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					Harvard Returns to Geography

      The reasons for creating and
         the prospects for the
    Center for Geographic Analysis
              Harvard and Geography
Harvard University closed its Geography
  Department in 1948. Since then --
• Quantitative geography has gained much
  ground in the 1950s                                      (http://www.infoplease.com/ce6/world/A0858357.html)


• Geographic Information Systems started in the
  1960s when computers became available
  (http://envstudies.brown.edu/Thesis/2001/james/gishistory.html)


• Geoinformatics, geospatial analysis, geotech …
  boomed in the past two decades as fruits from
  the crossbreed of geography and information
  technology
Geographic Analysis in Harvard
Geographic analysis continues to occur in
  Harvard:
• The Harvard Map Library and Harvard
  Geospatial Library
• Datasets in the social sciences from HMDC
• Urban planning and landscape from the GSD
• Public health data from HSPH and the Ellison
  Institute
• Environmental sciences from the University
  Center for the Environment
• The China Historical GIS project
                 The Harvard Map Library
    • Catalog of geographically
      referenced data
    • Repository for storing data
    • Infrastructure for distributing data


                                                 King County, Washington: Zoning




Global GIS: Volcanoes




                        Andover historical map
     Harvard Geospatial Library


A catalog and
repository of
geospatial data
within the
Harvard library
system
Datasets in the Social Sciences
from Harvard MIT Data Center
   Urban Planning and Landscape
from the Graduate School of Design
   Urban Planning and Landscape
from the Graduate School of Design
  Data from Harvard School of Public
    Health and the Ellison Institute



                        Contamination Plume




Predicted particulate
concentration
  Environmental Sciences from the
University Center for the Environment

            Coal fueled power plants
The China Historical GIS Project

                Tax quota in the year 1077
      Why?



Because it is estimated that 80%
 of all data has a spatial
 component – a component that
 has been largely neglected
         The Creation of the
    Center for Geographic Analysis
• Many faculty and staff across the university have
  joined discussions during the past two years
  concerning
   – improving access to spatial data,
   – support for research employing geospatial analysis,
   – and curriculum development.
• With support and encouragement from the
  Provost, the FAS Dean and the GSD Dean, the
  Center for Geographic Analysis has been
  established in the new Institute for Quantitative
  Social Science.                           (http://hgl.harvard.edu:8080/HGL/html/CGA_announcement1.pdf;
  http://www.news.harvard.edu/gazette/2005/10.20/26-bol.html)
                 CGA Goals
• The Center for Geographic Analysis at Harvard
  University is a newly established program
  focusing on research and education in the field
  of spatial analysis and geographic information.
• The Center’s goal is to work with entities across
  the university to
  – strengthen university-wide geographic information
    systems' infrastructure and services;
  – provide the common platform for the integration of
    data from diverse sources and knowledge from
    multiple disciplines; and
  – enable scholarly research that would use, improve or
    study geospatial analysis techniques.
A technology platform that supports research and
teaching in all the fields that employ geospatial
analysis across the university
      CGA Staff Responsibilities
• Supporting research and teaching that relies on
  geographic analysis
• Helping to select and administer Harvard-wide
  GIS software site licenses
• Collecting and disseminating spatial datasets
  currently residing in isolated locations around
  the university
• Working with the Harvard MIT Data Center to
  create links between the Harvard Geospatial
  Library and the Virtual Data Center project
• Maintain the Harvard GIS website
  (http://www.gis.harvard.edu)
           CGA Activity Plan
• Organize a guest speakers series to promote
  academic exchange in geographic analysis
• Create positions for post-doctoral fellows who
  will work with research projects across the
  university
• Create internships for undergraduates and
  fellowships for graduate students who apply
  spatial analysis in their research
• Provide teaching facilities for geographic
  analysis through the computer labs in the Center
Faculty Position and Curriculum
• In creating the Center the University has also
  committed itself to raise funds for senior faculty
  positions that will give us greater strength in
  such fields as geospatial analysis,
  geoinformatics, and geography.
• We are concerned with adding to the
  undergraduate and graduate curriculum across
  the University and look forward to working with
  current faculty in DEAS, FAS, GSD, and HSPH
  to help develop and support the appropriate
  courses, course modules, and labs.
              CGA Governance
• The Center has faculty steering committee of
  •   Peter Bol, FAS, Director of the CGA;
  •   Gary King, FAS, Director of the IQSS;
  •   Niall Kirkwood, GSD, Chair of Landscape Architecture;
  •   Carl Steinitz, GSD;
  •   Peter Rogers, DEAS;
  •   Louise Ryan, HSPH;
  •   Robert Sampson, FAS; and
  •   Dan Schrag, FAS, Director of the Harvard University
      Center for the Environment.
• There is also a professional technical staff
  committee composed of professionals from
  across the university.
             CGA as a “Hub”
• There are already a number of research groups
  and centers, departments, and schools which
  employ geographic analysis, some of which
  already have professional staff with expertise in
  GIS. In addition the Harvard College Library’s
  Map Collection has GIS specialists.
• The Center for Geographic Analysis serves as a
  “hub” that supports and coordinates with these
  various “spokes” by providing technical and
  design expertise and by increasing the
  capabilities of the Harvard Geospatial Library as
  a common repository for geospatial datasets.
  Support Research and Teaching
• There is a substantial list of projects across the
  University that seek technical support.
• It is expected that when research projects require
  ongoing staff support that grant proposals will
  include this in the budget.
• The Center’s staff has already begun to provide
  support in formulating grant proposals and
  conducting analysis for on-going research projects:
   – Thailand local economic development
   – Germany labor productivity
   – Amazon forest fragmentation
• We also support teaching and provide technical
  consultation to students.
The Effects of Protected Forest Areas on Local Economic
Development in Villages of Chiang Mai Province, Thailand

