Visual Appeal Ranking — Belmont
Updated July 8, 2026
Which Belmont neighborhoods have the highest visual appeal score? All 9 neighborhoods ranked. City average: 7.72/10. How visual appeal is measured →
Top Visual Appeal Neighborhoods — Ranked
Large homes and frequent upscale amenities contribute to a high level of visual interest. According to iHuus data, the aesthetic quality of this area is slightly above the Belmont city average.
Lush landscaping, custom homes, and private pools create a highly manicured aesthetic that is more polished than the Belmont average. According to iHuus data, the presence of large estates and complex architectural features defines the area's visual character.
Large custom homes with complex rooflines and private pools define this area. Lush landscaping and well-maintained properties contribute to a visual quality that is slightly higher than the Belmont average, according to iHuus data.
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Full Belmont Visual Appeal Ranking
| Neighborhood | Score | City Rank | vs. City Avg |
|---|---|---|---|
| Belmont Heights | 8 | #1 | +0.3 ↑ |
| McDougal | 8 | #2 | +0.3 ↑ |
| Cipriani | 8 | #3 | +0.3 ↑ |
| Plateau-Skymont | 8 | #4 | +0.3 ↑ |
| Western Hills | 8 | #5 | +0.3 ↑ |
| Central | 7.7 | #6 | — |
| Downtown | 7.5 | #7 | -0.2 ↓ |
| Sterling Downs | 7.2 | #8 | -0.5 ↓ |
| Homebire | 6.8 | #9 | -0.9 ↓ |
iHuus Neighborhood Intelligence Insights
Get block-level neighborhood insights for Belmont
- Street-level scores — see how individual blocks compare, not just neighborhood averages
- Micro-zone boundaries — identify quiet pockets, flood boundaries, and walkable clusters before you visit
- 15 dimensions in full — walkability, noise, air quality, school quality, insurance coverage, population age profile, urban/rural index, and more
- Boundary risk alerts — know if your address sits near a block boundary where scores drop, the kind of detail no listing will ever mention
- School insights — individual school ratings and insights, not just district-level data
- Compare before you commit — side-by-side data across neighborhoods, down to block precision
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