Dr. Paz-Kagan is the PI of the Agro-informatics Lab. We study plant and soil interactions ‎‎using remote sensing applications, focusing on identifying and quantifying spatial and ‎‎‎temporal ‎patterns in soil and plant distribution and their response to ‎biotic and abiotic stress ‎in ‎agricultural and natural systems. Studying such complex ‎interactions of multivariate and ‎multi-scaled ‎problems requires quantitative and ‎interdisciplinary approaches. Consequently, ‎our research ‎increasingly involves developing and using computer models, ‎ state-of-the-art ‎‎remote sensing ‎technologies, earth observation systems, ‎spectroscopy, ‎spatiotemporal ‎‎modeling, big-data analytics, ‎machine learning modeling‎ with advanced imaging ‎‎processing ‎methods.‎

‎Our research includes developing remote sensing (sensors, algorithms, applications) using ‎imaging spectroscopy, light detection and ranging (LiDAR), hyperspectral, multispectral, ‎‎thermal imaging, UAV application, plant and soil spectroscopy, and satellite data analysis. ‎‎The data processing includes applying and developing artificial intelligence, machine ‎learning, machine vision and ‎optimization algorithms, spatial data analysis, and ‎time series analysis.‎
‎
Publications:
‎https://www.researchgate.net/profile/Tarin-Paz-Kagan-2
Lab Website:‎
https://paztarin.wixsite.com/mysite