Remote sensing
A new study by Aalto University investigators has aimed to overcome the shortcomings of conventional remote sensing approaches by integrating terrestrial laser scanning (TLS) with UAV-based photogrammetry for effective vegetation monitoring using change detection methods. The research findings demonstrate the method's capability to identify growth in urban vegetation
Remote sensing
In a recent study published in the IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, researchers from Transilvania University have assessed the patterns of green infrastructure in urban and peri-urban areas of two Romanian cities, Brasov and Oradea. The study used morphological spatial pattern analysis (MSPA)
Remote sensing
A recent study published in the Journal of Engineering has demonstrated the potential of machine learning algorithms in improving forest aboveground biomass estimations using multimodal remote sensing data. The research, conducted by scientists at the University of Connecticut, highlights the importance of variable selection methods, hyperparameter tuning of machine learning
Remote sensing
Research conducted by Akdeniz University has examined the elemental geochemistry of lignites from various coalfields in Turkey, revealing high concentrations of radioactive elements that could pose a radiological risk when burnt. The study, which analyzed 48 samples from four sites, found high concentrations of uranium, thorium, and potassium in certain
Remote sensing
A new study on the Muga watershed, upper Abay basin, Ethiopia, has revealed significant land use/land cover changes over a 35-year period. The research, conducted by Debre Markos University, explores the drivers of wetland transformations and evaluates the effectiveness of mitigation strategies. Using geospatial analysis and statistical methods, the
Remote sensing
Researchers at the Ocean University of China have developed a novel approach for retrieving vertical particulate matter (PM) concentrations using a single coherent Doppler lidar (CDL) combined with machine learning (ML) models. The study presents a promising pathway for three-dimensional PM observation with atmospheric dynamics information, offering the potential to
Remote sensing
The Canadian-based 55 North Mining Inc. has begun a detailed LiDAR (Light Detection and Ranging) survey over its wholly owned Last Hope Gold Project in Manitoba. This airborne LiDAR survey, which started on October 16, 2025, aims to provide high-resolution topographic data across the project area. The Company intends to
Remote sensing
As autonomous driving technology advances, the reliability of LiDAR sensors in adverse weather conditions, such as snow, has become a pressing concern. Traditional denoising algorithms have limited effectiveness in handling snow noise, making it challenging to distinguish dynamic noise points from environmental features. Researchers at Shanghai Dianji University have proposed
Remote sensing
Researchers at Southeast University in Nanjing, People's Republic of China, have developed a novel visual-assisted LiDAR odometry system, Livox-cam, specifically tailored for small field-of-view solid-state LiDAR. This innovative system incorporates a two-stage architecture and a spatial adaptive module to achieve robust and accurate performance in challenging scenarios, including
Remote sensing
Researchers at Xi'an Jiaotong University have published a comprehensive review on the use of perovskite materials in spectral imaging technology. According to the study, perovskite materials possess unique properties that make them ideal for overcoming the limitations of current spectral systems. These properties include tunable bandgaps, high sensitivity,
Machine learning
A new study published in the Journal of Hydrology has delved into the role of machine learning in assessing water quality in reservoirs. The research, conducted by Talal Etri and his team from Sultan Qaboos University, investigates the effectiveness of machine learning, remote sensing, and multivariate statistical analysis in monitoring
Periodical publishing
Researchers from Karpagam Institute of Technology, India, have made significant advancements in the field of artificial intelligence by developing a machine learning model to monitor seawater temperature variations and their effects on desalination efficiency. This breakthrough allows for more efficient and resilient management of desalination plants, especially in climate-sensitive coastal
