Old settlement on the banks of the Kyu-Edogawa, where in February men dress as women and go door to door praying for freedom from illness
The closest neighborhoods in the same city.
Every year on the last Sunday of February, men dressed in makeup and women's clothing set out from Shinzoin in 4-chome, carrying sutra boxes as they make a circuit through the neighborhood. Homeowners wait at their front doors with celebratory gifts, and the procession calls out "congratulations," praying for the household to be free of illness and disaster.
This neighborhood's designated intangible folk cultural property is called the Ikazuchi no Daihannya. Ikazuchi is the name of an old settlement, built on the natural levee along the banks of the Kyu-Edogawa. Across the river is already Urayasu City in Chiba Prefecture; here it's about 1.5 km from Tokyo Bay, held back by the levee.
This neighborhood covers the parts of Higashi-Kasai that are farther from Kasai Station—1, 3, 4, 8, and 9-chome—with a population of about 23,000 in 2020.
There's no station within the neighborhood; daily life relies on buses connecting to Kasai Station. The Ikazuchi Fudomae bus stop in front of Shinzoin is on the Kasai 22 bus route, with one end at Kasai Station and the other at Toei Shinjuku Line's Ichinoe Station.
The Kasai 21 bus route passes through 8-chome and 9-chome: 8-chome's community hall houses the Higashi-Kasai Library, and 9-chome has the Kasai Riverside Mall shopping center.
Based on our street photos, greenery ranks 228th out of 395 neighborhoods in Tokyo, in the middle range, which is the highest-ranking category for this neighborhood. Daily shopping ranks 338th, in the lower range.
Real estate listings mostly cite Kasai Station; the median walk time from 1, 4, 8, and 9-chome is 15 to 16 minutes. There aren't many listings in 3-chome near the river; most cite Urayasu Station on the opposite bank. Overall convenience ranks 391st, and public transit and medical/pharmacy access are also both near the bottom.
Based on the Geospatial Information Authority's flood inundation hazard maps, TidyMap sampled points roughly every 40 meters within the neighborhood: excluding the river surface, about 90% fall within the projected flood zone, mostly 0.5 to 3 meters deep, with about 10% at 3 meters or more.
About 3 days before a large-scale flood disaster, the five Koto-area Cities jointly decide, and in principle all residents evacuate outside Edogawa City (wide-area evacuation). Edogawa City's flood hazard map includes area-by-area maps, marking the flood depth at each location.
In medieval times, the northern part of Higashi-Kasai was called Nagashima, and Nagashima Port was a harbor that prospered through river transport. In 1629, the Shinkawa River was dug along the northern border of this neighborhood, later becoming a major artery of Edo's water transport.
Myokenjima, an island in the river within 3-chome, was an exclave of Shimosa Province during the Edo period, and wasn't incorporated into Tokyo from Chiba Prefecture until 1895. It was only after Kasai Station opened in 1969 that Higashi-Kasai developed into a residential area.
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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