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1 - Intro to GIS for the Social Sciences. ARE 493I. Goal. Apply GIS techniques to social science and business research Explore spatial and quantitative analysis methods
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Goal • Apply GIS techniques to social science and business research • Explore spatial and quantitative analysis methods • Examine problems in business and marketing, community planning and development, health care, crime analysis, environmental justice, recreation, and other applications • Explore the significance of spatial thinking in social science research and analysis.
Learning objectives • Explain how place and space are important and can be analyzed with GIS in various social science fields. • Find and download appropriate census data for use with political boundaries. • Perform business and marketing space based analyses. • Analyze the patterns of features and use models to make predictions about future conditions.
Today • Intro to GIS for social sciences • Combining Tables
GIS use in the social sciences • An analytical tool for social sciences • Not new, but only recently has it gained wider recognition • Due to availability and easy to use software • Applied in various social science disciplines • Is a continuously evolving technology
Examples • Mapping crime statistics • Social inequality • Environmental justice
Understanding the “G” in GIS • Knowing exact location is an important part of the GIS process • Information about people and places is location based. • Street address, zip or area code, census block, x,y coordinates, latitude and longitude, etc • scientific basis for mapping – scale (level of spatial detail - privacy and ethical issues), coordinates, control datums.
Understanding the “G” in GIS • Not all social science research use spatial analysis • focus on social, economic, cultural and survey data without spatial questions • E.g. Do educated or wealthier pregnant women receive higher quality prenatal care? • Alternatively • Where are the prenatal clinics located relative to available public transportation, child care etc ? → causative relationships.
Understanding the “G” in GIS • Not all data is geographic – e.g. data on perceptions, desires, social ties, ideas or interactions. • Use of cartograms - to represent social relationships • Data variability in time and space • Most data are static – snapshot in time. • Difficult to map changes or trends in data • Many things are dynamic • Choice of variables to be used. E.g. Mapping individuals over time - home address or place of employment; or where the person is likely to be at a particular time of the day or week.
Understanding the “G” in GIS • Computers allow us to transform static data into dynamic data – Animation • Difficult and expensive to collect and update temporal scale (real time) data • Fortunately, only a few social science applications use this kind of data • Representation issues • Privacy and ethical issues • Lumping (grouping) or degrading to mask individual data points
Understanding the “I” in GIS • Information relates to software database • Databases are specialized software programs designed for storage, organization and retrieval of information. • Most GIS can interact with any database system • May involve some transformation and translations • Most data are now available in GIS ready formats e.g USCensus, local and state agencies, private companies and universities • Primary data – surveys, interviews, and observations • locational information and coding and formatting
Extending the “I” in GIS • Multimedia capabilities of computers • Allows the incorporation of video, audio, photos and text • Oral history, narratives and interviews, • Data is stored in a raw form • Can be used for further and different analysis • Dynamically linked to a map location
Understanding the “S” in GIS • System component • Hardware, software and people • GIS setup involves costs and training • Issues of data structure, format and compatibility – Interoperability • High costs and training may warrant subcontracting to GIS specialists.