 By Kate Eman, Kennedy School of Government
 • This project analyzes how protected area policies have
   affected economic development in the context of villages
   in Chiang Mai Province in Northern Thailand.
 • It compares the growth of selected household assets
   and employment rates for villages inside and outside
   different types of designated forest protection areas over
   a period from 1986-2003, using bi-annual survey data
   from the Thai Community Development Department.
 • Geospatial data plays an important role in choosing
   villages in the comparison or "control" group that are
   similar in terms of geographic characteristics (including
   elevation, slope, soil type, and proximity to major water
   bodies) to those villages that are inside of protected
   areas.
        Thailand Project: Tasks
•   Collect and calibrate data
•   Conduct geospatial analyses
•   Make maps, and
•   Provide technical tutorial
       Thailand Project: Analysis
    The project
    calculates five
    geographic data
    variables for roughly
    1,500 villages in the
    Chiang Mai
    province.

•   Average Elevation within 1.5 km radius
•   Average Slope within 1.5 km radius
•   Distance to closest major river or perennial stream
•   Distance to border of nearest conservation area
•   Soil type composition within 1.5 km radius
    Thailand Project: Mapping
• Visualize major steps of analyses
• Make thematic maps for publication
       Thailand Project: Result
Export result into database for further statistical
  analyses
Thailand Project:
Tutorial Documentation
• Help researchers to have
  a better understanding of
  the methodology
• Make it easier for
  researchers or graduate
  students to repeat the
  procedure if they want to
  change variables or just
  want to practice GIS skills
• Document major steps
  that are useful to similar
  projects
   What Causes the Low Labor Productivity in
      East Germany? A Spatial Analysis
By Nicola Fuchs-Schündeln, Assistant Professor of
Economics and Rima Izem, Assistant Professor of Statistics
 • The study analyzes the reasons for the
   stubbornly low labor productivity in former East
   Germany and aims to distinguish between two
   main causes: worker characteristics (e.g. skills)
   vs. job characteristics (e.g. capital or
   infrastructure).
 • The study uses a spatial labor market model that
   allows for commuting. The discontinuity of
   unemployment rates in proximity to the former
   border will determine which factor is more
   influential in the unemployment rate.
  What Causes the Low Labor Productivity in
     East Germany? A Spatial Analysis

• The study uses county level data and tools of
  spatial econometrics to empirically analyze the
  slope of the unemployment rate along the former
  border, and calibrate the model to match the
  observed slope.
• Euclidean (e.g. as the crow flies) distance
  measurements distort proximity to labor markets
  because commuters rarely travel through the air.
  A drive-time matrix provides a more accurate
  measure of labor market spatial relationships.
  What Causes the Low Labor Productivity in
     East Germany? A Spatial Analysis

Task 1: Create Network Dataset
• The source of the data were layers of Germany’s
  Autobahns and National Roads from MACON GFK
• Each road segment in the source layers was
  attributed with distance. The estimated travel time
  on each segment was calculated using speed
  assumptions for the different road classes.
• A Network Dataset was built using ArcGIS Network
  Analyst. The dataset had to be rebuilt after it was
  discovered that 15% of the junctions in the road
  network were dropped due to offsets in vertices.
  The Integrate tool was used to correct the offsets.
 What Causes the Low Labor Productivity in
    East Germany? A Spatial Analysis

