Applications of Micro Geo Data for Urban Monitoring

Yuki Akiyama（aki@iis.u-tokyo.ac.jp）
Assistant professor
Earth Observation Integration and
Fusion Research Institute (EDITORIA)
The University of Tokyo
Applications of Micro Geo Data
for Urban Monitoring
August 26, 2014 @Coex, Seoul , Korea
Smart Geospatial EXPO 2014
ICGIS2014

2
Recently, various geo data are available.

3
Building scale
Building data：Zmap-TOWNⅡ ©Zenrin CO. Ltd.
Detailed geo data are available.
Building scale → household scale → person scale…

4
Building scale
Household scale
Micro Population Census ©Yuki Akiyama

5
People flow data ©CSIS
Person scale
Building scale
Household scale

6
Person scale
People flow data ©CSIS
Big data with location and time
＝Micro Geo Data（MGD）
Building scale
Household scale

7
Japanese government is looking to the
utilization of MGD.
NHK News Web（2014/06/09）
http://www3.nhk.or.jp/news/html/20140609/k1
0015066701000.html
Japanese government begins
to introduce legislation toward
promotion of utilization of big
data.
Ministry of Internal Affairs and Communications of
Japan authorized a budget of approx 75million
USD for utilization and application of geo big data.
http://www.soumu.go.jp/main_content/000264428.pdf

8
Recently, personal computers and mobile phones are
becoming widespread and internet environment are
being developed rapidly.
Anyone can access detailed digital map.
The widespread use of detailed digital map creates demands
for more detailed and reliable spatial data then before.
Researches to utilize such spatial data attract rising attention.
Spatially and temporally high resolution big data
which can cover whole country area
＝Micro Geo data (MGD)
It is gathering attention
how to develop, apply and popularize MGD now.
Coming of age to utilize MGD

9
Today’s Keyword
Micro Geo Data (MGD)
=Spatial and temporal big data that spatial and
temporal resolutions are very fine
①Available Japanese MGD for urban monitoring
②Examples of urban monitoring using MGD
③MGD Forum

10
Census data aggregated by administrative unit
(e.g. Population census)
Digitalization Map data
Integration
You can monitor
actual states of
residents
(populations) in
each cities, towns
or villages. ©Softnat

11
Road length data (Digital
national land information,
500m grid)
Grid statistics（e.g. Commercial statistics）
Commercial statistics aggregated into
1km, 500m or 250m square grids

12
Many previous studies used relatively macro scale GIS data.
In the case to collect micro scale data (i.e. each building,
shop or pedestrian), many studies relayed on field survey.
> it is difficult to collect micro scale data in broad area.
Data volume of micro scale data in broad area are very
large.
> Previously, it is difficult to handle them because of
constraint of hardware’s performance.
Recently, it is possible to handle large data thanks to
improvement of hardware’s performance. In addition, it has
almost come to realize to accumulate micro scale data with
the popularization of large volume hard discs.

History of commercial-release PC specs
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CPUクロック数[MHz] メインメモリ[GB]
History of CPU clocks and main memory volumes by NEC home PC
[MHz] [GB]
Specs of commercial-release PC are improving rapidly.
In addition, SaaS and cloud computing are spreading now.
Windows95
Released
Windows XP
Released
Google
Founded
Google Map
Released
PC8001(1985)
1,750USD
PC-9821Ct20(1997)
4,150USD
VN370(2012)
975USD
CPU clocks [MHz] Main memory[GB]

History of commercial-release HDD specs
14
Volumes of HDD are also improved rapidly.
Their volumes are increasing 1.6~2 times / yrs.
※http://www.infonet.co.jp/ueyama/ip/hardware/harddisk2.html
Commercial-
release HDD
HDD confirmed
in research level
Hundredfold in 10 yrs.
（100MB→10GB）
Hundredfold in 10 yrs.
（10GB→1TB）
Now, we can develop environment
to use MGD easlly!

15
Many previous studies used relatively macro scale GIS data.
In the case to collect micro scale data (i.e. each building,
shop or pedestrian), many studies relayed on field survey.
> it is difficult to collect micro scale data in broad area.
Data volume of micro scale data in broad area are very
large.
> Previously, it is difficult to handle them because of
constraint of hardware’s performance.
Recently, it is possible to handle large data thanks to
improvement of hardware’s performance. In addition, it has
almost come to realize to accumulate micro scale data with
the popularization of large volume hard discs.
Next interesting stage is…
How to utilize MGD?

