Nasrin Nasrollahi’s dissertation has been selected by scientific publisher Springer for its Springer Theses series. Nasrollahi has finished her doctorate in civil and environmental engineering working with Distinguished Professor Soroosh Sorooshian and Associate Professor Kuo-lin Hsu in the Center for Hydrometeorology and Remote Sensing (CHRS). Theses in this annual publication are selected for their scientific excellence and impact on research. They must be nominated and endorsed by two recognized specialists.
The CHRS provides global, near real-time rainfall information using remote sensing technology. With a mathematical modeling approach, the center processes different electromagnetic signals picked up by satellites from clouds and storm systems and converts them into rain estimates. Used primarily by government officials and climate researchers for flood forecasting around the world, the information is also accessible to the public via the Internet.
Nasrollahi’s dissertation research involved improving the quality of precipitation estimation information that is provided by the center. She applied a multi-satellite, multi-spectral approach, incorporating data on clouds and rainfall from two recent NASA satellites and using machine learning techniques to develop a better estimate of rainfall. She also added a filter to reduce false rain signals in the data, which significantly improved the results.
The Springer Theses series, available to millions of readers worldwide, provides an accredited documentation of the research contributions made by today’s younger generation of scientists.