Privacy Index Ranking — Lake Forest
Updated June 22, 2026
See how neighborhoods in Lake Forest 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
Residential lots feature standard suburban setbacks and natural greenbelts that provide more separation between neighbors than the Lake Forest average. This moderate density offers a functional buffer between homes according to iHuus data.
Residential spacing provides a degree of separation through standard setbacks and natural greenbelts. According to iHuus data, this level of privacy is higher than the Lake Forest average.
Residential spacing is consistent with the city average, featuring a mix of standard suburban setbacks and some areas of higher density. Some homes sit close to neighbors or feature shared walls, though natural greenbelts provide occasional buffers according to iHuus data.
Full Lake Forest Privacy Index Ranking
| Neighborhood | Score | City Rank | vs. City Avg |
|---|---|---|---|
| Sycamore Creek | 6 | #1 | +1.1 ↑ |
| Montbury | 6 | #2 | +1.1 ↑ |
| Grandview Crest | 4.8 | #3 | -0.1 ↓ |
| Woodside | 4.5 | #4 | -0.4 ↓ |
| Cedar Glen | 4 | #5 | -0.9 ↓ |
| Lower Greenridge | 4 | #6 | -0.9 ↓ |
| Upper Greenridge | 4 | #7 | -0.9 ↓ |
iHuus Neighborhood Intelligence Insights
Get block-level neighborhood insights for Lake Forest
- 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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