CUSP-GX-3007.001 Page 1 CUSP - TERM YEAR Fall 2015

Urban Spatial Analytics CUSP-GX-3007.001 Fall 2015 Thursdays, 6:00pm to 8:50pm (Lecture: 6 to 7:15 pm, & Lab Session: 7:15 - 8:50 pm) Location: Tisch Hall, 40 W 4th St, New York, NY 10012, USA Room: LC-19 Instructors: Him Mistry Manager, Data Services, & Adjunct Assistant Professor, NYU CUSP

Email: himist@nyu.edu Office phone: 212-998-2427, 718-249-5255 (cell) Office Hours*: Wednesdays 12-1:30 pm (except 9/16, 11/18 & 11/25) & By appointments. *Appointments during Office hours are preferred for allocating appropriate time for the consultations. Teaching Assistant: Kunal Barde Graduate Student, NYU School of Engineering krb385@nyu.edu

Course Description: Urban Spatial Analytics focuses on developing spatial analysis skills specifically in urban context, which cuts across various interdisciplinary fields like urban land-use planning, socio-economic development, education, public health, real estate, criminal justice, environmental studies, transportation, and urban demography. This course will equip students with Geographic Information System (GIS) concepts to collect, understand, organize, store, analyze and visualize complex urban geospatial data. Students will learn about combining and overlaying local urban datasets (like MapPLUTO, Taxi/Cab data, Tree Census, Transportation & other datasets) with regional and national datasets like US Census, in order to understand spatial relationships and foster critical thinking in addressing urban issues that informs urban and regional policies. Students will gain hands-on training on geospatial data management, advance analyses (geo-statistics, proximity analysis, site suitability analysis, cluster analysis..) , visualization techniques, and applications on solving real world problems, using ESRI's product - ArcGIS (ArcInfo with advanced extensions) as a primary software, however students will be exposed to other tools/programming languages like QGIS, CartoDB, ArcGIS Online, Python and others. Course Prerequisites: Experience with windows-based software and basic computer skills.

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Course Objectives: The purpose of this class is to equip you with GIS tools, specifically ArcGIS software via series of lectures, hands-on exercises, course readings, assignments, project work and exam. This class will enable you to create thematic maps, understand various spatial data and research, and conduct advanced spatial analyses. Furthermore, it will expose you to some geo-statistical analysis, network analysis, model-builders, 3D-GIS and web-based GIS tools. Course Textbooks: Required: This course will primarily use “GIS Tutorial 1 – Basic Workbook for ArcGIS 10.1 (5th Edition) by Wilpen l. Gorr and Kristen S. Kurland” as a required text. **Important Note: This course heavily relies on this aforementioned textbook and the data that comes with it. So please make sure to bring your textbook and the data on the first day of the class & onwards.** Optional: - GIS for the Urban Environment (2006) by Juliana Maantay & John Ziegler - GIS Tutorial 2 – Spatial Analysis Workbook for ArcGIS 10.1 by David Allen - How to Lie with Maps (2nd Edition, 1996) by Mark Monmonier - Analyzing Urban Poverty: GIS for the Developing World by Rosario Giusti de Pérez & Ramón Pérez Other course material will be distributed intermittently and as needed. Software Requirements: ArcGIS 10.3 (min. ArcGIS 10.2 or latest). You can get a free ArcGIS copy from NYU Data Services by filling out the Software Request form. You must have ArcGIS installed on your own laptop (macbook, notebook...) at the beginning of the first class. **Please note that ArcGIS is a Windows-based software. Macintosh users must install Windows OS in order to runArcGIS (see the instructions below). MAC users can buy and install Windows Operating System via Bootcamp (should be pre-installed for all new Macs ) or via VM Ware or Paralles. Once you have installed Windows OS on your MAC, you can then install ArcGIS on the Windows OS part of your MAC. Ask your Academic Coordinator for obtaining Windows OS. For student pricing on VM Ware and Parallels visit NYU Computer Store:https://www.bookstores.nyu.edu/computer.store/software.prices.html Grades:

Attendance & in-class participation 15% Assignments 15% Mid-term 30% Final Project 40% Attendance is crucial as our class only meets once a week, and has a lot of hands-on in-class exercises. Only one unexcused absence per term will be allowed, with the due responsibility of the student to catch up on readings, exercises and assignments for the class he/she has missed. Following that, each unexcused absence

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will be one percentage point off your grade. For excused absences, I will need a doctor’s note or other proof of an emergency, and I prefer to be notified in advance via email. All assignments need to be submitted in a timely manner. Unless instructed otherwise please upload/submit an electronic version (pdf format) for each assignment, on the NYU Classes > Assignments section. Each late submission will be penalized with 0.5 percent point, with a maximum of 2 percent points per assignment. The final will be a group project. Guidelines for the project proposals and projects will be delivered later in the semester. The project proposal should not exceed one A4 size page. Please do not hesitate to ask questions if you are not clear and/or struggling with concepts instead of waiting till the last minute. Statement of Academic Integrity NYU CUSP values both open inquiry and academic integrity. Students’ graduate programs are expected to follow standards of excellence set forth by New York University. Such standards include respect, honesty, and responsibility. The program does not tolerate violations to academic integrity including:

