Total Articles : 5
Solar Panel Defect Detection Using Geospatially-Aware Deep Learning framework
Abstract: Large-scale photovoltaic (PV) systems demand reliable inspection techniques to maintain efficiency, as manual methods remain labor-intensive and inconsistent. This study introduces a geospatially informed deep learning framework for defect detection …
[This section belongs to Journal of Remote Sensing & GIS ]
Integrated Polarimetric-Interferometric Fusion for Heterogeneous Urban Signature Extraction
Abstract: Mapping heterogeneous urban environments using conventional Synthetic Aperture Radar (SAR) backscatter intensity frequently produces classification errors due to spectral similarity between sparse built-up features, bare soil, and dry vegetation a …
[This section belongs to Journal of Remote Sensing & GIS ]
Seasonal Dynamics of Coastal Landscapes: A Critical Review Using Remote Sensing and GIS
Abstract: Coastal landscapes are among the most dynamic environments on Earth, undergoing continuous transformation due to both natural processes and anthropogenic activities. In India, particularly along the southern coastal regions of Andhra Pradesh, Tamil …
[This section belongs to Journal of Remote Sensing & GIS ]
Integrated Remote Sensing Indices for Assessing Pre-Monsoon Water Scarcity Vulnerability in a Semi-Arid Coastal Ecosystem: A Case Study of Barda Wildlife Sanctuary, Gujarat, India
Abstract: Freshwater availability fundamentally shapes the structure and function of dryland ecosystems, where evapotranspiration exceeds precipitation for most of the year. Protected areas in semiarid regions face intensifying hydrological stress from climate …
[This section belongs to Journal of Remote Sensing & GIS ]
Geo AI-Powered Urban Footprints
Abstract: In the contemporary era, building footprints are of paramount importance for accurate and current inventories in the development of infrastructure and geospatial analysis. Traditional methods, relying on manual digitization, were largely …
[This section belongs to Journal of Remote Sensing & GIS ]