Shibamata, the setting of the film "Otoko wa Tsurai yo", with bronze statues of Torajiro and his sister Sakura by the station
The closest neighborhoods in the same city.
Shibamata is the setting for the "Otoko wa Tsurai yo" film series; bronze statues of the protagonist Tora-san and his sister Sakura stand in front of the station. Right outside Shibamata Station, the approach to Taishakuten (Daikyoji) begins at the station square. Centered on this temple and its approach, the "Katsushika Shibamata Cultural Landscape" became the first National Important Cultural Landscape in Tokyo in 2018.
What's valued here is that the streetscape built up through people's livelihoods is still alive today.
Behind the approach are houses; most of Shibamata is residential land, with many dango shops in 6-chome and 7-chome. Walking east to the end is the Edogawa River, and the opposite bank is already Matsudo, Chiba Prefecture.
This neighborhood covers Shibamata 1-chome through 7-chome, plus Kamakura 3-chome. In 2020, about 27,000 people lived here, roughly 135 people per hectare.
From our street photos, street cleanliness ranks 98th among 395 neighborhoods in Tokyo, and greenery ranks 112th, both in the top tier.
The Keisei Kanamachi Line at Shibamata Station only runs back and forth between Keisei-Takasago and Keisei-Kanamachi; to reach central Tokyo you need to transfer at Keisei-Takasago.
Shin-Shibamata Station is on the Hokuso Line, which connects to the Oshiage Line at Keisei-Takasago and runs through directly to the Toei Asakusa Line. There's a supermarket on the 1F of the station. The Ko55 bus passes in front of Taishakuten, heading to Koiwa Station and Kanamachi Station, running about every 7 to 8 minutes during the day.
Public transit ranks 268th among 395 neighborhoods in Tokyo, and convenience of daily life ranks 294th, both in the bottom tier.
Every year in late July, the Katsushika Noryo Fireworks festival is set off on the Edogawa riverbed in Shibamata 7-chome within this neighborhood. The City's announcement lists three nearest stations, and specifically notes that Shin-Shibamata Station is less crowded.
Based on points taken every 40 meters within the neighborhood from the Geospatial Information Authority's flood maps, about 80% of the points fall within the expected flooding zone, mostly 0.5 to 3 meters. Katsushika City's evacuation principle is to move in advance to a place that won't flood.
In a household registry from 721 preserved at Nara's Shosoin, there is a place called "Shimamata no Sato," which is generally believed to be present-day Shibamata, though other theories exist.
When Shibamata Station opened in 1899, it was a station on the Taishaku Jinsha Railway; it only became a Keisei station in 1912.
In April 2022, the approximately 5.3-kilometer grade separation project of the railway from Keisei-Takasago to near Edogawa Station was included in the national government's pre-construction preparations, with the section covering as far as Shibamata Station included. The project is led by the Tokyo Metropolitan Government, and will elevate or put the railway underground, removing 13 railroad crossings.
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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