1 year
２ months
1 hour
5 years
Existing data and census MGD New MGD developed in our study
Open data Commercial data（Some of them is free in case of academic research） 16
Available Japanese MGD for urban monitoring
Some census (grid)
Population census
Commercial statistics
Business census etc.
Temporal
Resolution
Real time
Prefectures/
Cities
Each building/
person
Grid scale
(1km / 500m grid)
Spatial
Resolution
Spatial data with high
spatial and temporal
resolution
Collected by field survey or
questionnaire survey by
researchers
→Fine reliability
Large amount of labor
国勢調査
商業統計
事業所・企業統計
Previously, these kinds of
data are not used (or can not
used) adequately.
If you can use raw data…
・Development and handling
of them are difficult.
・Development of Sharing
environment of them is
difficult.

1 year
２ months
1 hour
5 years
Various mobile census
People flow dataset
Commercial
Accumulation
Statistics
Micro Population
Census
Some census (grid)
Population census
Temporal
Resolution
Real time
Prefectures/
Cities
Each building/
person
Grid scale
(1km / 500m grid)
Spatial
Resolution
Web data
（Estate, restaurants, SNS etc.)
Residential map
Telephone
directory
High spatial and temporal resolution
・They are very helpful for
detailed urban monitoring.
・New MGD can be developed using
them.
・Data holders are seeking how to
utilize MGD.

1 year
２ months
1 hour
5 years
People flow dataset
Commercial
Accumulation
Statistics
Micro Population
Census
Some census (grid)
Population census
Temporal
Resolution
Real time
Prefectures/
Cities
Each building/
person
Grid scale
(1km / 500m grid)
Spatial
Resolution
Web data
Residential map
Telephone
directory
them.
utilize MGD.

Residential map（Zmap-TOWNⅡ Zenrin Co., Ltd.）
You can monitor detailed building
information
・Buildings or residents names
・Number of stories
・Usage of building
・Tenants or residents information in all
floors or rooms
→It covers almost all areas of Japan.
19

20
Digital telephone directory
（Zenrin Co., Ltd. , NTT Business Information Service, Inc. etc.）
Telephone directory (text data)
Address
Point data with attributes of
telephone directory
We can develop point data
by the address geocoding
(address → longitude, latitude)
・Name ・Business
・Phone number
・Address etc
of each shops and offices

21
Yellow page (old)
Digital house map (old) Digital house map (new)
Yellow page (new)
Spatial integration
with digital house map
Spatio-temporal integration
(Based on location and name similarity)
Time-series digital map
Monitoring of time-series changes on buildings and tenants
Akiyama, Y., Shibasaki, R., 2012,"A Method for Identifying Japanese Shop and Company Names by Spatiotemporal Cleaning of
Eccentrically Located Frequently Appearing Words", Advances in Artificial Intelligence, Vol2012, Article ID 562604.

Integration of time-series data!
Tenant names
(in 2008) 22
Monitoring of time-series changes on buildings and tenants
Continuation
Change
Emergence
Demise
Legend
Time-series
changes
between 2003
and 2008

Time-series changes of all floors can be monitored
23
Monitoring of time-series changes on buildings and tenants;
3D mapping
Continuation
Change
Emergence
Demise
Legend
Time-series
changes
between 2003
and 2008

渋谷駅
Shibuya Sta.
渋谷駅
Shibuya Sta.
渋谷駅
Shibuya Sta.
24
Continuation
Change
Emergence
Demise
Legend
Time-series
changes
between 2003
and 2008
Utilization of attribute data

渋谷駅
Shibuya Sta.
渋谷駅
Shibuya Sta.
渋谷駅
Shibuya Sta.
Locations of McDonalds
(Based on tenant names in 2008)
Locations of new clothing shop opened between 2003-2008
(based on business categories and time-series changes)
25
Utilization of attribute data

