Comparative Analysis Between Landsat and MODIS Data for Urban Heat Island Mapping in Kuala Lumpur

Abstract

The urban heat island effect, a critical environmental challenge exacerbated by urbanization, significantly impacts climate change, energy consumption, and public health. Remote sensing technology offers an efficient approach for UHI monitoring, with Landsat and MODIS being the most widely used data sources. This study evaluates the applicability of Landsat 8/9 (30 m spatial resolution) and MODIS LST (MOD11A1, 1 km spatial resolution) data in UHI monitoring, using Kuala Lumpur as a case study from 2015 to 2024. We compare land surface temperature retrieval accuracy, assess the influence of spatial and temporal resolution on UHI detection. Higher NDVI value (>0.1) reduces UHI by cooling, while higher LST (>31.43° C) intensifies UHI through surface heating. Results indicate that Landsat’s high spatial resolution (30 m) makes it more suitable for microscale urban heat island analysis, whereas MODIS, with its high temporal resolution (daily observations), is better suited for large-scale, dynamic UHI monitoring. This study provides valuable insights for selecting optimal remote sensing data for UHI research, supporting urban planning and climate mitigation strategies.