Privacy Index Ranking — Tamalpais-Homestead Valley
Updated June 22, 2026
See how neighborhoods in Tamalpais-Homestead Valley compare on privacy index. Rankings are based on measured data aggregated across each neighborhood boundary. How privacy index is measured →
Top Privacy Index Neighborhoods — Ranked
Expansive lots with significant spacing between structures provide much greater seclusion than the typical city average. According to iHuus data, this density of vegetation and distance between homes ensures a highly private living environment.
Residential separation varies across the area, as central structures sit closer together while perimeter estates benefit from significant forest buffers. According to iHuus data, privacy levels are generally consistent with the city average.
Residential spacing provides a balanced level of separation between neighbors. According to iHuus data, this level of privacy is roughly in line with the city average.
Full Tamalpais-Homestead Valley Privacy Index Ranking
| Neighborhood | Score | City Rank | vs. City Avg |
|---|---|---|---|
| Muir Woods Park | 7.5 | #1 | +1.3 ↑ |
| Homestead Valley | 6.3 | #2 | +0.1 ↑ |
| Tamalpais Valley | 6 | #3 | -0.2 ↓ |
| Almonte | 6 | #4 | -0.2 ↓ |
| Tamalpais Valley Junction | 6 | #5 | -0.2 ↓ |
iHuus Neighborhood Intelligence Insights
Get block-level neighborhood insights for Tamalpais-Homestead Valley
- 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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