Nick Steiner, PhD 🛰️
Nick Steiner, PhD

Research Assistant Professor, Earth & Atmospheric Sciences

About Me

Nicholas Steiner is a Research Assistant Professor in the Department of Earth and Atmospheric Sciences at the City College of New York. His research focuses on the applied science of remote sensing for terrestrial ecosystems and surface hydrology, with expertise in using microwave remote sensing observations and modeling to advance understanding of surface hydrology, wetland dynamics, and the water and carbon cycles.

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Interests
  • Remote Sensing
  • Surface Hydrology
  • Environmental Science
  • Geospatial Intelligence
Education
  • PhD, Earth and Environmental Science

    The Graduate Center, City University of New York

  • MA, Earth Science

    The City College of New York, City University of New York

  • BA, Arts and Sciences

    University of Colorado, Boulder

📚 My Research

I am a Research Assistant Professor in the Department of Earth and Atmospheric Sciences at City College of New York. My research focuses on remote sensing, surface hydrology, and environmental science, with applications in wetland monitoring, carbon cycle dynamics, and geospatial intelligence.

I work with NASA missions such as NISAR and ECOSTRESS, developing methods to improve satellite-based observations of surface water dynamics, soil moisture, and vegetation structure.

Please reach out to collaborate! 🚀

Featured Publications
Recent Publications
(2025). Full-wave Simulations of Forest at L-band with Fast Hybrid Multiple Scattering Theory Method and Comparison with GNSS Signals. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
(2024). ADVANCED OPERATIONAL FLOOD MONITORING IN THE NEW ERA: HARNESSING HIGH-RESOLUTION, EVENT BASED, AND MULTI-SOURCE REMOTE SENSING DATA FOR FLOOD EXTENT DETECTION AND DEPTH ESTIMATION. Authorea Preprints.
(2024). High-Resolution Assessment of Heat Mitigation and Water Stress in New York City's Urban Forests Using ECOSTRESS and UAVSAR. AGU24.
(2024). Near-real-time Flood Mapping System Using Multi-source SAR images: Adaptive Initialization Enhances Detection in Snow and Arid Terrains. Authorea Preprints.