Landsat Retrieved Surface Properties Effects on the Day Time Temperature Pattern in New York City

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Sunday, 4 January 2015
Awolou Silvere Sossa, NOAA CREST REU/ City College of New York, bronx, NY; and B. Vant-Hull, R. Nazari, and M. Karimi

This study aims to assess the variability in the near surface temperatures in New York City and it's correlation to surface characteristics such as the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Moisture Index (NDMI) and Albedo. The dataset used is the product of a fine scale data collection with mobile instruments during the summer of 2012 and 2013. Landsat TM data is processed using Envi and Matlab in order to extract the land surface characteristics at the data collection points. The methodology involved correlating Landsat derived surface properties to a high resolution temperature and humidity spatial dataset to produce a statistical surface temperature anomaly model. Existing Modis retrieved surface properties were compared with the new Landsat dataset to investigate the better correlation with temperature. The results show an improvement on the correlation coefficients for the Landsat products compared to the previously used Modis dataset. The output will be incorporated to previous studies for a better estimation of the anomaly of temperature within Manhattan. This work will contribute to the development of a thermal map of the City of New York which will eventually be replicated for others cities.