Understanding the “S” in GIS • GIS data model is based on discrete data categories of points, lines and polygons that are in space • Assumes all data can be linked to a specific discrete location • Assumes that lines can be drawn to delineate boundaries between data categories • Many data sets are not clearly defined • E.g degraded • Efforts to develop fuzzy GIS systems – less defined locations and boundaries
Qualitative Research Methods • Integrating qualitative research and GIS • Qualitative research forms: • Sociospatial grounded theory • Participant observation • Ethnography • Oral histories
Qualitative Research Methods • Inductive Approach • Grounded Theory and GIS • Sociospatial Grounded Theory • Determine topic of interest • Determine geographic location of interest • Collect data (qualitative, spatially linked social data) • Geocode the data • Ground truth the data • Analyze the data, look for spatial and social patterns • General theory (spatial and social)
Integrating GIS & Field Research • GIS software in the field • Entering data in the field. • Consider climate conditions, access to power or recharge the computer and storage space • Base maps of study area • Hard copy maps • Mark some reference points • Ground truth of map data • Verification and ground truthing • Use of aerial photos • Elicit help from local people
Integrating GIS & Field Research • Cultural perceptions of technology • How technology is viewed by people in the study area e.g. Amish community • Alternative methods • Access to Results • Who will read the report • Public access
Local Sources of Data • Oral History Interviews • GIS and oral history • Participant Observation • Researcher actively participates in the issue and topic under study • Researcher record their experiences (social, environmental and personal sentiments)
News as Data Source • Background data or actual data • Newspapers, magazine, TV and online formats • Content Analysis Approach • Analyze events in time, location, time of occurrence etc • Identify patterns in news stories • Information can be used for decision making
Ethnography and GIS • Detailed description of a problem or issue • “Telling people stories the way the people want the stories told” (Earl Babbie, 2003) • Recorded conversations • GIS integrates contextualized or environmentally situate the stories over time • Key elements/variables from stories can be used for analysis
Public Participation and GIS • Local people’s ideas, thoughts and actions are solicited to be part of the planning process. • Community meetings, stage hearings to solicit community input, focus groups, surveys, key informant interviews, needs assessments etc • Disadvantage – very few people (general public) understand GIS • PPGIS allows people to see the data and its physical, environmental or social context now or in future • Use of GIS as means of idea portrayal can give planners of community desires
Sociospatial Research • Enhances analysis by providing additional insights and information not previously considered • understand social context and characterstics • Outline • Explore GIS as a tool for the integration and analysis of social science data • Role of GIS in research • Applications
GIS in the social science • Does not have a long history in the social science • Its value is beginning to be recognized
Why is GIS a good tool for the social scientist? • Allows for the integration and comparison of contextual data from social as well as environmental or physical standpoint
Social science researcher • Almost all of their data have an associated geographic point of location • Researchers need to identify where the differences, similarities, correlations, and interactions exist • GIS can accommodate both qualitative and quantitative variables into a study
Inductive vs deductive approaches to research • GIS can be helpful to both • Inductive – hypotheses emerge from the data, no preconceived notions • Deductive – more traditional approach of lit review, generate framework, create hypotheses, test the hypotheses by collecting data
Combining Tables(application of Census data or other demographic information with spatial layers)
Right-click Tables • Descriptive information about features • Each feature class has an associated table • One row for each geographic feature
Understanding table anatomy • Basic table properties • Records/rows and fields/columns • Column types can store numbers, text, dates • Unique column names Columns (fields) Attributevalues Rows(records)
Table manipulation • Open table in ArcMap or preview in ArcCatalog • Sort ascending or descending • Freeze/Unfreeze columns • Statistics • In ArcMap • Select records • Modify table values
Associating tables • Can store attributes in feature table or separate table • Associate tables with common column key values • Must be same data field types • Must know table relationships (cardinality) Additional attribute table Feature attribute table Example: Associating county attribute table with separate table of poverty estimates by county for WV
Table relationships • How many A objects are related to B objects? • Types of cardinality • One-to-one, one-to-many or many-to-one, and many-to-many • Must know cardinality before connecting tables One parcel has one owner One parcel has many owners Many parcels have one owner Many parcels have many owners or
Joins and relates • Two methods to associate tables in ArcMap based on a common field • Join appends the attributes from one onto the other • Label or symbolize features using joined attributes • Relate defines a relationship between two tables
Connecting tables with joins • Appends the attributes of two tables • Assumes one-to-one or many-to-one cardinality WV_Poverty98 County Attributes (before Join) One-to-one County Attributes with joined poverty data (virtual table after Join) c c
Connecting tables with relates • Define relationship between two tables • Tables remain independent • Additional cardinality choices • One-to-many • Discovers any related rows 1) Make selection 2) Open related table Example: Relate WV county attributes to table of coal production statistics for 1986 - 1998