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1 - Intro to GIS for the Social Sciences

1 - Intro to GIS for the Social Sciences. RESM 493r. Goal. Apply GIS techniques to social science and business research Explore spatial and quantitative analysis methods

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1 - Intro to GIS for the Social Sciences

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  1. 1 - Intro to GIS for the Social Sciences RESM 493r

  2. 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.

  3. 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.

  4. Today • Into to GIS for social sciences • Hazards of place model

  5. 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

  6. Examples • Mapping crime statistics • Social inequality • Environmental justice

  7. 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.

  8. 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.

  9. 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.

  10. 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

  11. 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

  12. 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

  13. 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.

  14. 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

  15. Qualitative Research Methods • Integrating qualitative research and GIS • Qualitative research forms: • Sociospatial grounded theory • Participant observation • Ethnography • Oral histories

  16. 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)

  17. 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 • 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

  18. 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)

  19. 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

  20. 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

  21. Public Particiaption 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

  22. 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

  23. GIS in the social science • Does not have a long history in the social science • Its value is beginning to be recognized

  24. 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

  25. Social science researcher • Almost all of their data have an associcated 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

  26. 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 hypoth, test the hypoth by collecting data

  27. Hazards of place model

  28. Example: Hazards-of-Place Model of Vulnerability

  29. Example: Hazards-of-Place Model of Vulnerability

  30. Example:Hazards-of-Place Model of Vulnerability Step 1: Determining Biophysical Vulnerability

  31. Example:Hazards-of-Place Model of Vulnerability Step 1: Determining Biophysical Vulnerability

  32. Example:Hazards-of-Place Model of Vulnerability Step 1: Determining Biophysical Vulnerability

  33. Example:Hazards-of-Place Model of Vulnerability Step 1: Determining Biophysical Vulnerability

  34. Example:Hazards-of-Place Model of Vulnerability Step 2: Defining Social Vulnerability

  35. Example:Hazards-of-Place Model of Vulnerability Step 2: Defining Social Vulnerability

  36. Example:Hazards-of-Place Model of Vulnerability Step 3: The Vulnerability of Places

  37. Combining Tables(application of Census data or other demographic information with spatial layers)

  38. Right-click Tables • Descriptive information about features • Each feature class has an associated table • One row for each geographic feature

  39. 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)

  40. 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

  41. 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

  42. 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

  43. 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

  44. 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

  45. 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

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