Environmental Sensing using Hyperspectral Imaging

HSI is an emerging technology for environmental sensing that provides high-resolution spectral data across many applications. It is key to monitoring air quality, water resources, soil properties, and vegetation health. It is essential for addressing global challenges like climate change, pollution, and sustainable resource management. The ability to collect and analyze data across many spectral bands gives unparalleled insights, allowing for precise detection and monitoring of environmental changes. Despite this, HSI faces many challenges such as high cost, limited datasets and calibration complexities preventing accurate analysis requires advanced computational resources. This review article will discuss the challenges and future advancements that are necessary for environmental sensing. HSI technical advancements have focused on increasing spatial resolution, portability, and low cost. Innovations like drone-mounted hyperspectral sensors, machine learning models for data analysis, and cloud computing have made the technology more accessible and applicable. This allows for real-time environmental monitoring, enabling prediction and providing better responses to environmental issues. Using advanced technologies it can overcome all these limitations of HSI. Distributed processing and edge computing can handle big data more efficiently, low-cost sensors and advanced algorithms are being developed to make it cost-effective and accurate. By enabling real-time environmental monitoring and informed decision-making. HSI will help for a sustainable future and its continued evolution will empower researchers and policymakers to address environmental issues more efficiently. Key Words: optics, photonics, light, lasers, templates, journals