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DATEㅣ2017.10. 15
Junyoung Choi, Ph.D. in urban planning & GIS
Spatial Big Data Team at MOLIT
Spatial Information Office, LH
Charter Member, OSGeo
Spatial Big Data Strategy for
UN Habitat Smart Safer City
Presention is about my personal opinion and is
not related to UN Habitat’s official direction
October 5, 2015, Open Source GIS for Rapid Urban Growth and Land Management, UN-GGIM-AP,
UN-ESCAP, UN-HABITAT/GLTN Joint Workshop on Land Administration and Management, Jeju,
South Korea.
September 16, 2015, FOSS4G for Rapidly Urbanizing Cities and UN Sustainable Development
Goals(SDGs); SDG 11 Cities and Human Settlement, LH-OSGeo Joint Conference on the Open Source for
UN and Developing Countries, FOSS4G Seoul 2015, Seoul, South Korea.
August 24, 2106, Achieving Urban SDG and New Urban Agenda using the Open Geospatial Data of the
International Organizations, FOSS4G Bonn 2016, Bonn, Germany.
March, 2016, Supporting the measurement of the United Nations’ sustainable development goal 11
through the use of national urban information systems and open geospatial technologies: a case study of
south Korea, Open Geospatial Data, Software and Standards 1(4).
October, 2016, What drives developing countries to select free open source software for national
spatial data infrastructure?, Spatial Information Research 24(5), pp 545–553.
My presentations on Global Urban Goals & FOSS4G*
*FOSS4G: Free Open Source Software for Geospatial
FOSS4G-ASIA 2017
January, 2017, FOSS4G for Global Urban Goals and K-Smart City, FOSS4G ASIA 2017, Hyderabad,
India.
September,2017, Spatial BigData Strategy forCityLab onSmart Safer City, UN HABITATUrbanThinkersCampusSeoul:HowSmart
TechnologyMakesCitiesSafer?, Seoul,Korea
November 15, 2017, Outstanding : One panel discussion and one presentation, “Security, Democracy
and Cities: Coproducing Urban Security Policies” organized by European Forum for Urban Safety(EFUS),
Barcelona, Spain.
1 l UN HABITAT Safer City
2 l Spatial Big Data Strategy for Safer City
3 l Case study : Safe Route for Chungju City
Contents
4 l How Smart Technology Makes Cities Safer?
#1
UN Habitat Safer City
Manifestations of Urban Crime
• The fortification of cities through the “architecture
of fear” and the rapid expansion of surveillance a
nd walled cities are all testament to the shared h
eritage of urbanization and security.
• Crime is impacting more on the urban poor (who liv
e largely in unplanned settlements) – contrary to c
ommon perceptions.
Photo Credit: UN Habitat(2017)
Photo Credit: UN Habitat(2017)
UN support – The Safer Cities Programme
In 1996 UN-HABITAT established a ‘urban crime prevention programme’ t
o assist cities to develop crime prevention initiatives and thereby reduc
e incidence and impact of crime and violence in cities.
The Programme operates through:
– Direct support to cities that intend to formulate and implement crime
prevention strategies
– Support to networking and city-to-city collaboration
– Development and dissemination of tools
– Advocacy and policy development on crime prevention issues - gen
der, youth-at-risk, role of local government
Photo Credit: UN Habitat(2017)
Three pillars of prevention
SOCIAL PREVENTION
Youth and Women
Youth empowerment
Victim support
Recreational facilities to
occupy youth
Developing victim support
LAW ENFORCEMENT
AND CJS REFORM
Targeted visible police patrols
Conflict resolution
Neighborhood watch
By-law enforcement
Improve relationships and
accessibility
URBAN DESIGN
Supporting street layout
Improving street lighting
Designing streets, buildings, parks
etc. to reduce opportunities for
crime
Reorganize markets or terminals
Photo Credit: UN Habitat(2017)
Towards Human Settlement Vulnerability Reduction
Security of
Tenure
Targeting land and
housing
evictions and
associated
violent conflicts
Natural
Disasters
Targeting risk
reduction,
preparedness
and resilience
Crime, Violence
& Social
Cohesion
* Targeting urban
vulnerability
reduction
to crime and
violence
* Building on
social capital of
communities
* Focusing on
social
interventions
Photo Credit: UN Habitat(2017)
Safer Cities Process
Key Elements for Effective Implementation
A COALITION
• with leadership
• assembling all key partners
• sensitive to age, gender &
cultural differences
• supported by a secretariat
• engaging citizens
• a communication strategy
A security diagnosis
• challenges
• risk factors
• community resources
A strategy and action plan
• establish priorities
• identify model for practices
• target actions on risk factors
• balance short & long
term actions
Implementation
• training
• co-ordination of partners
• actions
Evaluation
& Feedback
• process evaluation
• impact evaluation
• tools development
Regional and (inter)
national networks fo
r exchange and repli
cation
Photo Credit: UN Habitat(2017)
Safer City 2.0
Photo Credit: UN Habitat(2017)
Overview of CityLab as Pilot Action Site
Knowledge
City Lab will connect cities to new and inspiring sources
of knowledge that can be adapted to the local contexts
to inform more effective policy responses as well as pra
ctice.
