Adeyeye received his undergraduate degree in Environmental Engineering from Stony Brook University. He interned at the New York State Department of Environmental Conservation. His goal is to develop a science and engineering based understanding of weather prediction and natural disaster prevention
Significant advances have been achieved in generating soil moisture (SM) products from satellite remote sensing and/or land surface modeling with reasonably good accuracy in recent years. However, the discrepancies among the different SM data products can be considerably large, which hampers their usage in various applications. Nevertheless, understanding the characteristics of each of these SM data products is required for many applications including flood assessment and drought monitoring. Therefore, most accurate soil moisture data products availability resulting in potentially great economic, environmental and social benefits.
The objective of 12 weeks NERTO research is to estimate bias, accuracy and reliability of these products, which can be used for validation and improvement for NOAA soil moisture product. This study inter‐compares soil moisture products from different remote sensing sensors (Microwave, and Thermal Infrared) and Land surface models with each other, and evaluates them against in situ SM measurements.The intern is expected to join our team for the effort and will understand the soil moisture data processing, statistical comparison and applications in hydrology and water resources management.