an unsupervised port detection method by extracting the water of the port based on three-component decomposition and multi-scale thresholding segmentation. Firstly, the polarimetric characteristics of the port water are analyzed using modified three-component decomposition. Secondly, the volume scattering power and the power ratio of the double-bounce scattering power to the volume scattering power (PRDV) are used to extract the port water. Water and land are first separated by a global thresholding segmentation of the volume scattering power, in which the sampling region used for the threshold calculation is automatically selected by a proposed homogeneity measure. The interference water regions in the ports are then separated from the water by segmenting the PRDV using the multi-scale thresholding segmentation method. The regions of interest (ROIs) of the ports are then extracted by determining the connected interference water regions with a large area. Finally, ports are recognized by examining the area ratio of strong scattering pixels to the land in the extracted ROIs. Seven single quad-polarization SAR images acquired by RADARSAT-2 covering the coasts of Dalian, Zhanjiang, Fujian, Tianjin, Lingshui, and Boao in China and Berkeley in America are used to test the proposed method. The experimental results show that all ports are correctly and quickly detected. The false alarm rates are zero, the intersection of union section (IoU) indexes between the detected port and the ground truth can reach 75%, and the average processing time can be less than 100 s.

On the Understanding of the Hydrodynamics and the Causes of Saltwater Intrusion on Lagoon Tidal Springs

Springs are common features on the Yucatán coast. They can discharge either under the sea (submarine) or inland in coastal lagoons and wetlands. Previous observations of a coastal lagoon located on the northern Yucatán Peninsula (La Carbonera) reported sea water intrusion on a spring that discharge on a coastal lagoon (lagoon tidal spring). The saltwater intrusion occurs when the tide is at its lower level, which is the opposite to what has been reported for submarine springs in the Yucatán Peninsula. In this study, the hydrodynamics of the spring is analyzed and the driving forces controlling the seawater intrusion are identified and discussed. Time series of water levels, salinity, and velocity measurements in the lagoon, the aquifer, and the spring are analyzed by means of tide component decomposition and cross-correlations analysis of the tide signals. Results show that the main driving forces causing the intrusion are the density differences and pressure head gradients, and the mechanisms influencing the driving forces driving those differences are the tides, the friction in the lagoon, and the confinement of the aquifer; other mechanisms are discussed to present a complete idea of the complexity of the interactions between the coastal aquifer, the coastal lagoons, and the sea.

Independent components of spatial-temporal structure of chlorophyll a patterns in the upper layer of the north-western shelf of the Black Sea

In the present study, the results of independent component decomposition of satellite-derived chlorophyll a (Chla) patterns for the north-western part of the Black Sea are presented. The study has been carried out on the basis of the DINEOF-reconstructed dataset of 8-day average log-transformed Chla (alChla) patterns for 1997-2016. The alChla patterns were decomposed into six independent components of its spatio-temporal variability in the north-western shelf of the Black Sea. The independent components reflect the spatial distribution of alChla anomalies which are likely to be formed under the influence of sea circulation factors driven by wind. The paper presents the results of the analysis of the intra-annual variability of independent components. The interpretation of the patterns of intra-annual independent components variability is given, taking into account the seasonal variability of the wind factor, the flow of the Danube, the Dnieper and Southern Bug rivers and the fact of modulation of independent components dynamics by seasonal phytoplankton succession.

Revealing the component structure of the world air transportation network

Air transportation plays an essential role in the global economy. Therefore, there is a great deal of work to understand better the complex network formed by the links between the origins and destinations of flights. Some investigations show that the world air transportation network exhibits a community and a core-periphery structure. Although precious, these representations do not distinguish the inter-regional (global) web of connections from the regional (local) one. Therefore, we propose a new mesoscopic model called the component structure that decomposes the network into local and global components. Local components are the dense areas of the network, and global components are the nodes and links bridging the local components. As a case study, we consider the unweighted and undirected world air transportation network. Experiments show that it contains seven large local components and multiple small ones spatially well-defined. Moreover, it has a main global component covering the world. We perform an extensive comparative analysis of the structure of the components. Results demonstrate the non-homogeneous nature of the world air transportation network. The local components structure highlights regional differences, and the global component organization captures the efficiency of inter-regional travel. Centrality analysis of the components allows distinguishing airports centered on regional destinations from those focused on inter-regional exchanges. Core analysis is more accurate in the components than in the whole network where Europe dominates, blurring the rest of the world. Besides the world air transportation network, this paper demonstrates the potential of the component decomposition for modeling and analyzing the mesoscale structure of networks.

Framework for Reconstruction of Pseudo Quad Polarimetric Imagery from General Compact Polarimetry

Pseudo quad polarimetric (quad-pol) image reconstruction from the hybrid dual-pol (or compact polarimetric (CP)) synthetic aperture radar (SAR) imagery is a category of important techniques for radar polarimetric applications. There are three key aspects concerned in the literature for the reconstruction methods, i.e., the scattering symmetric assumption, the reconstruction model, and the solving approach of the unknowns. Since CP measurements depend on the CP mode configurations, different reconstruction procedures were designed when the transmit wave varies, which means the reconstruction procedures were not unified. In this study, we propose a unified reconstruction framework for the general CP mode, which is applicable to the mode with an arbitrary transmitted ellipse wave. The unified reconstruction procedure is based on the formalized CP descriptors. The general CP symmetric scattering model-based three-component decomposition method is also employed to fit the reconstruction model parameter. Finally, a least squares (LS) estimation method, which was proposed for the linear π/4 CP data, is extended for the arbitrary CP mode to estimate the solution of the system of non-linear equations. Validation is carried out based on polarimetric data sets from both RADARSAT-2 (C-band) and ALOS-2/PALSAR (L-band), to compare the performances of reconstruction models, methods, and CP modes.