Date of Graduation

7-2026

Document Type

Thesis

Degree Name

Master of Science in Geography (MS)

Degree Level

Graduate

Department

Geosciences

Advisor/Mentor

Tullis, Jason

Committee Member

Peter, Brad

Second Committee Member

Holland, Edward

Keywords

Land Surface Phenology (LSP), Thermal Remote Sensing, Urban Heat Islands (UHI), Land Surface Temperature (LST)

Abstract

Thermal remote sensing has been widely applied to characterize urban heat islands (UHI) and their relationship to land use; however, few studies have explored the relationship between land surface temperature (LST) and land surface phenology (LSP). This study focused on the relationship between LST and LSP in the metropolitan region of Kansas City, Missouri, USA using Landsat 8 satellite images from 2015 to 2024. Thermal and normalized difference vegetation index (NDVI) time series were processed using Google Earth Engine to derive annual LST metrics alongside phenological indicators including timing of green-up and senescence as well as growing season length. Individually, LST and LSP both exhibited interannual variability with clear seasonal (spring, summer, fall) and zonal (urban, suburban, rural) patterns. The results indicated noticeable summer heat intensity of 6.7 ± 0.5 °C, and the thermal footprint extends 12-14 km from the urban core. Additionally, urban areas showed 12 days earlier green-up and 18 days later senescence, producing a 30-day longer growing season compared to rural areas, but urban vegetation showed reduced urban peak vegetation greenness (NDVI) is only 56% of rural. NDVI and LST showed the strongest negative correlation (r = -0.75). Moreover, urban impervious surfaces were associated with a 10% increase corresponding to 1.2 °C warming, and 0.1 increase in NDVI was associated with surface cooling of approximately 3%. Spatial patterns indicated that areas with higher vegetation coverage generally exhibit lower LST and more stable LSP, while thermally intense areas displayed greater LSP variability. The results demonstrated the value of integrating LST and phenological metrics to assess urban thermal dynamics and vegetation response, with implications for excessive heat mitigation, and effectiveness of urban planning in large metropolitan areas.

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