Massachusetts Institute of Technology
Department of Urban Studies and Planning

 

11.188: Urban Planning and Social Science Laboratory

11.205: Intro to Spatial Analysis (1st half-semester)
11.520: Workshop on GIS (2nd half-semester)

Lecture One Notes:
Overview of CLass, GIS Principles, Map Elements, QGIS Basics

 

February 17, 2021


Class Overview & Logistics

  • 11.188 = 11.205 + 11.520
    • 11.188 is undergrad, full-semester class
    • 11.205 (1st half-semester) & 11.520 (2nd half-semester) are graduate
    • classes meet together but individual projects differ
  • Times and rooms: Wed. lecture, 2:30-4:00 + Mon. lab, 2:30-5:00
    • Additional, optional lab time: Friday, during time to be arranged
    • Office hours: Tuesday, 12:30-2pm (Rounaq), and Thursday, 10:45-12:15pm (Joe)
  • Stellar website - only for lab exercises, homework, and test
  • Download start-up Lab #0 exercise: http://mit.edu/11.188/www/labs/lab0/lab0.pdf
  • Piazza website for Q&A: https://piazza.com/
    • Can also send email to 11.520staff@mit.edu



Class Introduction

  • Remember to SIGN UP on Google Docs:here
  • Review class website: http://web.mit.edu/11.188
    • Skim links for Syllabus, lectures, labs, readings, homework, test, project, calendar (on Stellar)
    • Software for exercises
      • QGIS, R+RStudio, Postgres (limited use), ArcGIS (intro)
      • Lab #0 and QGIS software installation
  • Background and motivation: Where does learning GIS fit in
    • 11.188 as an "urban planning and social science lab" that meets Institute lab requirement
    • 11.205 to meet MCP spatial analysis requirement
    • Explain 11.205 + 11.520 half-semester parts for graduate credit
    • Distinguish types of spatial analysis
      • Map as digital representation of physical form (cartographic depiction of geography)
      • Map of human activity and community (CBD, mixed residential, land use ...)
      • Map 'algebra' to integrate data by location (homes in flood plain, scenic views...)
      • Construction and visualization of spatial proximity indicators (walkability, accessibility...)
  •  Prep before Monday's lab
    • Read Lab #0 and download QGIS v. 3.10 software
    • Skim Lecture #1 readings (listed in syllabus)
    • Review newspaper articles with maps and spatial analysis (and find new examples during semester)

(1) The Geography of Voting - and not Voting: Washington Post, October 23, 2018:
https://www.washingtonpost.com/graphics/2018/politics/voter-turnout/?utm_term=.255ddace8f04

(2) Mapping Block-Level Segregation: The Twin Cities’ Black Population, 1980-2010: http://blog.popdata.org/mapping-segregation/
(3) Mapping Poverty in America: NYTimes, Jan. 4, 2014: http://www.nytimes.com/newsgraphics/2014/01/05/poverty-map/

Meet your classmates

    • Brief round-the-zoom introductions
    • Zoom norms for class:
      • audio-on during discussion and Q&A
      • video-on where practical, especially for discussion and Q&A
    • Breakout rooms to discuss the three map examples - 10 minutes
      • Questions to ponder during breakout groups:
        • What does each map 'say'?
        • What are the data measuring? 
        • What is the level of spatial aggregation?
        • What do variations in colors/symbols mean? 
        • Is the evidence convincing, diagnostic, misleading? 


Additional Questions to ponder later as you review published spatial analyses this semester:

  • Is the evidence convincing, diagnostic, misleading?
  • Are there better alternatives for measuring the phenomenon of interest?
  • Are the visualizations consistent with the story, appropriate, biased, sensitive to the spatial scale?
  • What data and tools are needed to construct the visualization?
  • What context is needed in order to interpret the maps appropriately

Additional examples to consider:
(1) The Great Gerrymander of 2012: New York Times, Sunday, Feb. 2, 2013

-- Article: http://www.nytimes.com/2013/02/03/opinion/sunday/the-great-gerrymander-of-2012.html?pagewanted=all&_r=0
-- Graphic: http://www.nytimes.com/interactive/2013/02/03/sunday-review/imbalance-of-power.html?ref=sunday

(2) The Geography of Government Benefits: NYTimes, Feb. 11, 2012
http://www.nytimes.com/interactive/2012/02/12/us/entitlement-map.html

(3) The Pollution Proximity Index, Metropolitan Area Planning Council (MAPC), 2020: https://datacommon.mapc.org/calendar/2020/july

(4) Tricking Google Maps to think there is a traffic jam:

What is GIS?

