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Mapping spatiotemporal variability of the urban heat island across an urban gradient in Worcester, Massachusetts using in-situ Thermochrons and Landsat-8 Thermal Infrared Sensor (TIRS) data

2020; Taylor & Francis; Volume: 57; Issue: 7 Linguagem: Inglês

10.1080/15481603.2020.1818950

1943-7226

Arthur Elmes, Marc Healy, Nicholas Geron, Michelle Andrews, John Rogan, Deborah G. Martin, Florencia Sangermano, C. A. Williams, Benjamin Weil,

Urban Green Space and Health

Landsat-8 derived Land Surface Temperature (LST) is used to measure Surface Urban Heat Island (SUHI) patterns and intensity in Worcester, MA, USA. Additionally, near-surface air temperature variability is measured using in-situ sensors to further contextualize the urban-to-rural land-cover driven thermal patterns in the study area. Despite the widespread applicability of thermal data, many SUHI studies do not compare LST with in-situ information. Comparisons between satellite-based and in-situ measurements of land surface temperature (LST) are important for establishing confidence in the utility of remotely sensed information to monitor and help improve the lived experience in cities. The objective of this study is to determine the capability of Landsat-8 Thermal Infrared Scanner (TIRS) to measure fine-scale temperature variation in a moderately sized urban area with a mixture of land-cover types. Ground-Level Temperature (GLT) was measured at 13 sites using iButton® Thermochron® temperature sensors from 13 June 2013 to 28 October 2014. Landsat-derived LST was compared to in-situ GLT using 30 Landsat-8 TIRS images for the commensurate time period. Sites with 1) eastern solar exposure; 2) low tree canopy coverage; and 3) proximity to impervious surfaces have higher annual temperature and greater offset from Landsat-derived LST. Sites with more than 47% tree canopy coverage have a more consistent LST and GLT relationship, (e.g. MAE < 3.74°C), show lower annual variability (e.g. r2 > 0.85), and also experienced low LST variability over the time series (e.g. coefficient of variation 0.007). Results indicate that site characteristics and land-cover type affect the offset between in-situ air temperature measurements and satellite-derived LST.