arXiv ·
Researchers in Saudi Arabia have developed a deep learning framework for automated counting and geolocation of palm trees using aerial images. The system uses a Faster R-CNN model trained on a dataset of 10,000 palm tree instances collected in the Kharj region using DJI drones. Geolocation accuracy of 2.8m was achieved using geotagged metadata and photogrammetry techniques.
KAUST ·
KAUST collaborated with NASA's Langley Research Center to launch six weather balloons from KAUST's Coastal & Marine Laboratory, reaching an altitude of 35 kilometers. The balloons were equipped with instruments to measure meteorological properties and characterize the optical properties of aerosols, including a Compact Optical Backscatter Aerosol Detector (COBALD). The research focuses on understanding the impact of dust aerosols on the Arabian Peninsula, including their effects on climate, air quality, and solar energy. Why it matters: This collaboration advances understanding of atmospheric aerosols in the region, with implications for climate modeling, solar energy efficiency, and Red Sea ecosystems.