Learning
Providing learning opportunities for the urban practitio
ner - using existing context specific practices; action-lea
rning seminars; city to city learning through structured
exchange visits and other means.
Supporting
Innovation
Testing innovative approaches in cities in a range of are
as and validate their applicability.
Facilitating
Solutions
Provider of high quality technical expertise and facilitato
r of change within cities . Drawing on partner networks
and network cities– arranging and sequencing support a
nd processes to provide a sustainable solution.
Safer Cities in
Sutainable Dev. Goal(SDG)
Source: https://unhabitat.org/wp-content/uploads/2016/02/SDG-Goal%2011%20Monitoring%20Framework%2025-02-16.pdf
11.7.1 The average share of the built-up area of
cities that is open space in public use for all
disaggregated by age group, sex and persons with
disabilities
11.7.2 Proportion of women subjected to physical or
sexual harassment by perpetrator and place of
occurrence (last 12 months)
• Need to disaggregated indicators
• Defining urban and city
• Working with spatial indicators and data
Safer Cities in
New Urban Agenda(NUA)
100. Supporting the provision of
well-designed networks of safe,
accessible, green and quality streets
and other public spaces &
103. Integrating inclusive measures
for urban safety and the prevention
of crime and violence
Source: https://unhabitat.org/wp-content/uploads/2016/02/SDG-Goal%2011%20Monitoring%20Framework%2025-02-16.pdf
Supporting the monitoring of safe city in the
measuring the indicators of SDG and NUA
by international org. and central gov.
#2
Spatial Big Data Strategy for
Safer City
What is Spatial Big Data
ㆍRoad
ㆍParcel
ㆍZoning
ㆍDEM
ㆍ3 dimensional
ㆍFloating pop.
ㆍCredit card
ㆍDocuments
ㆍLand transaction
ㆍTraffic
•Road/Building/Stream/Parcel/Zoning…
•Flooded area, Susceptible coastal flood, Land slide…
•DEM, Aerial photo, R.S., 3 dimensional data…
Spatial data
(Vector/Raster)
•SNS, Blog, News…
•Floating pop./Credit card…
•Photos/Movies…
Big Data
(Private)
•Document issuance of land regulation etc.
•Land transaction/Rental housing contract…
•Traffic/Transportation…
•Geosensor, CCTV…
Big Data
(Public)
Clickstream/Query word
Joining
Geocodin
g
•
•
•
•
•
•
Geo-
parsing
Parcel
Administrative bnd.
POI
Over 80% of Big Data is also
geographically referenced! Source: Kim, D.J.(2014)”Geospatial Big Data for Gov. 3.0”
What is Spatial Big Data
Prompt/accurate/precise diagnosis 
Customized/effective prescription
Simul-
ation
Spatial
analytics
Visuali-
zation
Diagnosis Alternatives Implementation Evaluation
ㆍRoad
ㆍParcel
ㆍZoning
ㆍDEM
ㆍ3 dimensional
ㆍFloating pop.
ㆍCredit card
ㆍTraffic
ㆍDocuments
ㆍLand transaction
•
•
•
•
•
•
Environment
Physical & logical
Behavior
Planning
Opinion
Source: Kim, D.J.(2014)”Geospatial Big Data for Gov. 3.0”
Spatial Big Data Platform
…
[Population] [Permits] [Registries]
Big Data(MOSPA)
Private
[Credit card, Floating pop…]
[Road]
… [Building] [3D image]
…
NSDI Spatial Big Data(MOLIT)
Public
ㆍLand trans. / Document issuance
ㆍLand reg. / Rental contract
ㆍTraffic accident / Traffic volume
ㆍTravelling etc.
