This study addresses the challenge of oil spill detection using Synthetic Aperture Radar (SAR) satellite imagery, employing deep learning techniques to improve accuracy and efficiency. We investiga…
Crop type and crop extent are critical information that helps policymakers make informed decisions on food security. As the economic growth of Bhutan has increased at an annual rate of 7.5% over th…
Supervised deep learning algorithms have recently achieved state-of-the-art performance in the classification, segmentation and analysis of 3D LiDAR point cloud data in a wide-range of applications…
3D reconstruction is a long-standing research topic in the photogrammetric and computer vision communities; although a plethora of open-source and commercial solutions for 3D reconstruction have be…
Forest diebacks pose a major threat to global ecosystems. Identifying and mapping both living and dead trees is crucial for understanding the causes and implementing effective management strategies…
Real-time semantic segmentation of point clouds has increasing importance in applications related to 3D city modelling and mapping, automated inventory of forests, autonomous driving and mobile rob…
In recent years, there has been a growing emphasis on assessing and ensuring the quality of horticultural and agricultural produce. Traditional methods involving field measurements, investigations,…
Thermal mapping of buildings can be one approach to assess the insulation, which is important in regard to upgrade buildings to increase energy efficiency and for climate change adaptation. Persona…
Fine-grained information on the level of individual trees constitute key components for forest observation enabling forest management practices tackling the effects of climate change and the loss o…
Change detection from traditional 2D optical images has limited capability to model the changes in the height or shape of objects. Change detection using 3D point cloud from photogrammetry or LiDAR…