THE STUDY OF PEDESTRIAN PLAZA’S INFLUENCE
ON CRIME RATES IN NEW YORK CITY, USING
GEOSPATIAL DATA AND FOCUSING ON LOCATION
AND SEASONAL VARIATIONS
Eva Thiel
Dissertation submitted in partial fulfilment of the requirements for the degree of MSc in Crime and Forensic
Science (UCL) of the University of London in 2019.
UNIVERSITY COLLEGE LONDON
UCL DEPARTMENT OF SECURITY AND CRIME SCIENCE
This Dissertation is an unrevised examination copy for consultation only and it should not be quoted or cited
without the permission of the Chairman of the Board of
Examiners of the MSc in Crime and Forensic Science (UCL)
, University College London
Department of Security and Crime Science
MSc and MRes Dissertations
SUPERVISOR’S DECLARATION
Name of student: Eva Thiel
Name of (primary) supervisor: Dr Matt Ashby
I confirm that the student named above has undertaken this dissertation under my supervision, attended
meetings with me as requested and provided me with adequate information about the progress of the research.
Supervisor’s signature: Matt Ashby
Date: 30/08/19
2
, University College London
Department of Security and Crime Science
MSc and MRes Dissertations
STUDENT’S DECLARATION
I, Eva Thiel, hereby declare that this dissertation is my own original work and that I have clearly identified
and acknowledged all source material used. No part of this dissertation contains material previously submitted
to the examiners of this or any other university, or any material previously submitted for any other
examination.
This dissertation is 9079 words in length (including abstract but excluding reference list and reasonable use of
tables and figures).
Student’s signature: Eva Thiel
Date: 30/08/19
Student name: Eva Thiel
Supervisor name: Matt Ashby
Title of proposed project: The Study of Pedestrian Plaza’s Influence on Crime Rates in New York
City, using Geospatial Data and Focusing on Location and Seasonal variations.
3
, LONDON’S GLOBAL UNIVERSITY
Upon review of the materials that you provided, the Department of Security and Crime Science Ethics
Committee has decided that your proposed research is exempt from requiring approval by the UCL
Research Ethics Committee. This is because the proposed research either:
- does not involve human participants and/or does not involve the collection and/or use of data
derived from human individuals, or
- corresponds to one or more of the following UCL exemption criteria
(https://ethics.grad.ucl.ac.uk/exemptions.php):
Ethics exemption
1. Research involving information freely available in the public domain. For example, published biographies,
newspaper accounts of an individual's activities and published minutes of a meeting, whilst still personal data
under the Data Protection Act would not require ethics review.
2. Research involving anonymised records and data sets that exist in the public domain. For example, datasets
available through the Office for National Statistics or the UK Data Archive where appropriate permissions have
already been obtained and it is not possible to identify individuals from the information provided.
3. Studies of public behaviour that are purely observational (non-invasive and non-interactive), unless the recorded
observations identify individuals (names, photographs) which could place them at risk of harm, stigma or
prosecution.
4. Research involving the use of non-sensitive, completely anonymous educational tests, survey and interview
procedures when the participants are not defined as "vulnerable" and participation will not induce undue
psychological stress or anxiety.
5. Research involving the use of educational tests, survey and interview procedures on human participants in the
public arena (e.g. elected or appointed public officials, candidates for public office, artists).
Should your project substantially change from what you have proposed, you will need to go
through the ethics process again.
Signed: Dated: July 30, 2019
Dr Georgina Meakin
Chair, Departmental Ethics Committee
Department of Security and Crime Science
University College London
University College London, Gower Street, London WC1E 6BT
Tel: +44 (0)20 7679 2000
4
ON CRIME RATES IN NEW YORK CITY, USING
GEOSPATIAL DATA AND FOCUSING ON LOCATION
AND SEASONAL VARIATIONS
Eva Thiel
Dissertation submitted in partial fulfilment of the requirements for the degree of MSc in Crime and Forensic
Science (UCL) of the University of London in 2019.
UNIVERSITY COLLEGE LONDON
UCL DEPARTMENT OF SECURITY AND CRIME SCIENCE
This Dissertation is an unrevised examination copy for consultation only and it should not be quoted or cited
without the permission of the Chairman of the Board of
Examiners of the MSc in Crime and Forensic Science (UCL)
, University College London
Department of Security and Crime Science
MSc and MRes Dissertations
SUPERVISOR’S DECLARATION
Name of student: Eva Thiel
Name of (primary) supervisor: Dr Matt Ashby
I confirm that the student named above has undertaken this dissertation under my supervision, attended
meetings with me as requested and provided me with adequate information about the progress of the research.
Supervisor’s signature: Matt Ashby
Date: 30/08/19
2
, University College London
Department of Security and Crime Science
MSc and MRes Dissertations
STUDENT’S DECLARATION
I, Eva Thiel, hereby declare that this dissertation is my own original work and that I have clearly identified
and acknowledged all source material used. No part of this dissertation contains material previously submitted
to the examiners of this or any other university, or any material previously submitted for any other
examination.
This dissertation is 9079 words in length (including abstract but excluding reference list and reasonable use of
tables and figures).
Student’s signature: Eva Thiel
Date: 30/08/19
Student name: Eva Thiel
Supervisor name: Matt Ashby
Title of proposed project: The Study of Pedestrian Plaza’s Influence on Crime Rates in New York
City, using Geospatial Data and Focusing on Location and Seasonal variations.
3
, LONDON’S GLOBAL UNIVERSITY
Upon review of the materials that you provided, the Department of Security and Crime Science Ethics
Committee has decided that your proposed research is exempt from requiring approval by the UCL
Research Ethics Committee. This is because the proposed research either:
- does not involve human participants and/or does not involve the collection and/or use of data
derived from human individuals, or
- corresponds to one or more of the following UCL exemption criteria
(https://ethics.grad.ucl.ac.uk/exemptions.php):
Ethics exemption
1. Research involving information freely available in the public domain. For example, published biographies,
newspaper accounts of an individual's activities and published minutes of a meeting, whilst still personal data
under the Data Protection Act would not require ethics review.
2. Research involving anonymised records and data sets that exist in the public domain. For example, datasets
available through the Office for National Statistics or the UK Data Archive where appropriate permissions have
already been obtained and it is not possible to identify individuals from the information provided.
3. Studies of public behaviour that are purely observational (non-invasive and non-interactive), unless the recorded
observations identify individuals (names, photographs) which could place them at risk of harm, stigma or
prosecution.
4. Research involving the use of non-sensitive, completely anonymous educational tests, survey and interview
procedures when the participants are not defined as "vulnerable" and participation will not induce undue
psychological stress or anxiety.
5. Research involving the use of educational tests, survey and interview procedures on human participants in the
public arena (e.g. elected or appointed public officials, candidates for public office, artists).
Should your project substantially change from what you have proposed, you will need to go
through the ethics process again.
Signed: Dated: July 30, 2019
Dr Georgina Meakin
Chair, Departmental Ethics Committee
Department of Security and Crime Science
University College London
University College London, Gower Street, London WC1E 6BT
Tel: +44 (0)20 7679 2000
4