BD in public
ㆍFloating pop.
ㆍLand transaction
ㆍRental contract
ㆍDocuments
ㆍTraffic
ㆍCredit card
Hadoop Spatial Hadoop
ㆍSNS, Blog, Cafe...
ㆍVGI
BD in private
Parcel map
Administrative
POI
Joining
Geocoding
Geoparsing
& Geocoding
Fusion
Source: Kim, D.J.(2014)”Geospatial Big Data for Gov. 3.0”
Smart + Safer City
A COALITION
• Social Media
• Cloud Computing
• FOSS
(Free Open Source Software)
A security diagnosis
-Big Data
-Social Media
-Crowdsourcing
-Open Data
A strategy and action plan
- Big data
- GIS data
- Lidar, BIM(3D data)
Implementation
• Sensors
• CCTV
• IoT
• Drone, 3D printing
Evaluation
& Feedback
• Social Media
• Big Data
• Drone
Regional and (inter)
national networks
for exchange and
replication
1st step: Adopting smart technology to the Safer City
Photo Credit: JY. Choi(2016) Smart City Lounge, Jakarta, Indonesia
Smart + Safer City
2nd step: Identifying and collaborating with Stakeholders
Research
InstitutionLocal &
central gov.
Police
Office
NPO
IT
company
A COALITION
A security
diagnosis
A strategy and
action plan
Implementation
Evaluation
& Feedback
Regional &
international
Networks for
exchange &
replication
Citylab on Smart Safer City
Knowledge
When applying a smart safer city knowledge, it is needed
to consider the technological infrastructure and maturity
of society’s adoption of smart technology
Learning
Focus more on bridging digital divide and raise smart citi
zen who will be familiar with smart technology and lead
the smart technology based practices
Supporting
Innovation
Testing smart technologies inside Smart Safer City throug
h the living lab approach by participating citizens to appli
cation processes of Smart Safer City solutions
Facilitating
Solutions
Collaboration with open source and standardization orga
nizations to lower adoption and maintenance cost and al
leviate the technological barriers
Applying spatial big data to
the three pillars of safer city
Source: Safer Cities City Changer Toolkit(www.worldurbancampaign.org)
Time-series
analysis to
evaluate the
practice
Identifying
groups at risk
when analyzing
Spatial analysis
using big data
#3
Case Study: Safe Route for
Chungju City
Crime status in Chungju
from 2014 to 2016
Security
Diagnosis
A Strategy &
Action Plan
Implementation
Evaluation &
Feedback
# of crime
Security
Diagnosis
A Strategy &
Action Plan
Implementation
Evaluation &
Feedback
Crime status in Chungju
from 2014 to 2016
# of crime
In night
time
# of crime
in day
time
Security
Diagnosis
A Strategy &
Action Plan
Implementation
Evaluation &
Feedback
1631
368 352
27 44 3
요약
범죄발생 현황
폭력
청소년비행
절도
성폭력
변사자
강도
Violence
Violence
Juvenile delinquency
Sexual assault
Murder
Robbery
Robbery
Juvenile
delinquency
Theft
Sexual assault
Murder
Crime occurence
Crime status in Chungju
from 2014 to 2016
Theft
A Strategy &
Action Plan
Security
Diagnosis
Implementation
Evaluation &
Feedback
Night time crime occurrence
Facilities vulnerable to crime at night
Facilities related to enhance safety
Population by mobile phone
Crime risk index along the pedestrian network
Ranking
(Vulnerable)
Administrative
boundary
District Ration
1st 성내·충인동 15 구역 22.4%
12th 호암·직동 0 구역 0%
Crime Risk Index Framework
A Strategy &
Action Plan
Security
Diagnosis
Implementation
Evaluation &
Feedback
Crime Risk Index Framework
• Gaussian Kernel Density using
population of night time
• Gaussian Kernel Density using
crime occurrence of night time
A Strategy &
Action Plan
Security
Diagnosis
Implementation
Evaluation &
Feedback
Crime Risk Index Framework
Indoor parking
Vacant house
Entertainment venue
One-room
A Strategy &
Action Plan
Security
Diagnosis
Implementation
Evaluation &
Feedback
Crime Risk Index Framework
Bus stop
CCTV
Streetlight
Streetlight with CCTV
Implementation
A Strategy &
Action Plan
Security
Diagnosis
Evaluation &
Feedback
Safe Route Analysis
Implementation
A Strategy &
Action Plan
Security
Diagnosis
Evaluation &
Feedback
Safe Route Analysis
Comparison of index and crime
Evaluation &
Feedback
A Strategy &
Action Plan
Implementation
Security
Diagnosis
Comparison of index and CCTV
Evaluation &
Feedback
A Strategy &
Action Plan
Implementation
Security
Diagnosis
Comparison using Community mapping
Evaluation &
Feedback
A Strategy &
Action Plan
Implementation
Security
Diagnosis
Application of the index
Evaluation &
Feedback
A Strategy &
Action Plan
Implementation
Security
Diagnosis
#4
How Smart Technology Make
Cites Safer
Future directions
Relationship
with SDG
Achieving SDG through Smart Safer City program need to
have a close relationship with SDG goals. Therefore, Sma
rt Safer Citylab activities should support the achieving th
e goals.
