Place and postal discovery

Nearby Places & ZIP Codes

Choose a populated place, then discover nearby towns and the postal codes that match the selected place in the active postal dataset.

Places near Yono

Radius: 30 km · Japan

OpenStreetMap

Map around Yono

The marker shows the selected gazetteer place used as the centre of the nearby-place calculation.

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Map data © OpenStreetMap contributors.

Nearby populated places from the gazetteer
DistancePlaceAreaPopulation fieldPostal action
9.3 kmŌzatoOsaka JP9,079Find codes
9.9 kmKawanishiHyōgo JP0Find codes
10.8 kmMinohOsaka JP136,868Find codes
11.8 kmKameokaKyoto JP97,181Find codes
12.6 kmKimokawaHyōgo JP29,680Find codes
12.6 kmIkedaOsaka JP104,993Find codes
13.5 kmIbarakiOsaka JP287,730Find codes
13.7 kmKawanishiHyōgo JP155,165Find codes
13.8 kmTakatsukiOsaka JP354,468Find codes
15.7 kmToyonakaOsaka JP401,558Find codes
16.3 kmMinaseOsaka JP30,927Find codes
17.5 kmItamiHyōgo JP198,138Find codes
17.6 kmOyamazakiKyoto JP15,953Find codes
17.9 kmSuitaOsaka JP385,567Find codes
18.0 kmNagaokaKyoto JP0Find codes
18.4 kmSettsuOsaka JP87,456Find codes
18.5 kmHirakataOsaka JP406,331Find codes
18.6 kmTakarazukaHyōgo JP226,432Find codes
19.2 kmKōtariKyoto JP80,608Find codes
19.6 kmArashiyamaKyoto JP50,000Find codes
19.7 kmMukōKyoto JP56,859Find codes
19.8 kmYawataKyoto JP71,656Find codes
20.9 kmNantanKyoto JP31,629Find codes
21.1 kmNeyagawaOsaka JP238,549Find codes
21.7 kmKadomaOsaka JP131,727Find codes

Postal codes matching Yono

What this explorer adds beyond a nearby-postal-code search

The existing Nearby Postal Codes tool starts with a postal code and returns nearby postal records. This tool starts with a populated place from the general GeoNames gazetteer. That difference is useful when you know a town or city but want to discover surrounding settlements before deciding which postal record to inspect.

GeoNames' general gazetteer includes coordinates and population fields for populated places. ZipCodeGlobe uses those coordinates to calculate straight-line distances and then offers postal actions from a separate postal snapshot. The geographic and postal sources are deliberately not merged into one opaque table.

Distance is context, not a delivery promise

Distances are great-circle calculations between source coordinates. They do not account for roads, rivers, mountains, customs borders, delivery zones or carrier service areas. A nearby place can be operationally difficult to reach, and a farther place can share a direct transport corridor. Use the result to explore geography, not to promise delivery time or eligibility.

The tool limits both radius and result count. Those limits keep the response fast on shared hosting and prevent a global radius query from turning into an unbounded table scan.

Why nearby towns are useful for postal research

Place names are often ambiguous. Seeing neighbouring settlements can quickly confirm whether you selected the intended Springfield, Portland or Albany. Nearby places can also reveal spelling variants and suburban relationships that are hard to understand from a bare postal table.

After selecting a nearby place, the Place to Postal Code Finder compares its canonical and alternate names with the active postal snapshot. If it cannot make a conservative match, it says so instead of assuming geographic proximity proves postal equivalence.

How this supports better engagement without doorway pages

Every nearby-place link represents a genuine next task: understand the place, look for associated postal codes, or move to another nearby settlement. Raw place pages remain noindex by default. ZipCodeGlobe does not create thousands of indexable pages merely because the gazetteer contains thousands of names.

Search-demand-backed city ZIP guides remain the earning layer. They can use gazetteer context such as timezone, first-level administration, nearby populated places and population fields to become more useful, while still requiring human originality review and postal-specific statistics before indexation.

Choosing a useful search radius

A small radius is best when you are distinguishing suburbs, neighbouring villages or a dense urban area. A wider radius is more appropriate for rural regions where settlements are farther apart. Increasing the radius does not make the source more precise; it simply broadens the geographic candidates considered around the selected coordinate. ZipCodeGlobe still caps the candidate pool and ranks the final set by actual calculated distance.

If the intended town does not appear, first confirm that you selected the correct country and administrative area rather than immediately increasing the radius. A same-named place in another state can produce a perfectly valid but irrelevant neighbourhood. For postal research, the safest sequence is place identity first, nearby geographic context second, and postal-code verification third. That order is why this explorer links into the Place to Postal Code tool and the normal aggregated postal-result pages instead of declaring a nearby code from proximity alone.

International and multilingual place names

The main GeoNames format includes UTF-8 names, ASCII names and alternate names. Those fields improve discovery for accents, transliterations and common variants. A visitor can often find the intended place even when the spelling differs from the postal file. The canonical place identity is still the GeoNames ID rather than the wording of the search query.

Alternate names are a search aid, not a basis for generating duplicate URLs. That restraint helps both usability and crawl quality.

Data freshness and responsible verification

The general gazetteer can be refreshed independently through country dumps, the cities500 subset and GeoNames daily modification/delete files. The postal dataset has its own snapshot workflow. ZipCodeGlobe therefore shows separate freshness signals in the footer and data-source documentation.

For shipping, taxation, legal boundaries or emergency-service decisions, treat this tool as context and verify the final address against the responsible authority. Public datasets are valuable for discovery but are not a substitute for jurisdiction-specific operational data.