Hyperspectral Data for Mineral Detection, Soil Salinity, and Crop Disease Monitoring

This collection of studies explores cutting-edge applications of hyperspectral remote sensing, ranging from snow property retrieval and mineral detection to soil salinity mapping and agricultural disease monitoring. The research includes innovative methods such as Siamese Networks for mineral detection, spectral requirements for wheat disease detection, and hyperspectral data analysis for tomato stress caused by late blight. With a focus on both environmental and agricultural monitoring, these papers provide valuable insights for researchers, remote sensing professionals, and students, offering advanced techniques to enhance our understanding of diverse ecosystems and crop health.