International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B4, 2012 
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia 
DATA UPDATING METHODS FOR SPATIAL DATA INFRASTRUCTURE THAT 
MAINTAIN INFRASTRUCTURE QUALITY AND ENABLE ITS SUSTAINABLE 
OPERATION 
Saya Murakami ', Takashi Takemoto, Yutaka Ito 
Kokusai Kogyo Co., Ltd, 2-24-1 Harumi-cho, Fuchu-shi, Tokyo, 183-0057 JAPAN - (saya murakami, 
takashi takemoto, yutaka_ito)@kk-grp.jp 
Commission IV, WG IV / 1 
KEY WORDS: Spatial Information Sciences, Spatial Infrastructures, Framework Data, Sustainable, GIS, Reliability 
ABSTRACT: 
The Japanese government, local governments and businesses are working closely together to establish spatial data infrastructures in 
accordance with the Basic Act on the Advancement of Utilizing Geospatial Information (NSDI Act established in August 2007). 
Spatial data infrastructures are urgently required not only to accelerate computerization of the public administration, but also to help 
restoration and reconstruction of the areas struck by the East Japan Great Earthquake and future disaster prevention and reduction. 
For construction of a spatial data infrastructure, various guidelines have been formulated. But after an infrastructure is constructed, 
there is a problem of maintaining it. In one case, an organization updates its spatial data only once every several years because of 
budget problems. Departments and sections update the data on their own without careful consideration. That upsets the quality 
control of the entire data system and the system loses integrity, which is crucial to a spatial data infrastructure. To ensure quality, 
ideally, it is desirable to update data of the entire area every year. But, that is virtually impossible, considering the recent budget 
crunch. The method we suggest is to update spatial data items of higher importance only in order to maintain quality, not updating all 
the items across the board. We have explored a method of partially updating the data of these two geographical features while 
ensuring the accuracy of locations. Using this method, data on roads and buildings that greatly change with time can be updated 
almost in real time or at least within a year. The method will help increase the availability of a spatial data infrastructure. We have 
conducted an experiment on the spatial data infrastructure of a municipality using those data. As a result, we have found that it is 
possible to update data of both features almost in real time. 
1. INTRODUCTION 
This study focuses on the fact that planimetric features vary in 
Japan suffered massive damage in the Great East Japan requirements in their uses on a map. We have explored 
Earthquake that struck on March 11, 2011. In hard-hit areas, updating methods that will enable sustainable operation of 
local governments were brought to a standstill. Documents, spatial data infrastructures by partially updating the data on 
including maps and registers, were carried away by the ensuing features that are highly important and change substantially over 
tsunami. To share information in the disaster areas, people set time, and improving the freshness of data while maintaining its 
up an earthquake information site using OpenStreetMap, accuracy. 
sinsai.info, and provided information on water supply station. 
These incidents highlighted the importance of spatial data 
infrastructure, which links various information with locations. 2. EXAMINATION PROCEDURE 
In Japan, advanced municipalities use spatial data As shown in Figure 1, we studied the methods according to the 
infrastructures. In principle, data on planimetric features following procedures: (1) we classified planimetric features 
excluding roads are updated every five to more than 10 years according to requirements from the perspective of use on a 
with data acquired by aerial photogrammetry on a scale of topographical map; (2) we developed updating methods for 
1:2500 (a horizontal standard deviation of approximately 1.75 high-demand planimetric feature data and to required quality 
m). Municipalities update data on roads every year by field based on category; (3) we conducted a field study in Mie 
survey to a scale of at least 1:1000 (a horizontal standard Prefecture to verify those methods; and (4) we evaluated the 
deviation of approximately 0.70 m). In reality, different methods. 
departments update data with different frequencies and to 
different scales, as the required quality (accuracy and Mie Prefecture is an area of Japan that is prone to disasters, 
freshness) varies depending on the purpose of spatial data such as tidal waves and landslides. Having a better awareness 
infrastructure. This reality reduces the quality of spatial data than other prefectures of the effectiveness of maps, Mie 
infrastructures. Prefecture was an early adopter of spatial data infrastructure 
that integrates cities, towns and villages in the area. Mie 
It would be desirable to update all data on planimetric features Prefecture also has a problem with maintaining infrastructure 
frequently and with consistent accuracy, but achieving this is quality. For these reasons, we chose this prefecture for the field 
difficult. Most governments are hard-pressed financially and study. 
cannot afford to update all the data each year by using aerial 
photogrammetry and field surveys. 
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