Heatmap Layers

Interactive layered analysis — combine multiple metrics

How to Use the Heatmap Layers

Key Takeaways

  • Map data is refreshed from URA, HDB and OneMap APIs — hover any marker for live values.
  • Use the filter panel to narrow results by district, bedroom type, price range, or tenure.
  • Click any marker or polygon to drill down into the underlying property or area detail.

What It Does

The Heatmap Layers map provides four independently toggle-able data overlays on a single Singapore basemap: Transit Proximity (red-intensity, distance to nearest MRT), Walkability Score (green-intensity, based on POI density across 7 amenity categories), CBD Distance (red-intensity, straight-line distance from Raffles Place), and Amenity Density (purple-intensity, concentration of hawker centres, supermarkets, clinics, parks, and schools). Each layer uses a kernel-smoothed heatmap — brig...

Why It Matters

Individual property data points — PSF, yield, ShiokNest score — tell you about a specific development but not about the quality of the surrounding area at a city-wide scale. The Heatmap Layers map fills this gap: it shows the spatial distribution of transit, walkability, CBD proximity, and amenity density simultaneously, so you can visually identify which parts of Singapore score well on multiple dimensions at once. The intersection of high-walkability and high-transit-proximity is the...

How It Works

  • Pan and zoom to the area of Singapore you are interested in.
  • Use the filter panel to narrow results by district, bedroom type, or price range.
  • Hover any marker or polygon for a tooltip with exact values.
  • Click a marker to open the underlying property or area detail page.

Examples

Transit + Walkability dual-layer: identifying the RCR sweet spot

Inputs
Layers enabled
Transit Proximity (red) + Walkability Score (green)
Layers disabled
CBD Distance, Amenity Density
Question
Which districts glow intensely on BOTH layers?
Results
Highest dual-intensity areas
D3 (Queenstown), D12 (Toa Payoh), D15 (East Coast)
High transit / lower walk
Parts of D19 (Hougang) — MRT-dense but thinner amenity
High walk / moderate transit
D10 (Holland / Bukit Timah) — walkable but fewer MRT nodes
Takeaway
D3 and D12 offer best dual-layer overlap at RCR/OCR pricing

How to read this: Enabling both layers simultaneously creates a visual intersection: the areas brightest under both overlays have genuine dual-advantage. D3 (Queenstown) lights up strongly on both because it has multiple CCL and EWL stations plus dense hawker and supermarket amenity. D12 (Toa Payoh) shows the same pattern. Both are priced significantly below D9/D10 despite similar dual-layer intensity — the heatmap makes this spatial story readable at a glance. Use it to shortlist neighbourhoods for your Property Finder search.

Amenity Density layer alone: high-amenity areas at OCR pricing

Inputs
Layer enabled
Amenity Density only (purple)
Question
Where does high amenity density extend beyond CCR boundaries?
Results
Expected high (CCR)
D9, D10, D11 — dense amenity, high PSF
Unexpected high (OCR)
D20 (Bishan), D12 (Toa Payoh) — dense amenity at OCR pricing
Moderate
D19 (Hougang/Sengkang) — good but not exceptional
Lower density
D27 (Sembawang northern fringe) — thinner amenity coverage

How to read this: The Amenity Density layer reveals that D20 and D12 match or exceed many RCR districts in amenity coverage — because they have large hawker centres, mature supermarkets, and established school clusters. A private condo in Bishan or Toa Payoh Central sits within an amenity catchment that rivals many RCR developments at 30–40% lower PSF. The heatmap makes this visible in 10 seconds; building the same comparison from a table would take considerably longer and would be less spatially intuitive.

Tips & Pitfalls

Expert Tips

  • Zoom out first to spot macro patterns before diving into individual districts.
  • Compare this map against the rental yield map to find high-demand, low-price outliers.
  • Use the legend to understand colour encoding — the same colour can mean different things on different maps.

Common Pitfalls

  • Judging a district by headline colour alone — the underlying sample size varies wildly across Singapore.
  • Confusing median with mean when both are shown — means are skewed by luxury outliers.
  • Forgetting that new-launch prices are discounted — resale prices are a better benchmark for fair value.

Frequently Asked Questions

Where does the map data come from?
Data is sourced from URA (Urban Redevelopment Authority), HDB, OneMap, and official Singapore government APIs, refreshed monthly.
How often is the map updated?
Transaction-based maps refresh monthly as URA and HDB publish new data. Planning layers (Master Plan, GLS) update as gazetted.
Can I filter by district or bedroom type?
Yes — use the filter panel on the map. Filter state is preserved in the URL so you can share a deep link to a specific view.

Related Resources

Map Browse all maps Insight Rental Yield Insight Calculator District Comparison Calculator Guide Property Guides