渋谷駅
Shibuya Sta.
渋谷駅
Shibuya Sta.
渋谷駅
Shibuya Sta.
渋谷駅
Shibuya Sta.
山手線
Yamanote
line
渋谷駅
Shibuya Sta.
山手線
Yamanote
line
渋谷
Shibuya
原宿駅
Harajuku Sta.
代々木公園
Yoyogi park
表参道
Omote sando
原宿駅
Harajuku Sta.代々木公園
Yoyogi park
渋谷
Shibuya
明治神宮
Meiji Shrine
表参道
Omote sando
原宿駅
Yoyogi park
渋谷
Shibuya
明治神宮
Meiji Shrine
表参道
Omote sando
原宿駅
Harajuku Sta.
代々木公園
Yoyogi park
渋谷
Shibuya
明治神宮
Meiji Shrine
原宿駅
Yoyogi park
渋谷
Shibuya
明治神宮
Meiji Shrine
新宿御苑
Shinjuku Gyoen park
原宿駅
Yoyogi park
渋谷
Shibuya
明治神宮
Meiji Shrine
新宿御苑
Shinjuku Gyoen park
原宿駅
Yoyogi park
新宿
Shinjuku
明治神宮
Meiji Shrine
新宿御苑
Shinjuku Gyoen park
原宿駅
Harajuku Sta.
代々木公園
Yoyogi park
新宿
Shinjuku 新宿御苑
Shinjuku Gyoen park
原宿駅
Harajuku Sta.
代々木公園
Yoyogi park
新宿
Shinjuku
新宿御苑
Shinjuku Gyoen park
新宿
Shinjuku
新宿御苑
Shinjuku gyoen park
代々木公園
Yoyogi park
早稲田大学
Waseda Univ.
26
Data development in broad urban area
Continuation
Change
Emergence
Demise
Legend
Time-series
changes
between 2003
and 2008

Extremely detailed for macro scale monitoring…Make a grid map
Tenant changed rate
Percentage of the number of all
tenants in 2008 of the number of
changed tenants.
<Example>
Total number: 866
Changed tenants: 379
Changed rate = 379/866 = 0.4376
Evaluation index of briskness of
commercial activity
Changed
rate[%]
(2003-2008)
27

Extremely detailed for macro scale monitoring…
28
Changed
rate[%]
(2003-2008)

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Changed
rate[%]
(2003-2008)

Korea
D.P.R.Korea
Taiwan
China Russia
30
Changed
rate[%]
(2003-2008)

1 year
２ months
1 hour
5 years
People flow dataset
Commercial
Accumulation
Statistics
Micro Population
Census
Some census (grid)
Population census
Temporal
Resolution
Real time
Prefectures/
Cities
Each building/
person
Grid scale
(1km / 500m grid)
Spatial
Resolution
Web data
Residential map
Telephone
directory
them.
utilize MGD.

This data is developed based on the person trip survey and they are
interpolate spatio-temporaly using road and railroad network data.
People flow prohect
http://pflow.csis.u-tokyo.ac.jp/index-j.html
32
We can monitor distributions of persons
to stay or move (every 1 minute).
・Person attributes (age, sex etc)
・Methods of transport
・Aim of movement
→It covers many metropolitan areas of Japan
People flow dataset

1 year
２ months
1 hour
5 years
People flow dataset
Commercial
Accumulation
Statistics
Micro Population
Census
Some census (grid)
Population census
Temporal
Resolution
Real time
Prefectures/
Cities
Each building/
person
Grid scale
(1km / 500m grid)
Spatial
Resolution
Web data
Residential map
Telephone
directory
them.
utilize MGD.

34
Konzatsu Toukei
(Mobile census data; Zenrin data com Co., Ltd. ）
We can monitor estimate populations of every
hours by 250m square grids (updated everyday).
・Real time data based on GPS logs by mobile phones
・It covers throughout Japan.

1 year
２ months
1 hour
5 years
People flow dataset
Commercial
Accumulation
Statistics
Micro Population
Census
Some census (grid)
Population census
Temporal
Resolution
Real time
Prefectures/
Cities
Each building/
person
Grid scale
(1km / 500m grid)
Spatial
Resolution
Web data
Residential map
Telephone
directory
them.
utilize MGD.