Analysis
framework
To perform a spatial big data analysis, there have to be a
analysis framework which contains standardized indicato
rs and models
Identify vulne
rable class
Vulnerable classes such as woman, youth, elder have to
be considered when finding a result using mobile phone
data
Acquisition of
data
The most important thing is an acquisition of data. Befor
e applying this method, related data have to be collected
beforehand.
Future directions
Smart City Evaluation System (FOSS4G based)
Smart Safer City Award
Evaluation
Framework
City Prosperity Index
(CPI)
Smart City
Readiness Index
Data
base
Urban Open Data Portal
(urbandata.unhabitat.org)
Proposed cities’ database
Future directions
• World Urban Forum 9
- 7~13 February, 2018, Kuala Lumpur
- http://wuf9.org/
• European Forum for Urban Safety
- 15~17, November, 2017, Barcelona
- http://efusconference2017.eu/
Thank you
Spatial Big Data Center
Ministry of Land, Infrastructure and Transportation(MOLIT)
Junyoung Choi (Ph.D in Urban Planning & GIS)
novacite@gmail.com, junyoung@lh.or.kr
Spatial Information Office
Korea Land and Housing corp.

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SBD strategy for UN Habitat Smart Safer City171015

  • 1. DATEㅣ2017.10. 15 Junyoung Choi, Ph.D. in urban planning & GIS Spatial Big Data Team at MOLIT Spatial Information Office, LH Charter Member, OSGeo Spatial Big Data Strategy for UN Habitat Smart Safer City Presention is about my personal opinion and is not related to UN Habitat’s official direction
  • 2. October 5, 2015, Open Source GIS for Rapid Urban Growth and Land Management, UN-GGIM-AP, UN-ESCAP, UN-HABITAT/GLTN Joint Workshop on Land Administration and Management, Jeju, South Korea. September 16, 2015, FOSS4G for Rapidly Urbanizing Cities and UN Sustainable Development Goals(SDGs); SDG 11 Cities and Human Settlement, LH-OSGeo Joint Conference on the Open Source for UN and Developing Countries, FOSS4G Seoul 2015, Seoul, South Korea. August 24, 2106, Achieving Urban SDG and New Urban Agenda using the Open Geospatial Data of the International Organizations, FOSS4G Bonn 2016, Bonn, Germany. March, 2016, Supporting the measurement of the United Nations’ sustainable development goal 11 through the use of national urban information systems and open geospatial technologies: a case study of south Korea, Open Geospatial Data, Software and Standards 1(4). October, 2016, What drives developing countries to select free open source software for national spatial data infrastructure?, Spatial Information Research 24(5), pp 545–553. My presentations on Global Urban Goals & FOSS4G* *FOSS4G: Free Open Source Software for Geospatial FOSS4G-ASIA 2017 January, 2017, FOSS4G for Global Urban Goals and K-Smart City, FOSS4G ASIA 2017, Hyderabad, India. September,2017, Spatial BigData Strategy forCityLab onSmart Safer City, UN HABITATUrbanThinkersCampusSeoul:HowSmart TechnologyMakesCitiesSafer?, Seoul,Korea November 15, 2017, Outstanding : One panel discussion and one presentation, “Security, Democracy and Cities: Coproducing Urban Security Policies” organized by European Forum for Urban Safety(EFUS), Barcelona, Spain.
