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Learning powerful discriminative features is the key for remote sensing scene classification. Most existing approaches based on convolutional neural network (CNN) have achieved great results. However, they mainly focus on global-based visual features while ignoring object-based location features, which is important for large-scale scene classification. There are a large number of scene-related ground objects in remote sensing images, as well as Graph convolutional network (GCN) has the potential to capture the dependencies among objects. This article introduces a novel two-stream architecture that combines global-based visual features and object-based location features, so as to improve the feature representation capability. First, we extract appearance visual features from whole scene image based on CNN. Second, we detect ground objects and construct a graph to learn the spatial location features based on GCN. As a result, the network can jointly capture appearance visual information and spatial location information. To the best of authors' knowledge, we are the first to investigate the dependencies among objects in remote sensing scene classification task. Extensive experiments on two datasets show that our framework improves the discriminative ability of features and achieves competitive accuracy against other state-of-the-art approaches.

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PurposeThe authors investigated a psychological process that links characteristics of events related to the coronavirus disease (2019) COVID-19 pandemic (i.e. perceived novelty, disruptiveness and criticality) to compassion fatigue [(CF), a form of caregiver burnout] and subsequent post-traumatic stress disorder (PTSD) in nurses.Design/methodology/approachAdministering two online surveys (October and November 2020) resulted in matched data from 175 nurses responsible for patient care during the COVID-19 pandemic.FindingsPerceived disruptiveness and criticality of COVID-19 events were positively associated with nurses' CF, which also mediated those characteristics' effects on PTSD instigated by COVID-19. Contrary to the authors' hypothesis, the perceived novelty of COVID-19 events was not significantly associated with CF nor was the indirect effect of perceived novelty on PTSD mediated by CF.Originality/valueThe authors extend event system theory by investigating the psychological processes linking event features and resultant outcomes while providing practical implications on preparations for future unexpected and potentially life-altering events.