Remote Sensing, Volume 17, Issue 15

Building change detection and building damage assessment are two essential tasks in post-disaster analysis. Building change detection focuses on identifying changed building areas between bi-temporal images, while building damage assessment involves...

Synthetic aperture radar (SAR) images suffer from speckle noise due to their imaging mechanism, which deteriorates image interpretability and hinders subsequent tasks like target detection and recognition. Traditional denoising methods fall short of...

Wildfires have become increasingly frequent and intense due to climate change, posing severe threats to ecosystems, infrastructure, and human lives. As a result, accurate wildfire spread prediction is critical for effective risk mitigation, resource...

Accurate and non-destructive monitoring of leaf chlorophyll content (LCC) is essential for assessing crop photosynthetic activity and nitrogen status in precision agriculture. This study introduces a phenology-aware machine learning framework that co...

Illegal mining operations induce cascading ecosystem degradation by causing extensive ground subsidence, necessitating accurate underground goaf localization for effectively induced-hazard mitigation. The conventional locating method applied the synt...

Floods stand as one of the most harmful natural disasters, which have become more dangerous because of climate change effects on urban structures and agricultural fields. This research presents a comprehensive flood mapping approach that combines mul...

The detection of seabed boulders is a critical step in mitigating geological hazards during the planning and construction of offshore wind energy infrastructure, as well as in supporting benthic ecological and palaeoglaciological studies. Traditional...

The growing use of remote-sensing technologies has placed greater demands on object-detection algorithms, which still face challenges. This study proposes a hierarchical adaptive feature aggregation network (HAF-YOLO) to improve detection precision i...

Morphology is an important characteristic of the hydraulic and gravitational processes driving gully erosion. In this study, field scouring experiments were conducted on five experimental plots using terrestrial laser scanning to study gully erosion...

The number of CNN application areas is growing, which leads to the need for training data. The research conducted in this work aimed to obtain effective detection models trained only using simplified synthetic objects (SSOs). The research was conduct...