Red Sea crisis impacts on maritime shipping networks.

The Red Sea crisis (RSC) is an ongoing military conflict affecting maritime trade. Based on automatic identification system data, this study analyzed the changes in vessel behavior in the Red Sea using the seasonal decomposition method. The number and speed of vessels decreased significantly after the RSC, and many vessels chose to sail away from the Red Sea rather than anchor at its shores.

Patch Matching and Dense CRF-Based Co-Refinement for Building Change Detection from Bi-Temporal Aerial Images.

The identification and monitoring of buildings from remotely sensed imagery are of considerable value for urbanization monitoring. Two outstanding issues in the detection of changes in buildings with composite structures and relief displacements are heterogeneous appearances and positional inconsistencies. In this paper, a novel patch-based matching approach is developed using densely connected conditional random field (CRF) optimization to detect building changes from bi-temporal aerial images.

Building Change Detection from Bi-Temporal Dense-Matching Point Clouds and Aerial Images.

In this work, a novel building change detection method from bi-temporal dense-matching point clouds and aerial images is proposed to address two major problems, namely, the robust acquisition of the changed objects above ground and the automatic classification of changed objects into buildings or non-buildings. For the acquisition of changed objects above ground, the change detection problem is converted into a binary classification, in which the changed area above ground is regarded as the foreground and the other area as the background. For the gridded points of each period, the graph cuts algorithm is adopted to classify the points into foreground and background, followed by the region-growing algorithm to form candidate changed building objects.