  • What about Google Maps, Apple Maps, and Bing?

  • What's different about QGIS or ArcGIS?

  • What to learn? how to add your own data/analyses?...

  • Some distinctions:

    • User flexibility in manipulating, recombining, symbolizing geospatial data
    • Analyzing and characterizing spatial relationships through geoprocessing
    • Other issues: proprietary vs. open/interoperable; local vs. in-the-cloud; ...
Evolution of GIS: A Timeline from 1970s to now


 

 

 

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  • GISytems, GIScience, GIStudies, GIServices, Spatial Analysis, Urban Analytics... (lots of jargon and academic debates)
  • GISystems – A computerized tool that helps solve geographic problems.
  • GIScience – The development of data models, algorithms, and methods for representing geography and spatial relationships in order to support spatial analysis and location-based computing
  • GIA - Geographic Information and Analysis
  • GIStudies – the systematic study of society’s use of geographic information, including institutional, organizational and procedural issues.
  • GIServices – The business of providing GIS data and analysis tools to GIS users (often by chaining interoperable components in lego-block fashion).


Example GIS Applications - think about useful data models for each example

  • Resource inventory (what is available where?)
  • Thematic maps (spatial pattern of population density, income, household size, etc.)
  • Network Analysis (How to get somewhere by road in the shortest amount of time?)
  • Location Analysis (Where is the 'best' place to locate a shopping mall?)
  • Terrain Analysis (What is the danger zone for a natural disaster? What can be seen from here [visibility analysis])
  • Spatio-Temporal Analysis (Land use: what has changed over the last twenty years, and why?)
  • Runoff models (If it rains 1 inch in 3 hours, how big is the storm surge at the bottom of the hill?)


GIS Basics-- preview of Lab Exercise 1

  • We will thematic maps of Cambridge home sales and household income and overlay results on Google Maps
  • Here is a screenshot of ArcMap with several data layers and web services in the table of contents before symbolizing sales and shading census block groups

lab1 arcmap screenshot with web services

Things to think about this week and next

  • Explore elements in table of contents
    • Some are 'web services' in the cloud
    • Some are shapefiles (stored locally on disk)
    • How are spatial features modeled and linked to textual information about them
  • What are the major elements of GIS and how are they organized
  • What help resources are useful: QGIS documentation, Google searches, ...
  • How can a problem be split into operations that utilize the underlying 'vector' and 'raster' data models
    • E.G., which Cambridge housing sales occurred in low-income neighborhoods

 

Specific skills for this week and Monday's Lab

  • Setting Up a Work Environment
    • Starting QGIS
    • Setting up your class workspace on local disk, Dropbox, etc.
    • Accessing class datasets
  • Getting Data Into QGIS
    • From shapefiles, text files, postgres database, web service...
    • Managing 'layers' within your QGIS project
    • Attribute Data
  • Basic Map Making
    • Linking geometric objects with tabular data
    • Simple Symbolization
    • Classification and thematic mapping
  • Saving Your Work and Printing Output
  • Explore cross-referencing of map and data tables
  • Discuss data model for geometry and attributes
  • Compare QGIS and ArcGIS vs. Google Maps, Apple Maps, ...

