Estimation of terrestrial carbon balance is one of the key tasks in the understanding and
prognosis of climate change impacts and the development of tools and policies according to …

Jordan is witnessing major transformations in its environmental and topographic features,
where the desert dominates a large part of the territory, with very limited forest areas. Over …

The automatic and accurate detection of mangroves from remote sensing data is essential to
assist in conservation strategies and decision-making that minimize possible environmental …

Oil spills are a worldwide concern since they cause environmental problems and financial
losses. Automatic detection plays a crucial role in rapid decision-making to reduce damage …

Panoptic segmentation combines instance and semantic predictions, allowing the detection
of countable objects and different backgrounds simultaneously. Effectively approaching …

Eucalyptus plantations promote the economic development of forestry in southern China, but
many studies have reported their negative environmental impacts, such as high water …

This paper illustrates the results obtained by using pre-trained semantic segmentation deep
learning models for the detection of archaeological sites within the Mesopotamian …

Vehicle classification is a hot computer vision topic, with studies ranging from ground-view to
top-view imagery. Top-view images allow understanding city patterns, traffic management …

Mangrove-forest classification by using deep learning algorithms has attracted increasing
attention but remains challenging. The current studies on the transfer classification of …

Landslides are common and highly threatening geological disasters, and detecting
landslide occurrence areas using remote sensing images has important social significance …