  • 3. 1 l UN HABITAT Safer City 2 l Spatial Big Data Strategy for Safer City 3 l Case study : Safe Route for Chungju City Contents 4 l How Smart Technology Makes Cities Safer?
  • 5. Manifestations of Urban Crime • The fortification of cities through the “architecture of fear” and the rapid expansion of surveillance a nd walled cities are all testament to the shared h eritage of urbanization and security. • Crime is impacting more on the urban poor (who liv e largely in unplanned settlements) – contrary to c ommon perceptions. Photo Credit: UN Habitat(2017)
  • 6. Photo Credit: UN Habitat(2017) UN support – The Safer Cities Programme In 1996 UN-HABITAT established a ‘urban crime prevention programme’ t o assist cities to develop crime prevention initiatives and thereby reduc e incidence and impact of crime and violence in cities. The Programme operates through: – Direct support to cities that intend to formulate and implement crime prevention strategies – Support to networking and city-to-city collaboration – Development and dissemination of tools – Advocacy and policy development on crime prevention issues - gen der, youth-at-risk, role of local government
  • 7. Photo Credit: UN Habitat(2017) Three pillars of prevention SOCIAL PREVENTION Youth and Women Youth empowerment Victim support Recreational facilities to occupy youth Developing victim support LAW ENFORCEMENT AND CJS REFORM Targeted visible police patrols Conflict resolution Neighborhood watch By-law enforcement Improve relationships and accessibility URBAN DESIGN Supporting street layout Improving street lighting Designing streets, buildings, parks etc. to reduce opportunities for crime Reorganize markets or terminals
  • 8. Photo Credit: UN Habitat(2017) Towards Human Settlement Vulnerability Reduction Security of Tenure Targeting land and housing evictions and associated violent conflicts Natural Disasters Targeting risk reduction, preparedness and resilience Crime, Violence & Social Cohesion * Targeting urban vulnerability reduction to crime and violence * Building on social capital of communities * Focusing on social interventions
  • 9. Photo Credit: UN Habitat(2017) Safer Cities Process Key Elements for Effective Implementation A COALITION • with leadership • assembling all key partners • sensitive to age, gender & cultural differences • supported by a secretariat • engaging citizens • a communication strategy A security diagnosis • challenges • risk factors • community resources A strategy and action plan • establish priorities • identify model for practices • target actions on risk factors • balance short & long term actions Implementation • training • co-ordination of partners • actions Evaluation & Feedback • process evaluation • impact evaluation • tools development Regional and (inter) national networks fo r exchange and repli cation
  • 10. Photo Credit: UN Habitat(2017) Safer City 2.0
  • 11. Photo Credit: UN Habitat(2017) Overview of CityLab as Pilot Action Site Knowledge City Lab will connect cities to new and inspiring sources of knowledge that can be adapted to the local contexts to inform more effective policy responses as well as pra ctice. Learning Providing learning opportunities for the urban practitio ner - using existing context specific practices; action-lea rning seminars; city to city learning through structured exchange visits and other means. Supporting Innovation Testing innovative approaches in cities in a range of are as and validate their applicability. Facilitating Solutions Provider of high quality technical expertise and facilitato r of change within cities . Drawing on partner networks and network cities– arranging and sequencing support a nd processes to provide a sustainable solution.
  • 12. Safer Cities in Sutainable Dev. Goal(SDG) Source: https://unhabitat.org/wp-content/uploads/2016/02/SDG-Goal%2011%20Monitoring%20Framework%2025-02-16.pdf 11.7.1 The average share of the built-up area of cities that is open space in public use for all disaggregated by age group, sex and persons with disabilities 11.7.2 Proportion of women subjected to physical or sexual harassment by perpetrator and place of occurrence (last 12 months) • Need to disaggregated indicators • Defining urban and city • Working with spatial indicators and data
  • 13. Safer Cities in New Urban Agenda(NUA) 100. Supporting the provision of well-designed networks of safe, accessible, green and quality streets and other public spaces & 103. Integrating inclusive measures for urban safety and the prevention of crime and violence Source: https://unhabitat.org/wp-content/uploads/2016/02/SDG-Goal%2011%20Monitoring%20Framework%2025-02-16.pdf Supporting the monitoring of safe city in the measuring the indicators of SDG and NUA by international org. and central gov.
