Zelkova-lined avenue flanked by flagship stores, turn into the back lanes and it's all homes
The closest neighborhoods in the same city.
Brand flagship stores line both sides of Omotesando's zelkova-tree avenue; turn into the side streets and you'll find homes right next to clothing shops and beauty salons. Before this area became a fashion street, it was originally a quiet residential neighborhood.
Omotesando is the approach to Meiji Jingu Shrine, about 1.1 kilometers long, lined with about 160 zelkova trees. The avenue dips down into a valley partway along, where Cat Street—once the Onden River—was covered over into a walkway linking Omotesando and Ura-Harajuku.
People in this neighborhood are more likely to own their homes than Shibuya City as a whole: in 2020, about 45% owned their homes here, compared to about 39% for the whole City. People aged 65 and over make up about 20%, also higher than the City overall.
For public transit, this neighborhood ranks 56th out of 395 neighborhoods in Tokyo. Harajuku Station on the Yamanote Line is in Jingumae 1-chome, and the previous stop is Shibuya.
Meiji-jingumae Station on the Chiyoda Line is also in 1-chome. Omotesando Station is served by the Ginza Line, Chiyoda Line, and Hanzomon Line.
Based on our street photos, the buildings rank 28th.
Most shops open at street level or in low-rise buildings, rather than in station buildings or department stores.
The area along Omotesando is mostly shops and fashion streets; the whole neighborhood had about 100 people per hectare in 2020. For everyday shopping, this neighborhood ranks 175th out of 395 neighborhoods in Tokyo, and for healthcare it ranks 146th.
East of Harajuku Station, centered on Omotesando and Takeshita Street, is a shopping street aimed mainly at young people.
Harajuku Station's English-style wooden station building was completed in 1924. After the war, a cluster of love hotels appeared in front of the station, prompting local residents and the PTA to launch a cleanup campaign. In 1957, the Harajuku area was designated an educational and cultural district, and adult entertainment businesses disappeared from the area in front of the station.
In 1965, addresses were reorganized, and the area centered on Harajuku 1- to 3-chome was renamed Jingumae 1- to 6-chome, taking its name from Omotesando, the approach to Meiji Jingu Shrine.
By the 1990s, trendy clothing shops had begun appearing one after another in the residential area of Jingumae 3- and 4-chome. Since they moved in later than Takeshita Street, this area came to be called "Ura-Harajuku".
Harajuku Station switched to a new station building in 2020. A commercial facility is being built on the site of the old station building, which will try to recreate its original appearance as much as possible; as of the 2024 announcement, it was scheduled to open in winter of fiscal year 2026.
About 4.5 hectares of city-owned land in Jingumae 5-chome facing Aoyama-dori is to be redeveloped as a whole. A theater, startup support facilities, and a relocated Tokyo Metropolitan Central Library are expected to move in; the schedule depends on the recruitment of business operators, and no completion year has been set yet.
Compared with the 395 Tokyo neighborhoods in this guide (scores 0–10)
Hospitals with inpatient beds (2020 data), public elementary and junior high schools whose catchment covers this area, high schools and universities within 1 km, stations, parks of 1 ha or more, and large shopping malls and department stores. Many Tokyo junior high students attend private schools, so junior high catchments are only a guide.
Maps show the shops and the sights. What a street is like, you only know by walking it. TidyMap uses AI street imagery analysis and public facility data to turn each area's street environment and everyday convenience into something you can compare. Search an address and look at the street outside first.
How to read it: yellow = poor, blue = good; grey = not enough data
TidyMap rates the street environment and everyday convenience. It does not assess the home itself, safety, noise or actual living experience. Street environment scores use AI assessments of imagery; convenience scores use public facility data.
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