36
Example of Web data;
Shop information (Hotpepper API)
We can collect detailed and fresh shop information.

37
Example of Web data; Usage of the twitter and flickr
Monitoring of urban activity by the Twitter and the Flickr
(Blue dots: twitter, orange: flickr, white: both )
Tokyo, Japan
Eric Fischer, “Eric Fischer’s photostream”,
http://www.flickr.com/photos/walkingsf/
New York, USA

Collection of business hour of each shops by analysis of search
results by search engines (City center of Fukuoka, Japan)
Okamoto,Y., Akiyama, Y., Ueyama, S., Shibasaki, R.,
2011, "Visualization of Business Hours for Shops
and Offices Classified by Business Categories in
Shopping Area" The 32nd Asian Conference on
Remote Sensing, CD-ROM（TS3-10）
38
Example of Web data;
Analysis of search result by search engine

1 year
２ months
1 hour
5 years
People flow dataset
Commercial
Accumulation
Statistics
Micro Population
Census
Some census (grid)
Population census
Temporal
Resolution
Real time
Prefectures/
Cities
Each building/
person
Grid scale
(1km / 500m grid)
Spatial
Resolution
Web data
Residential map
Telephone
directory
them.
utilize MGD.

40
Distributions of commercial statistics are not
monitored in detail because aggregated unit is
administrative unit.
Problems of current Commercial Statistics
Actual distribution of commercial areas can not be monitored
because aggregated units are administrative unit or grid.
Actual situations of accumulations by
shops and offices are ignored because
aggregated unit is grid.

41
In our study…
商業集積地域A
店舗数：201件
新設店舗：52件
コンビニ：8件
商業集積地域B
店舗数：73件
新設店舗：9件
コンビニ：3件
商業集積地域C
店舗数：182件
新設店舗：38件
コンビニ：6件
Aggregated unit is shapes of actual commercial areas.
=Commercial Accumulation Statistics
It was realized to process
digital telephone directory (= Micro geo data)

42
Development flow
Actual shop information by Web pages of
some commercial areas
Commercial Accumulation Statistics
＝Each 1 polygon means 1 commercial areas.
Digital telephone directory （Telepoint
Pack! Zenrin Co., Ltd. ）
Integration based on names and
locations (address and X,Y)
Data selection based on business categories
Development of buffer polygons from each point and
integration (merging)
Polygons which contain less than 10 shops are removed.
This data was developed and commercialized by the joint research
with private company (Zenrin Co., Ltd.).
Joint research
Adviser
Univ. Researchers
Private companies
Lend/Share (free)
Selling

43
Number of
shops
10~20
20~30
30~50
50~100
100~
Akiyama, Y., Sengoku, H.,Hiroyuki, T., Shibasaki, R., 2011,
"Development of Commercial Accumulation Polygon Data
Throughout Japan Based on the Digital Classified Telephone
Directory", CUPUM2011, F-TC-3(1)
Commercial Accumulation Statistics（Kobe city, Japan）
Locations and shapes of commercial accumulations are expressed by polygons.

Total number of
shops
Number of shops
in each business
categories
You can monitor numbers of shops of each business category in all commercial areas. 44
Number of
shops
10~20
20~30
30~50
50~100
100~

Green points are telephone directory. 45
Number of
shops
10~20
20~30
30~50
50~100
100~

46
Number of
shops
10~20
20~30
30~50
50~100
100~

商業集積統計（世田谷区東部）
Commercial Accumulation Statistics (2009, Throughout Japan)
47

商業集積統計（世田谷区東部）
Commercial areas around main stations (Tokyo)
48

2 データ開発
商業集積地域ポリゴンデータ（日本全土）Road side shops（Asahikawa city）
Hot spring（Kusatsu town）
Isolated island
（Nishinoomote city）
49

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異なる時点の商業集積を重ねることで商業地域の広がりの変化を把握
We can detect declining
shopping areas
Monitoring of changes of commercial area’s shapes to overlay multi-year data
Detection of declining shopping areas

Estimated number of visitors in each commercial areas
It is realized to integrate the Commercial Accumulation Statistics with the mobile census
data by ZDC in the city center of Tokyo. (365days in 2012) 51
Legend
Estimated number
of visitors
Akiyama, Y., Ueyama, S.,
Horanont, T., Sengoku, H., and
Shibasaki, R., 2013, "Spatio-
temporal Analyses of Visitors in
Commercial Accumulations Using
Mass People Flow Data in Kanto
Region", IGU2013 Kyoto Regional
Conference, JS104-3-1.