  • 14. #2 Spatial Big Data Strategy for Safer City
  • 15. What is Spatial Big Data ㆍRoad ㆍParcel ㆍZoning ㆍDEM ㆍ3 dimensional ㆍFloating pop. ㆍCredit card ㆍDocuments ㆍLand transaction ㆍTraffic •Road/Building/Stream/Parcel/Zoning… •Flooded area, Susceptible coastal flood, Land slide… •DEM, Aerial photo, R.S., 3 dimensional data… Spatial data (Vector/Raster) •SNS, Blog, News… •Floating pop./Credit card… •Photos/Movies… Big Data (Private) •Document issuance of land regulation etc. •Land transaction/Rental housing contract… •Traffic/Transportation… •Geosensor, CCTV… Big Data (Public) Clickstream/Query word Joining Geocodin g • • • • • • Geo- parsing Parcel Administrative bnd. POI Over 80% of Big Data is also geographically referenced! Source: Kim, D.J.(2014)”Geospatial Big Data for Gov. 3.0”
  • 16. What is Spatial Big Data Prompt/accurate/precise diagnosis  Customized/effective prescription Simul- ation Spatial analytics Visuali- zation Diagnosis Alternatives Implementation Evaluation ㆍRoad ㆍParcel ㆍZoning ㆍDEM ㆍ3 dimensional ㆍFloating pop. ㆍCredit card ㆍTraffic ㆍDocuments ㆍLand transaction • • • • • • Environment Physical & logical Behavior Planning Opinion Source: Kim, D.J.(2014)”Geospatial Big Data for Gov. 3.0”
  • 17. Spatial Big Data Platform … [Population] [Permits] [Registries] Big Data(MOSPA) Private [Credit card, Floating pop…] [Road] … [Building] [3D image] … NSDI Spatial Big Data(MOLIT) Public ㆍLand trans. / Document issuance ㆍLand reg. / Rental contract ㆍTraffic accident / Traffic volume ㆍTravelling etc. BD in public ㆍFloating pop. ㆍLand transaction ㆍRental contract ㆍDocuments ㆍTraffic ㆍCredit card Hadoop Spatial Hadoop ㆍSNS, Blog, Cafe... ㆍVGI BD in private Parcel map Administrative POI Joining Geocoding Geoparsing & Geocoding Fusion Source: Kim, D.J.(2014)”Geospatial Big Data for Gov. 3.0”
  • 18. Smart + Safer City A COALITION • Social Media • Cloud Computing • FOSS (Free Open Source Software) A security diagnosis -Big Data -Social Media -Crowdsourcing -Open Data A strategy and action plan - Big data - GIS data - Lidar, BIM(3D data) Implementation • Sensors • CCTV • IoT • Drone, 3D printing Evaluation & Feedback • Social Media • Big Data • Drone Regional and (inter) national networks for exchange and replication 1st step: Adopting smart technology to the Safer City Photo Credit: JY. Choi(2016) Smart City Lounge, Jakarta, Indonesia
  • 19. Smart + Safer City 2nd step: Identifying and collaborating with Stakeholders Research InstitutionLocal & central gov. Police Office NPO IT company A COALITION A security diagnosis A strategy and action plan Implementation Evaluation & Feedback Regional & international Networks for exchange & replication
  • 20. Citylab on Smart Safer City Knowledge When applying a smart safer city knowledge, it is needed to consider the technological infrastructure and maturity of society’s adoption of smart technology Learning Focus more on bridging digital divide and raise smart citi zen who will be familiar with smart technology and lead the smart technology based practices Supporting Innovation Testing smart technologies inside Smart Safer City throug h the living lab approach by participating citizens to appli cation processes of Smart Safer City solutions Facilitating Solutions Collaboration with open source and standardization orga nizations to lower adoption and maintenance cost and al leviate the technological barriers
  • 21. Applying spatial big data to the three pillars of safer city Source: Safer Cities City Changer Toolkit(www.worldurbancampaign.org) Time-series analysis to evaluate the practice Identifying groups at risk when analyzing Spatial analysis using big data
  • 22. #3 Case Study: Safe Route for Chungju City
  • 23. Crime status in Chungju from 2014 to 2016 Security Diagnosis A Strategy & Action Plan Implementation Evaluation & Feedback # of crime
  • 24. Security Diagnosis A Strategy & Action Plan Implementation Evaluation & Feedback Crime status in Chungju from 2014 to 2016 # of crime In night time # of crime in day time
