The integration of optical and SAR datasets through ensemble machine learning models
shows promising results in urban remote sensing applications. The integration of multi …

Change detection in remote sensing images, especially optical high and very high
resolution images, is a pivotal technique that enables efficient identification of Earth …

The classification and recognition of features play a vital role in production and daily life;
however, the current semantic segmentation of remote sensing images is hampered by …

Abstract The United Nations sustainable development agenda emphasizes the importance
of forests. China's forests cover 5% of the world's forest area, significantly influencing global …

Accurate cropland distribution data are essential for efficiently planning production layouts,
optimizing farmland use, and improving crop planting efficiency and yield. Although reliable …

The demographic reality of a large population and limited land resources in China
necessitates the implementation of the world's most stringent cultivated land protection …

As the requirements for the downstream tasks of land cover classification (LCC) continue to
increase, the category system used for LCC is constantly being refined. This causes …

Current unsupervised domain adaptation (UDA) techniques in semantic segmentation
effectively decrease the domain discrepancy between the labeled source domain and …

Rapid urbanization and population expansion pose challenges for effective land
management and urban development. In this context, Geographic Information Systems (GIS) …

Forests are the most widely distributed terrestrial vegetation type and play a significant role
in the global carbon cycle and ecological diversity. Accurate and timely forest detection …