InSAR and GNSS data fusion for improved urban heat island estimation using local climate zone classification

Abstract

The phenomenon of the Urban Heat Island (UHI) is a common feature in city climates, impacting habitat quality and public health. The UHI refers to the temperature difference between metropolitan and countryside areas. This article introduces a new methodology for determining UHI using a high-resolution temperature map created by fusing Interferometric Synthetic Aperture Radar (InSAR) and Global Navigation Satellite Systems (GNSS) measurements. The validity of this method has been assessed by comparing the UHI results with the outputs of the Weather Research and Forecasting (WRF) model. Using the new approach, temperature determination focuses on the moist segment of the tropospheric delay. The wet tropospheric delay is divided into turbulent and non-turbulent components, with the first segment calculated using InSAR and the second using GNSS observations. After generating high-resolution temperature maps to compute the temperature difference between urban and non-urban regions and defining the UHI index, the research area was categorized into various classes based on land cover using the Local Climate Zone Classification (LCZ) approach. Finally, after calculating the UHI in different regions, the results were evaluated against the WRF model outputs. According to the statistical evaluations, the Root Mean Square Error (RMSE) of the UHI index obtained from the novel method and the WRF model outputs ranges from 0.7 to 0.4 Kelvin. The determination coefficient (R2) also varies from 0.85 to 0.9 in different months. These statistical markers illustrate the significant effectiveness of the suggested technique in computing the UHI phenomenon.

Keywords

• UHI
• GNSS
• InSAR
• LCZ
• Temperature