Urban Heat Vulnerability Indices for Melbourne Using Multiple Weighting Techniques

37.8 MB of supplementary materials for a paper submitted to the 33rd International Conference on Geoinformatics 2026. The package contains spatial data inputs, derived indices, and processing scripts focused on urban heat vulnerability in Melbourne, Victoria, Australia. It was authored by Ryan Turner and last updated on 2026-05-26.

Use Cases

• Compare urban heat vulnerability index results based on three different spatial weighting techniques (equal weighting, entropy weighting, principal component analysis)
• Analyze spatial consensus and pairwise agreement between different weighting methods for composite indicators
• Derive satellite-based inputs like Land Surface Temperature and Normalised Difference Vegetation Index using the provided Google Earth Engine scripts
• Reproduce the workflow for generating heat exposure, sensitivity, and adaptive capacity sub-indices using the Jupyter notebook

Strengths

• Includes six distinct spatial data inputs (LST, POPD, NDVI, NDBI, POPV, IRSD) in GeoTIFF format
• Provides three composite urban heat vulnerability indices (UHVI_EQW, UHVI_ENW, UHVI_PCA) for direct comparison
• Contains both raw data and full processing code (JavaScript scripts and Jupyter notebook) for reproducibility

Limitations

• Row count is unknown, which may limit suitability assessment
• Column-level documentation is absent; field semantics must be inferred after download
• Data may reflect geographic bias inherent to the single study area of Melbourne

Provenance

Source

Ryan Turner via figshare

Collection Method

Likely derived from satellite imagery (Landsat 9, Sentinel 2) and demographic data (WorldPop) using Google Earth Engine and processed via a Jupyter notebook.

Time Range

Summer composite Landsat 9 LST for 2023-2025; WorldPop data for 2025.

Freshness

Last updated 2026-05-26 01:40:36; freshness should be verified

Geography

Melbourne, Victoria, Australia.