Recently, Tokyo terminated its traditional visual-identification work, which had been used for 20 years, and shifted to a new automated system. This article introduces the Fixed Assets Change Judgment (FACJ) system and its core tool, RealScape. RealScape automatically detects changes in the height and color of buildings based on three-dimensional analysis of aerial photographs. It employs a unique pixelby-pixel stereo processing method and enables a foot-level precision for each building. RealScape automatically detects changes in the height and color of buildings based on three-dimensional analysis of aerial photographs. The three-dimensional analysis employs a pixel-by-pixel stereo processing method that calculates the height of each pixel in aerial photographs and thus enables precise difference detection between previous and current aerial photographs. Since then, it has been used at its tax bureau every year to calculate the municipality's fixed-asset tax. After the success in Tokyo, other major city governments, including Osaka and Sapporo, have followed suit. The Japanese fixed-property tax is imposed by municipalities on the owners of land, buildings, and depreciation assets (all hereinafter referred to as "fixed assets") on January 1 of every year by calculating the tax sum according to current asset values.

The Japanese fixed-property tax is imposed by municipalities on the owners of land, buildings, and depreciation assets (all hereinafter referred to as "fixed assets") on January 1 of every year by calculating the tax sum according to current asset values. This identification work is contracted out to survey companies. The identification of such en over a scale that can cover an actual area of 800 changes is entrusted to survey companies who hire by 600 meters or 500 by 600 meters (variable a large number of workers (figure 1, left). However, depending on the municipality), and every municipality reliance on human labor has led to problems has several hundred photographs that must detailed in the following paragraphs. Under these circumstances, the incentives for It takes about 10 hours to read and interpret a single the municipalities to overcome such challenges by photograph, and the average municipality automating or systematizing the photograph-reading must perform this work for several hundred photographs.

The Tokyo Metropolitan Government is the largest municipality in Japan and conducts building change identification work. Recently, Tokyo terminated its traditional visual identification work that has been in use for 20 years and shifted to a new automated system. This paper is intended to introduce the Fixed Assets Change Judgment (FACJ) system and its core tool, RealScape. RealScape automatically detects the changes in the height and color of buildings based on three-dimensional (3D) analysis of aerial photographs. It employs a unique pixel-by-pixel stereo processing method and enables the foot-level precision for each building. RealScape detects building changes more accurately than visual judgment operations by humans and reduces the labor costs to one third of the traditional approach and the required judgment duration to about two weeks per 100km2.