Remote Sensing (RMS)

Section Information

Remote Sensing focuses on the acquisition, processing, and interpretation of information about the Earth's surface and atmosphere using satellite, airborne, drone-based, and ground-based sensor systems. It integrates physical principles, sensor technologies, and analytical methods to monitor environmental conditions, land-use change, natural resources, and dynamic Earth processes.

Modern research in remote sensing includes multispectral and hyperspectral imaging, radar and LiDAR technologies, thermal sensing, image classification, machine learning, sensor fusion, calibration and validation techniques, environmental monitoring, and applications across agriculture, forestry, hydrology, disaster management, urban studies, and climate science.

This section publishes methodological advancements, sensor development studies, data-analysis approaches, case studies, and reviews addressing remote sensing physics, image processing, geospatial analytics, environmental applications, and multi-platform observational strategies.

Scope

Remote Sensing Principles and Sensor Technologies
- Electromagnetic radiation, spectral responses, and atmospheric effects
- Multispectral, hyperspectral, thermal, and microwave sensors
- Satellite, airborne, UAV, and ground-based platforms
- Sensor calibration, radiometric correction, and geometric accuracy
Optical and Hyperspectral Remote Sensing
- Visible, near-infrared, and shortwave infrared imaging
- Hyperspectral data analysis, material identification, and unmixing
- Vegetation indices, spectral signatures, and land-cover mapping
- Applications in agriculture, ecology, and environmental monitoring
Radar and LiDAR Remote Sensing
- SAR imaging, interferometry (InSAR), and deformation monitoring
- Radar backscatter modeling and moisture estimation
- LiDAR for topography, biomass estimation, and 3D structure mapping
- Applications in hazard assessment, forestry, and terrain modeling
Thermal and Microwave Remote Sensing
- Thermal infrared imaging, land surface temperature, and emissivity
- Passive microwave sensing for soil moisture and snow properties
- Heat flux estimation and urban thermal environment studies
- Atmospheric monitoring using thermal and microwave data
Image Processing, Analysis, and Machine Learning
- Image classification, segmentation, and feature extraction
- Object-based and pixel-based analysis approaches
- Deep learning models for pattern recognition and prediction
- Change detection, time-series analysis, and big data processing
Geospatial Integration and Sensor Fusion
- Integration of remote sensing with GIS and spatial databases
- Fusion of optical, radar, LiDAR, and ancillary data
- Multiplatform and multiscale remote sensing strategies
- Model–data integration for environmental and geophysical applications
Environmental and Earth System Applications
- Monitoring land cover, vegetation health, and biodiversity
- Hydrology, water resources, and cryosphere observations
- Geohazards including floods, landslides, earthquakes, and volcanic activity
- Atmospheric composition, climate change indicators, and aerosol studies
Urban, Agricultural, and Resource Applications
- Urban growth, infrastructure mapping, and smart city planning
- Precision agriculture and crop monitoring
- Mineral exploration, geology, and soil characterization
- Environmental impact assessment and land-use planning