Elements of the Map

    • Scale (Distance on the map compared with distance on the earth)
    • Symbolization
    • Projection (Euclidan coordinate system instead of Lat/Lon)
      • ... Ignore projections for today and jump into QGIS to get a feel for key features of a typical GIS package
      • ...We'll pay more attention to maps, data models, and GIS basics in other lectures or in lab

 

Data Models -- How to encode Geometry and Geography

Vector data model

  • Model spatial objects by describing their boundaries
    • Use coordinates that locate the spatial objects on the Earth
    • Point--a single XY location is often sufficient
      • MBTA Stops
      • Is Boston a point?--At different scales or for different purposes, Boston could be a point or polygon.
    • Line--only one dimension needs to be represented
      • Street centerline, MBTA Railroad track, ridgeline, bus route
      • How does it matter if street is modeled as centerline or as the void between blocks?
    • Polygon--2D planar surfaces
      • Cambridge border, central square boundary, census tract, parcel, ...
      • What about river boundary, edge of ocean (at high tide?)
    • Beyond planar surfaces - terrain models, 3D CAD models, ...
    • Link Attribute TABLE to spatial objects
      • Assign Object ID to each spatial object
      • Each row in attribute table links object ID to attributes of that object (census tract, zip code, ...)

Raster data model

  • Model the space that contains spatial objects (RASTER data models)
    • Divide space into 'cells' and encode whether a spatial object is in each cell
    • 30m x 30m grid cells for Landsat image - classified based on predominate land use within each cell
    • 6 inch pixels for color orthophotos developed from aerial photography
    • 3 km x 3km x 1 km (height) volumes (voxels) for meterological modeling


What does it mean to be "doing GIS"?

  • using the tools of Geographic Information Systems to solve a problem
    • urban planning relevant contexts were described above
    • a GIS project might have the following stages:
      1. define the problem
      2. acquire the software (and the hardware? or network resources?)
      3. acquire the data
      4. clean the database
      5. perform the analysis
      6. interpret and present the results
      7. institutionalize the process so that the analysis can be routinely redone
  • GIS tools and techniques are becoming more integrated with other tools and/or embedded in web services with geoprocessing capabilities
    • Do spatial analysis without being 'in' a GIS package
    • Include location, spatial indexing, etc. in general purpose database management tools
    • Use third-part tools and APIs to facilitate geoprocessing: e.g. Carto, MapBox, Leaflet,...

[Lecture #1 presentation is expected to stop around here...]

 

Additional notes on 'Vector' data models for geospatial location

    • Geometry model:
      • boundary representation 'vector' model of spatial features
      • assign spatial feature ID to each spatial object within each map 'layer'
      • points (sales), lines (streets), and polygons (block groups)
        • Separate X,Y data for every part of every feature
        • Shared X,Y data for shared points and boundaries
    • Attribute data model
      • relational tables linked to spatial features via feature-ID
      • graphical interface to utilize geometry/attribute links
        • highlight map features by selecting attribute table rows
        • highlight attribute table rows by selecting map features
    • More than one way to represent the geometry: shape detail, shared boundaries, ...
      • ArcGIS shapefiles are the simplest and most common vector model
        • Only one feature type per shapefile
        • Several (4+) files on disk for each shapefile: cambbgrp.xxx
      • The Open Geospatial Consortium (OGC) is an international consortium focused on interoperable geospatial standards for sharing location-embedded data (www.ogc.org)
    • Complications
      • islands, lakes, overpasses
      • shared edges?, do attached links move when you move points?
      • ambiguity: summer/winter wetland boundaries
      • scale, generalization, conflation, slivers
      • Coordinate systems and projections
      • One-to-many relationships among spatial features and events
    • Thematic mapping - tip of iceberg regarding GIS applications
      • Symbology
        • many options
        • review 'symbology' page of layer properties
        • review ArcGIS help files for symbology
      • Different classification schemes (show help page):
        • Equal Interval
        • Natural Breaks
        • Quantile
        • Standard Deviation
      • Normalization: people or population density - Why do we care? (show examples)

Created by Prof. Zhong-Ren Peng, September 2nd, 2003.
Modified by Joe Ferreira & Jinhua Zhao, September 7th, 2004.

Last Modified by Joseph Ferreira, Feb. 17, 2021.

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