Abstract

The United Arab Emirates (UAE) has undergone major urban transformation after the establishment of the country in 1971. One noticeable change is urban expansion in terms of massive infrastructure, including new residential areas, highways, airports, and sophisticated transportation systems. Major landscape changes and disturbances, such as urban development, are among the major contributors to global climate change. Urban areas can be 3.5°C - 4.5°C warmer than neighboring rural areas, a phenomenon known as urban heat islands (UHIs). As such, urban development in the UAE was expected to follow a similar pattern and to be a major contributor to the country’s impact on global climate change. Analyses of multi-temporal (1988-2017) land surface temperature (LST) data obtained from Landsat satellite datasets over a desert city in the UAE showed unexpected results. Urbanization of desert surfaces in the study area led to a decrease of 3°C - 5°C in the overall LST. This was attributed to the associated expansion of green spaces in the newly developed urban areas, the expansion of date plantations and perhaps a cooling in the previously desert surface. Therefore, the UHI effect was not well demonstrated in the studied desert surfaces converted to urban areas.

Highlights

  • Knowledge of land surface temperature aids understanding of the temporal and spatial variations in global land surfaces [1]

  • Urban areas can be 3.5 ̊C 4.5 ̊C warmer than neighboring rural areas, a phenomenon known as urban heat islands (UHIs)

  • Analyses of multi-temporal (1988-2017) land surface temperature (LST) data obtained from Landsat satellite datasets over a desert city in the United Arab Emirates (UAE) showed unexpected results

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Summary

Introduction

Knowledge of land surface temperature aids understanding of the temporal and spatial variations in global land surfaces [1] LST data are typically retrieved from raw Landsat datasets by converting the digital number values of the thermal bands into absolute radiance values [3] [4]. These radiance values are used to find satellite brightness temperatures, calculated under the assumption of unity emissivity and using pre-launch calibration constants [3] [4] [5]. [8] used detailed land-cover maps with reasonably similar surfaces to help in measuring temperature gradients across a region. Estimating thermal conditions of land surface using satellite images requires the relationship between surface temperature, surrounding topography, and land use and land cover to be determined [4] [11]

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