Dissertations and Theses
Date of Award
2025
Document Type
Thesis
Department
Earth and Atmospheric Sciences
First Advisor
Nicholas Steiner
Second Advisor
Kimberly Huppert
Third Advisor
Kyle McDonald
Keywords
UHI, urban heat, public housing, NYC, heat mitigation, remote sensing
Abstract
This work forms one part of a larger investigation into the ecosystem services provided by urban canopy that aims to characterize the temperature reduction provided by urban forests and develop process-level understanding of vegetation response to heat waves in order to improve estimates of heat mitigation in the face of extreme heat.
Surface temperatures are generally higher in cities than surrounding rural areas due to anthropogenically altered land cover. This phenomenon is known as the surface urban heat island (SUHI) and has significant consequences for the health of urban residents. The risk associated with extreme heat varies locally within cities due to both environmental conditions and social factors. Many cities have turned to increasing tree canopy as a strategy for mitigating heat. This study adapts modeling developed to characterize temperature reductions in large urban parks to look at intra-city temperature variation and the temperature reductions provided by much smaller, fragmented tracts of urban canopy present in public housing developments
We leverage land surface temperature measurements from NASA’s ECOSTRESS sensor, combined with high resolution land cover and structural data sets to model a relationship between canopy and temperature reduction in these highly complex and vital landscapes.
A focus on temperature mitigation within these developments connects fine scale variation in temperature to questions of environmental justice and inequality, and our research suggests potential avenues to increase mitigation in these important landscapes.
Recommended Citation
Steadman, Otillia, "Evaluating heat mitigation by urban canopy in New York City’s public housing developments" (2025). CUNY Academic Works.
https://academicworks.cuny.edu/cc_etds_theses/1191
