Priyanka Belbase is a graduate researcher in Earth and Environment at Florida International University, specializing in remote sensing, GIS, and sustainable agriculture. Her research focuses on precision agriculture by integrating spectral and hyperspectral analysis, LiDAR, and geospatial modeling to improve crop productivity and nutrient use efficiency. She is actively working on dragon fruit (Hylocereus spp.) cultivation systems in South Florida, evaluating high tunnel and open-field environments along with organic nutrient management strategies to understand plant growth, biomass, and nutrient dynamics. Her work links plant nutrient status (N, P, K) with spectral reflectance across VIS–NIR wavelengths using indices such as NDVI and GNDVI, while also applying hyperspectral data and machine learning for early detection and classification of plant diseases. She has strong expertise in LiDAR-based vegetation modeling (DSM, DTM, CHM) and Python-based statistical and machine learning approaches. Her academic interests include precision agriculture, remote sensing for crop and soil health monitoring, hyperspectral imaging for disease detection, nano-enabled fertilizers, and climate-smart sustainable farming systems. She aims to develop scalable, data-driven solutions that bridge geospatial science and agriculture to support food security and environmental sustainability.