Integrating Multi Sensor Satellite Data for Urban Heat Island and Vegetation Dynamics Analysis in Bali Putu Abel Nugraha Ardyan*, A. Muh. Tegar Juliarga Amrul, and Ilham Alimuddin
a & b) Geological Engineering Departmen, Faculty of Engineering, Hasanuddin University, Gowa, Indonesia
Abstract
Urban heat island (UHI) dynamics in tropical, monsoon-influenced environments require
integrated, multi-source observations to capture complex diurnal and seasonal variability. This study
integrates MODIS daytime and nighttime land surface temperature (LST), Landsat 8 thermal
observations, and Sentinel-2 normalized difference vegetation index (NDVI) to evaluate spatio
temporal patterns of UHI intensity and vegetation dynamics across Bali Province, Indonesia. Two
seasonal windows were examined, May to July 2024 (dry season) and December 2024 to February
2025 (wet season) to characterize monsoon-driven contrasts. Satellite-derived thermal and vegetation
metrics were processed, analyzed, and mapped across the study area, with key thematic outputs
presented as LST and SUHI maps, NDVI distributions, and summary figures. Results show pronounced
seasonal contrasts: SUHI signals are weak or slightly negative during the dry season but become
strongly positive in the wet season, with localized SUHI values reaching about 9 degrees Celsius in
highly urbanized areas. Daytime and nighttime phases exhibit differing responses, underscoring the
need to consider both diurnal components. Vegetation consistently moderates surface temperatures,
with higher NDVI associated with lower LST, while densely built and coastal zones correspond to
higher temperatures, reflecting local controls such as urban morphology, street-canyon effects, and
coastal proximity. The multisensor integration reconciles differences in spatial resolution and temporal
sampling across platforms, improving spatial coherence of thermal patterns and enabling more reliable
detection of spatial hotspots and seasonal shifts that single-sensor analyses may underrepresent.
Analytical outputs include composite LST maps, SUHI metrics, NDVI distributions, and comparative
summaries that together characterize spatial heterogeneity and temporal dynamics. These consolidated
outputs offer practical, data-driven i
Keywords: Geospatial Data Integration, Multisensor Analysis, Remote Sensing, Urban Heat Island, Vegetation Dynamics