52
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
16,000
18,000
20,000
22,000
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Averagenumberofvisitorsinweekday
Times[hour]
浅草歌舞伎町原宿八重洲1丁目下北沢南口
Asakusa Kabuki-cho Harajuku Yaesu-1 Shimo-kitazawa
data by ZDC in the city center of Tokyo. (365days in 2012)
Estimated time-series number of visitors
in some commercial areas

53
Estimated time-series number of visitors
in some commercial areas
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
16,000
18,000
20,000
22,000
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Averagenumberofvisitorsinweekday
Times[hour]
浅草歌舞伎町原宿八重洲1丁目下北沢南口
Asakusa Kabuki-cho Harajuku Yaesu-1 Shimo-kitazawa
data by ZDC in the city center of Tokyo. (365days in 2012)

1 year
２ months
1 hour
5 years
People flow dataset
Commercial
Accumulation
Statistics
Micro Population
Census
Some census (grid)
Population census
Temporal
Resolution
Real time
Prefectures/
Cities
Each building/
person
Grid scale
(1km / 500m grid)
Spatial
Resolution
Web data
Residential map
Telephone
directory
them.
utilize MGD.

Recently, various census data are being digitalized and we can get
them easily from websites of national and local governments.
Especially, the population census is used as base data to understand
distribution and movement of population by many previous studies.
More detailed and reliable population data are required than
before for following urban problems.
Background
Urban
planning
Disaster damage
estimation and
prevention
Traffic
planning
Marketing
support
＞We aim to develop new population census which
can be accumulated into arbitrary spatial unit. 55

56
Micro population census
(Population census + residential map + housing statistics)
It was realized to disaggregate population census. (Disaggregate: data processing to
reallocate data statistically based on other statistics and spatial features.)
東松原駅
LEGEND
Households
1 person
3 persons
4 persons
5 persons
≧6 persons
2 persons
Akiyama, Y., Takada, T. and Shibasaki, R., 2013, "Development of
Micropopulation Census through Disaggregation of National
Population Census", CUPUM2013 conference papers, 110.

57
It was realized to disaggregate population census. (Disaggregate: data processing to
reallocate data statistically based on other statistics and spatial features.)
東松原駅
Attribute table
Building type house
Longitute 139.65633
Latitude 35.663664
Area[m2
] 105.34
Family type 8
Household size 5
Householder [age-gender] 45 - 1
Spouse [age - gender] 40 - 2
Number of child 2
Information of children 5-1 | 10 - 2
Number of parent 1
Information of parent 75-2
Number of others 0
Information of others None
LEGEND
Households
1 person
3 persons
4 persons
5 persons
≧6 persons
2 persons

58
LEGEND
Households
1 person
3 persons
4 persons
5 persons
≧6 persons
2 persons

59
LEGEND
Households
1 person
3 persons
4 persons
5 persons
≧6 persons
2 persons

LEGEND
Households
1 person
3 persons
4 persons
5 persons
≧6 persons
2 persons

LEGEND
Households
1 person
3 persons
4 persons
5 persons
≧6 persons
2 persons
The Important thing to understand this data
This data is estimated data.
Values of each point are necessarily match as actual states.

Aggregation by grid (250m square meter)

Aggregation by grid (250m square meter)
LEGEND
Population
0 - 250
501 - 1000
1001 - 2000
2001 -
251 - 500
Aim of the Micropopulation census
=Development the new population census which can be aggregated
into arbitrary spatial unit.

Aggregation by city blocks
LEGEND
Population
0 - 50
101 - 250
251 - 500
501 -
51 - 100

LEGEND
Aging rate
(Over 65 yrs. old)[%]
0 - 10
20 - 30
30 - 50
50 -
10 - 20
65
Monitoring of aging rate
(rate of population over 65years old in 250m square grid)

凡例
高齢化率
(65歳以上割合)[%]
0 - 10
20 - 30
30 - 50
50 -
10 - 20
66
LEGEND
Aging rate
(Over 65 yrs. old)[%]
0 - 10
20 - 30
30 - 50
50 -
10 - 20

67

Application of MGD for urban problems
Many available MGD
Building data Time-series data Person flow data Mobile census
Commercial
accumulation
Micro population Web information
Internet
Application for urban problems
Integration
Traffic
planning
Urban
planning
Disaster damage
estimation
Marketing
support