Task 1: Create Network Dataset

           Original




          Integrated




                                 Autobahns and National Roads
  What Causes the Low Labor Productivity in
     East Germany? A Spatial Analysis

Task 2: Create Layer of District Points
• The source of the data were layers of Germany’s
  Districts (Kreis) and Municipalities (Gemeinden) from
  MACON GFK. Population data was attached to the
  Municipalities layer.
• The research uses data from 439 Districts. Network
  analysis requires origin and destination points.
  Therefore, a representative point had to be created for
  each district.
• The centroid of each district was rejected as a
  representative point due to its lack of relevance to
  settlement patterns. The most populous municipality in
  each district was queried and its centroid was deemed to
  be the best representative point, due to the smaller size
  of the municipalities.
   What Causes the Low Labor Productivity in
      East Germany? A Spatial Analysis

Task 2: Create Layer of District Points



  Sample District with Municipalities
       Shaded by Population
  What Causes the Low Labor Productivity in
     East Germany? A Spatial Analysis

Task 3: Create an Origin-Destination Cost
  Matrix
• The Network Dataset and the representative
  points layer were used as inputs for an OD Cost
  Matrix analysis in Network Analyst.
• The resulting table of nearly 200,000 routes was
  parsed to create one record for each unique pair
  of points. The analysis was performed twice:
  once with time as the impedance and once with
  distance as the impedance. The data was
  exported to ASCII files for use in statistical
  analysis software.
   What Causes the Low Labor Productivity in
      East Germany? A Spatial Analysis




Task 3: Create an Origin-
Destination Cost Matrix
   Amazonia Forest Fragmentation
      Impact on Precipitation
By Paul Moorcroft, Associate Professor of Biology
• This project compares landuse/landcover classification
  maps in different years to determine land use change
  patterns.
• It models forest fragmentation,
  and its impact on precipitation.
• The forest edge effect is related to
  forest fire risks, which in turn
  affects the hydrologic cycle.
   Amazonia Forest Fragmentation
    Impact on Precipitation: Tasks
• Image classification for land cover
   – from LandSat images, delineate non-vegetated land
     (water, bare soil, pavement); non-forested land
     (farmland, meadows); and forestland
• Spatial analyses
   – land cover change detection
   – land cover fragmentation
   – distance to edge calculation
   – forest degradation quantification
• Simulation results visualization
   – Mapping
   – 3-D animation
Amazonia Forest Fragmentation
 Impact on Precipitation: Data




                                Red: band 7,
                                mid-infrared
                                Green: band 4
                                (near-infrared)
                                Blue: band 2
                                (visible green)




   LandSat Image, summer 1990
Amazonia Forest Fragmentation
 Impact on Precipitation: Data




                                Red: band 7,
                                mid-infrared
                                Green: band 4
                                (near-infrared)
                                Blue: band 2
                                (visible green)




   LandSat Image, summer 2000
      GoogleEarth File Development and
     Training for Chinese History Students

• An ArcObjects procedure was developed to create
  GoogleEarth place files (KML files) from the China
  Historical GIS database.
• Freeware KML generation tools were not sufficient
  because they produced ASCII files, thereby corrupting
  the Chinese characters stored in the database.
• The procedure created a text file using the UTF-8
  character set to maintain the Chinese characters.
• A Chinese History class was given a one-hour
  introduction to GoogleEarth using the sample files.
• The class included instruction on placemark creation and
  description editing.
• The class was in preparation for coursework in which
  students will identify market towns using GoogleEarth.
 GoogleEarth File Development and
Training for Chinese History Students
             Technical Support for
       GIS Data Development and Analysis
An undergraduate student needed assistance in calculating
the distance from census tracts to state borders. His
research involved border effects for unemployment and
welfare benefits. After an hour of instruction and guidance
regarding ArcToolbox features and ArcGIS techniques, he
was able to complete the analysis independently.
            Technical Support for
      GIS Data Development and Analysis
Later in the week, the student requested assistance in
eliminating ocean and international boundaries from
the state boundaries layer. With minimal prompting, he
learned basic ArcEditor techniques and created the
layer independently.
Center for Geographic Analysis

 Contact:                            1737 Cambridge Street, N319
 Wendy Guan, Ph.D.                   Cambridge, MA 02138
 Director of GIS Research Services   617-496-6102 (voice)
 Center for Geographic Analysis      616-496-5149 (fax)
 Harvard University                  wguan@cga.harvard.edu

				
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