Due to limited resources and environmental pollution, monitoring the geological
environment has become essential for many countries' sustainable development. As various …

Geographic spaces is a vast and complex system involving multiple elements and nonlinear
interactions of these elements, and rich in geographical phenomena, processes and …

New satellite remote sensing and machine learning techniques offer untapped possibilities
to monitor global biodiversity with unprecedented speed and precision. These efficiencies …

Geological remote sensing interpretation can extract elements of interest from multiple types
of images, which is vital in geological survey and mapping, especially in inaccessible …

In recent years, supervised learning has been widely used in various tasks of optical remote
sensing image (RSI) understanding, including RSI classification, pixel-wise segmentation …

Given the large volume of remote sensing images collected daily, automatic object detection
and segmentation have been a consistent need in Earth observation (EO). However, objects …

High-resolution (HR) remote sensing imagery plays a critical role in remote sensing image
interpretation, and single image super-resolution (SISR) reconstruction technology is …

Remote sensing object detection based on the combination of infrared and visible images
can effectively adapt to the around-the-clock and changeable illumination conditions …

Recently, many studies have successfully exploited convolutional neural networks to
improve the performance of object detection in remote sensing images. However, detecting …

Due to the fast development of imaging sensors used in remote sensing, high-resolution
images can increasingly exhibit fine-grained information on the Earth's surface, which …