Mine Remote-Sensing Datasets

While providing resources for socio-economic development, mine development has also given rise to problems such as disorderly and illegal mining, and has caused serious damage and pollution to the surface environment, among a series of sustainable development problems. Therefore, remote sensing interpretation of mine development (including mine scenes and mine targets) is automatically realized with the help of machine learning and deep learning techniques, which can provide important support for the assessment of sustainable development of mining areas at the regional scale. However, the current lack of high-precision mine scenes and target datasets at a wide-area scale restricts the development of intelligent interpretation of remote sensing for mine development. In this paper, a mine multi-scene classification dataset, as well as a mine target detection dataset, are constructed in Hubei and Jiangxi provinces in the middle reaches of the Yangtze River. The dataset is characterized by a wide coverage area, multiple mine types, high image resolution, and multi-scale. In particular, for the mine multi-scene classification dataset, a feature fusion mine scene classification method based on a stereo attention mechanism is proposed, in which the salient features of the mine scene in three directions, horizontal, vertical, and channel, are modeled by the constructed stereo attention mechanism, and a feature activation module is used to avoid generating feature disappearance; For the mine target detection dataset, a mine target detection method based on a multi-scale dual-attention mechanism is proposed, which avoids feature bias through a multi-scale feature fusion module, while using a dual-attention mechanism to highlight salient features of the mine. The experimental results of the two models show that the mine multi-scene and target detection dataset constructed in the paper has good quality and can provide a benchmark dataset for the intelligent interpretation research of remote sensing for mine development in the Yangtze River Basin and even and global scale.