Remote Sensing

Substantial efforts have been devoted more recently to presenting various methods for object detection in optical remote sensing images. However, the current survey of datasets and deep learning based methods for object detection in optical remote sensing images is not adequate. Moreover, most of the existing datasets have some shortcomings, for example, the numbers of images and object categories are small scale, and the image diversity and variations are insufficient. These limitations greatly affect the development of deep learning based object detection methods.

Geohazards resulting from mining activities must be effectively monitored to mitigate their impact on the environment and human activities. Geohazards such as landslides and collapses caused by open-pit mining are relatively easier to monitor because they are primarily surface-based. In contrast, underground mining disrupts the stress balance in the overlying rock layers, leading to complex settlement patterns, including subsidence basins, cracks, and groundwater depletion.

The HROS dataset consists of OPT and SAR images collected from multiple sources. The OPT images are collected from the large-scale public remote sensing datasets. Image sources include different platforms, including Google Maps, JL-1 satellite, Gaofen-2 satellite, aerial imagery, etc. The SAR images are captured by the AS-01 satellite, developed by Skysight Technology Co., LTD. The AS-01 satellite is equipped with a two-dimensional scanning plane solid-state active phased array synthetic aperture radar (SAR) payload, which enables high-resolution imaging capabilities.

Greenland Ice Sheet is one of the key factors influencing global climate change. Its slight variations can lead to significant changes in sea level, making quantitative research on its mass balance of great scientific importance.