A5055823288- Advanced Image Fusion Techniques
- Remote-Sensing Image Classification
- Landslides and related hazards
- Remote Sensing in Agriculture
- Image and Signal Denoising Methods
- Synthetic Aperture Radar (SAR) Applications and Techniques
- Mineral Processing and Grinding
- Soil Geostatistics and Mapping
- Soil and Unsaturated Flow
- Remote Sensing and LiDAR Applications
- Smart Agriculture and AI
- Rock Mechanics and Modeling
- Remote Sensing and Land Use
Michigan Technological University
2022-2023
Rapid slope instabilities (i.e., rockfalls) involving highway networks in mountainous areas pose a threat to facilities, settlements and life, thus representing challenge for asset management plans. To identify different morphological expressions of degradation processes that lead rock mass destabilization, we combined satellite uncrewed aircraft system (UAS)-based products over two study sites along the State Highway 133 sector near Paonia Reservoir, Colorado (USA). Along with PS-InSAR...
Hyperspectral image (HSI) classification is the most vibrant area of research in hyperspectral community due to rich spectral information contained HSI can greatly aid identifying objects interest. However, inherent non-linearity between materials and corresponding profiles brings two major challenges classification: interclass similarity intraclass variability. Many advanced deep learning methods have attempted address these issues from perspective a region/patch-based approach, instead...
Abstract Purpose Soil texture identification is vital for various agricultural and engineering applications but generally involves rigorous laboratory work, especially estimating USCS (Unified Classification System) soil classes. influences water storage capacity, fertility, compaction characteristics, strength. spectroscopy offers a reliable approach that non-destructive, rapid, cost-effective to estimate several properties including texture. For applications, the classes are preferred,...
Terrain traversability is critical for developing Go/No-Go maps ground vehicles, which significantly impact a mission's success. To predict the mobility of terrain, one must understand soil characteristics. In-situ measurements performed in field are current method collecting this information, time-consuming, costly, and can be lethal military operations. This paper investigates an alternative approach using thermal, multispectral, hyperspectral remote sensing from unmanned aerial vehicle...
Hyperspectral image (HSI) classification is the most vibrant area of research in hyperspectral community due to rich spectral information contained HSI can greatly aid identifying objects interest. However, inherent non-linearity between materials and corresponding profiles brings two major challenges classification: interclass similarity intraclass variability. Many advanced deep learning methods have attempted address these issues from perspective a region/patch-based approach, instead...