A shrine on the bluff, and below it a residential quarter running alongside the Shinkansen and train depot
The closest neighborhoods in the same city.
South of Kami-Nakazato Station is a cliff; Kami-Nakazato 1-chome, on top of the cliff, belongs to the Musashino Plateau, and Hiratsuka Shrine stands on this side. Below the cliff, 2- and 3-chome are low-lying land along the Sumida River, and the residential streets don't go far north before running into two train yards, one for the Shinkansen and one for conventional lines.
Kami-Nakazato Station is served only by the Keihin-Tohoku Line; in fiscal 2024 about 7,241 people boarded there per day, the lowest figure on this line. There's no large shopping street in front of the station, and the only supermarket is a Maruetsu Petit.
From Kami-Nakazato, if you go through an underpass nearly 200 meters long beneath the train yard, you come out at Oku Station. This station is in Showamachi 1-chome and is served by the Utsunomiya Line and the Takasaki Line; "Oku" is actually the name of a place in neighboring Arakawa City.
The two stations are separated by the train yard, and each has its own streets. About 10,000 people live in the whole neighborhood; because the train yard takes up so much land, that works out to only about 134 people per hectare.
Public transit ranks 113th out of 395 neighborhoods in Tokyo, the highest-ranking item for this neighborhood. Besides the two JR stations, on Meiji-dori at the northern edge of the neighborhood there's also Kajiwara Stop on the Toden Arakawa Line, with the Kajiwara Ginza shopping street nearby.
Based on our street photos, the neighborhood environment ranks second from the bottom out of 395 neighborhoods in Tokyo. The weakest sub-item is buildings, ranking 392nd; sidewalks rank 388th, also near the bottom.
According to Kita City's flood evacuation guidelines, if the Arakawa River floods, all the homes in the Showamachi area below the cliff fall within the flood zone, with an average inundation depth of about 1.68 meters, and in most places the water won't recede for more than two weeks. So the City office's top recommendation is to leave Kita City before the wind and rain get worse, evacuating to higher ground farther away.
Based on our own calculation using points taken roughly every 40 meters within the neighborhood from the Geospatial Information Authority's flood map, nearly 80% fall within the flood zone, mostly at depths of 0.5–3 meters; 1-chome on top of the cliff is mostly outside the flood zone. Kita City's flood hazard map was revised in September 2025.
In the Jomon period, the area below the cliff was still a shoreline. From the middle to the late Jomon period, people processed large quantities of oysters and clams on the sandbar that existed then, leaving behind a shell layer about 1 kilometer long. This site, the Nakazato Shell Mound, was designated a National Historic Site in 2000 and is now a park with explanatory signboards.
Hiratsuka Shrine on top of the cliff is said to have been built by the Toshima clan at the place where three brothers of the Minamoto clan stayed. In 1930, the area east of the railway was split off to become Showamachi.
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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