Plagiarism

Cheating on an exam

Submitting your own work toward requirements in more than one course without prior approval from the instructor

Collaborating with other students for work expected to be completed individually

Giving your work to another student to submit as his/her own

Purchasing or using papers or work online or from a commercial firm and presenting it as your own work

Students are expected to familiarize themselves with the University’s policy on academic integrity and CUSP’s policies on plagiarism as they will be expected to adhere to such policies at all times – as a student and an alumni of New York University. The University’s policies concerning plagiarism, in particular, will be strictly followed. Please consult the Chicago Manual of Style for guidelines on citations. Do not hesitate to ask if you have any questions regarding writing style, citations, or any academic policies.

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Course Outline (subject to change as needed)

Session Topics

Week-1 Sep 03

Introduction to GIS (Ch. 1) Open and Save map documents Work with map layers Explore interface and various features of ArcGIS Readings/tutorials (1-1 to 1-4) In class tutorials (1-5 to 1-8) Assignments: 1-1 and 1-2 (Due Week-2)

Week-2 Sep 10

Map Design (Ch. 2) Thematic mapping Group layers, dynamic map scaling, and attribute query on point maps Readings/tutorials (2-1 to 2-3) In class tutorials (2-4 to 2-8) Assignments: 2-1 and 2-2 (Due Week-3)

Week-3 Sep 17

GIS Outputs (Ch. 3) & Spatial data (Ch. 4) - 1 Create map layouts and templates Geodatabase concepts Readings/tutorials (3-1 to 3-4), & (4-1 to 4-3) In class tutorials (3-5 to 3-8) & (4-4 to 4-6) Assignments: 3-1, 3-2, 3-3, 4-1 and 4-2 (Due Week-4)

Week-4 Sep 24

Spatial Data (Ch. 5) - 2 Constructs – types, metadata and components Digitization (Ch. 7) - Create, edit and save geo-spatial features Readings/tutorials (5-1 to 5-3) & (7-1 to 7-2) In class tutorials (5-4 to 5-6) & (7-3 to 7-5) Assignments: 5-1, 5-2, 7-1 and 7-2 (Due Week-5)

Week-5 Oct 01

Geoprocessing (Ch. 6) Extract, clip, dissolve, merger, intersect and union features ModelBuilder introduction to automate geoprocessing and python outputs. Readings/tutorials (6-1 to 6-3) In class tutorials (6-4 to 6-7) Assignments: 6-1, 6-2 and 6-3 (Due Week-6)

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Week-6 Oct 08

Geocoding (Ch. 8) + Mid-term discussion: Readings/tutorials (8-1 to 8-2) In class tutorials (8-3 to 8-5) Assignments: 8-1 and 8-2 (Due Week-10)

Week-7 Oct 15

Web-mapping introduction: ArcGIS Online & CartoDB Readings/tutorials (custom) In class tutorials (custom exercises) Assignments (TBD)

Week-8 Oct 22

Mid-term exam

Week-9 Oct 29

Spatial Analysis (Ch. 9): + Final Project Proposal discussion Proximity analysis, Site suitability analysis & cluster analysis In class tutorials (9-1 to 9-3) Assignments: 9-1, 9-2 and 9-3 (Due Week-10)

Week-10 Nov 05

Spatial Analysis advance (Ch. 11): + Final Project Proposal discussion Kernel density analysis, Raster-based site suitability study & creating risk index Readings/tutorials (11-1 to 11-3) In class tutorials (11-4 to 11-6) Assignments: 11-1 & 11-2 & Project Proposal Due date (Due Week-11)

Week-11 Nov 12

Geo-statistical Analysis - 1 + Project Proposal Due date (today) Concepts: What is spatial statistics? Spatial measurements, understanding spatial data distributions.. Readings/tutorials (custom) In class tutorials (custom exercises) Assignments: TBD: Due date (Due Week-12)

Week-12 Nov 19

Geo-statistical Analysis - 2 + (Guest - possibility) Measuring geographic distributions: compactness, orientation & direction, using statistics to identify patterns & clusters, defining weights, & identify geographic relationships. Readings/tutorials (custom) In class tutorials (custom exercises) Assignments: TBD: Due date (Due Week-13)

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Week-13 Nov 26

Thanksgiving - No Classes

Week-14 Dec 03

3D GIS / Web-mapping (ArcGIS Online & CartoDB) / Network Analysis - an introduction + Visualization Readings/tutorials (custom) In class tutorials (custom exercises)

Week-15 Dec 10

Final Project presentations