 Japanese government estimates that victims by Tokai-
Tonankai earthquakes are over 300 thousands.
 Calculation and estimation of micro-scale regional
disaster risks thorughout Japan is very important for
planning of earthquake disaster prevention in Japan.
Earthquake Disaster damage estimation by MGD
69
Y, Akiyama., Y, Ogawa., H, Sengoku., R, Shibasaki. And T, Kato., “Development of Micro Geo Data for Evaluation
of Disaster Risk and Readiness by Large-scale Earthquakes Throughout Japan”, Proceeding of Annual
conference on Infrastructure and Management, 2013, 392. (in Japanese)
Y, Ogawa., Y, Akiyama. and R, Shibasaki, “The Development of Method to Evaluate the damage of Earthquake
Disaster Considering Community-based Emergency Response Throughout Japan”, GI4DM2013, 2013, TS03-1.
Using various MGD and census data…
Estimation of earthquake disaster risk
(fire rate, collapse rate etc.) and death rate
of each building

Earthquake Disaster damage estimation by MGDEarthquake Disaster
damage estimation by MGD
(250m square grid)
Estimated death
rate [%]
In case of earthquake which will
occur 2% in 50years

Estimated death
rate [%]
occur 2% in 50years
Earthquake Disaster
damage estimation by MGD
(250m square grid)

Earthquake Disaster
damage estimation
by MGD
Estimated death
rate [%]
occur 2% in 50years

Earthquake Disaster damage estimation by MGD
This result received a lot of attention in Japan.
Medias (NHK) Magazines (GIS NEXT)
Research funds
(Ministry of Land, Infrastructure,
Transport and Tourism)

Revolution of GIS using MGD
Applicative studies which were difficult before are
being realized.
・Today is data “abundant” and “accumulating” era.
・Unrealizable studies (only ideas) can be realized by MGD.
Anyone can develop an environment to handle MGD.
・We can buy high spec PC and high-capacity HDD at low prices.
Our study can target multi-temporal broad areas with
any spatial units.
・Results can be accumulated by any spatial units.
・Results can cover all over the country in multi times.
81
Conclusions

82
Challenges
Development of human resources who can handle and
analyze MGD is needed.
・We need to acquire skills to handle and understand MGD.
> Programming skills to handle big data
> Skills to handle GIS software for visualization
> Knowledge of statistics to analyze results
Integration of MGD with field data
・We need to understand MGD is not universal data.
・To integrate MGD with field data, MGD will be used more than now.
> Skill and sense to integrate field data with MGD
Exploitation of MGD utilization field
・To popularize MGD researches, we need to work together with researchers
and experts in related fields.
Revolution of GIS by MGD

We established Micro Geo Data Forum in 2011. If you want
to know about Micro geo data and this forum in detail,
please visit our webpage.
http://geodata.csis.u-tokyo.ac.jp/
Micro Geo Data Forum
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There are many researches and publications
using MGD from our forum
From 2011…
Peer reviewed papers: 10 (Domestic: 6, International: 4)
Papers: over 50
Awards: 8 (GISA research encourage award, JSPRS award,
ACRS innovation award, etc.)
Magazines: GIS NEXT(15 times), Regional development etc.
Medias: NHK Special “Disaster big data file3.” (Mar. 2, 2014)
Magazines
Medias Awards

Mobmap; MGD visualization and analysis software
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This is the GIS application on Google chrome. A member of our forum is
developing now (Mr. Ueyama, Researcher of CSIS, The Univ. of Tokyo).
http://shiba.iis.u-tokyo.ac.jp/member/ueyama/mm/

Thank you for your kind attention
<Contact>
Yuki Akiyama（aki@iis.u-tokyo.ac.jp）
Assistant professor
Earth Observation Integration and
Fusion Research Institute (EDITORIA)
The University of Tokyo
URL: http://shiba.iis.u-tokyo.ac.jp/member/akiyama/
（You can download some my papers and slides)
Web page of Micro Geo Data Forum
http://geodata.csis.u-tokyo.ac.jp/wp/
Search「秋山祐樹」or” akiyama.yuuki”!
끝까지 경청해 주셔서 감사합니다.

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