Automated extraction of roads from remotely sensed data come forth various usages ranging
from digital twins for smart cities, intelligent transportation, urban planning, autonomous …

The data-complete and detail-correct road network information serves as important evidence
in numerous transportation-associated applications. Regular and rapid road network …

The buildings in the rural areas of Morocco exist in various shapes and sizes. They are
randomly distributed and are generally constructed of primary materials such as clay, wood …

Semantic segmentation, a fundamental research direction in synthetic aperture radar (SAR)
image interpretation, has significant application value for multiple sectors. However, noise …

Extracting roads from multi-source data, such as aerial images and vehicle trajectories, is an
important way to maintain road networks in the filed of urban computing. In this paper, we …

Road extraction is important for road network renewal, intelligent transportation systems and
smart cities. This paper proposes an effective method to improve road extraction accuracy …

Reservoir inventories are essential for investigating the impact of climate change and
anthropogenic activities on water scape changes. They provide fundamental data sources to …

High-resolution remote sensing imagery comprises spatial structure features of multispectral
bands varying in scale, color, and shape. These heterogeneous geographical features …

Fine-grained building heights are indispensable in various aspects of urban energy
consumption, environment, and climate. The highly accurate and refined building height …

Automatic road extraction has gained significant attention in urban navigation, sustainable
transport, and disaster response. Conventional convolutional neural networks operate within …