  • 25. Security Diagnosis A Strategy & Action Plan Implementation Evaluation & Feedback 1631 368 352 27 44 3 요약 범죄발생 현황 폭력 청소년비행 절도 성폭력 변사자 강도 Violence Violence Juvenile delinquency Sexual assault Murder Robbery Robbery Juvenile delinquency Theft Sexual assault Murder Crime occurence Crime status in Chungju from 2014 to 2016 Theft
  • 26. A Strategy & Action Plan Security Diagnosis Implementation Evaluation & Feedback Night time crime occurrence Facilities vulnerable to crime at night Facilities related to enhance safety Population by mobile phone Crime risk index along the pedestrian network Ranking (Vulnerable) Administrative boundary District Ration 1st 성내·충인동 15 구역 22.4% 12th 호암·직동 0 구역 0% Crime Risk Index Framework
  • 27. A Strategy & Action Plan Security Diagnosis Implementation Evaluation & Feedback Crime Risk Index Framework • Gaussian Kernel Density using population of night time • Gaussian Kernel Density using crime occurrence of night time
  • 28. A Strategy & Action Plan Security Diagnosis Implementation Evaluation & Feedback Crime Risk Index Framework Indoor parking Vacant house Entertainment venue One-room
  • 29. A Strategy & Action Plan Security Diagnosis Implementation Evaluation & Feedback Crime Risk Index Framework Bus stop CCTV Streetlight Streetlight with CCTV
  • 30. Implementation A Strategy & Action Plan Security Diagnosis Evaluation & Feedback Safe Route Analysis
  • 31. Implementation A Strategy & Action Plan Security Diagnosis Evaluation & Feedback Safe Route Analysis
  • 32. Comparison of index and crime Evaluation & Feedback A Strategy & Action Plan Implementation Security Diagnosis
  • 33. Comparison of index and CCTV Evaluation & Feedback A Strategy & Action Plan Implementation Security Diagnosis
  • 34. Comparison using Community mapping Evaluation & Feedback A Strategy & Action Plan Implementation Security Diagnosis
  • 35. Application of the index Evaluation & Feedback A Strategy & Action Plan Implementation Security Diagnosis
  • 36. #4 How Smart Technology Make Cites Safer
  • 37. Future directions Relationship with SDG Achieving SDG through Smart Safer City program need to have a close relationship with SDG goals. Therefore, Sma rt Safer Citylab activities should support the achieving th e goals. Analysis framework To perform a spatial big data analysis, there have to be a analysis framework which contains standardized indicato rs and models Identify vulne rable class Vulnerable classes such as woman, youth, elder have to be considered when finding a result using mobile phone data Acquisition of data The most important thing is an acquisition of data. Befor e applying this method, related data have to be collected beforehand.
  • 38. Future directions Smart City Evaluation System (FOSS4G based) Smart Safer City Award Evaluation Framework City Prosperity Index (CPI) Smart City Readiness Index Data base Urban Open Data Portal (urbandata.unhabitat.org) Proposed cities’ database
  • 39. Future directions • World Urban Forum 9 - 7~13 February, 2018, Kuala Lumpur - http://wuf9.org/ • European Forum for Urban Safety - 15~17, November, 2017, Barcelona - http://efusconference2017.eu/
  • 40. Thank you Spatial Big Data Center Ministry of Land, Infrastructure and Transportation(MOLIT) Junyoung Choi (Ph.D in Urban Planning & GIS) novacite@gmail.com, junyoung@lh.or.kr Spatial Information Office Korea Land and Housing corp.

Editor's Notes

  1. My name is Junyoung Choi and I will present about the monitoring the global development goal and FOSS4G. Title is a “Urban SDG Monitoring System using the Open Geospatial Data of the International Organizations.
  2. My presentation is consists of four sections. In section 1 and 2, we’re gonna explain the scope, characteristics and role of FOSS4G. In the last two sections, we will introduce conceptual diagram of UN SDG monitoring systems and examples of implementation.
  3. My presentation is consists of four sections. In section 1 and 2, we’re gonna explain the scope, characteristics and role of FOSS4G. In the last two sections, we will introduce conceptual diagram of UN SDG monitoring systems and examples of implementation.
  4. Thank you for listening my presentation. 제 프리젠테이션을 들어주신데 감사드립니다.