Читать книгу GIS Research Methods - Steven J. Steinberg - Страница 94

What is a conceptual model? As discussed earlier, a conceptual model or framework is a working theoretical model that explains your view of the world. In essence, it is your chance to identify key variables in your study, to explain the links between these variables, and to explain the sequence and flow of relationships by using arrows. (We introduced the concept of creating a flowchart for GIS analysis in detail in chapter 2.)

Once you complete your literature review, you should have an easy time developing this framework. A conceptual framework is different from a literature review because it guides the research process of your specific project. The conceptual model establishes factors important to your study and indicates to all who read your study the predicted relationships between key variables.

Brainstorming is a good approach to developing a conceptual model or framework. You might start by writing down the important aspects of your study on a sheet of paper. Next, draw circles around these objects and use arrows to indicate relationships between these variables. As you identify your key variables, you can decide what type of contextual, geographic, or other information can facilitate a study of the relationships among these variables. When you identify relationships between the variables in your study, consider how geographic information might enhance your understanding of these relationships.

Consider our earlier example relating poverty and pollution. Given the spatial distribution of polluting facilities on the map, we would want to conceptualize what the actual locations really mean to our hypothesis: is presence of a facility inside a polygon all that matters, or do sites affect people for some distance (perhaps in a neighboring polygon)? If there is an effect over a distance, how does the mode of transport (through air, water, or solid waste) influence the distance and direction of the effect? What about the poverty data? Are all of the people in the census block distributed equally, or does the housing cluster in certain portions of the polygon? (This relates to issues of boundaries and the modifiable area unit problem discussed more fully in chapter 5.) The list could go on, but the important point is to think beyond what is directly visible, such as points falling inside particular polygons, to consider other factors or mechanisms that might be important in assessing the validity of your hypothesis.

A GIS is very useful for establishing how different variables relate to one another conceptually. Some GIS software programs provide a flowchart tool as a means to develop your analysis approach and, once populated with data and analysis functions, to run your model. Even when the flowchart is simply drawn on paper, it can guide you in developing a systematic or holistic approach to a particular issue under study.

For instance, suppose that you are conducting a study about an individual’s attitudes about environmental issues. You may hypothesize that the nature of the community and its geographic location (e.g., proximity to unspoiled natural features, such as state or national parks or wilderness areas) influence community concern about environmental issues. Your conceptual framework would then incorporate the geographic variable of park and wilderness proximity into your model (figure 3.10). Using a GIS, you could map the locations of these natural features and overlay sociodemographic characteristics and residents’ levels of environmental concern to see if there are differences.

Figure 3.10 An example of a conceptual model or framework for environmental concern. Sociodemographic factors, such as age, race, gender, and income, might have some relationship to where individuals choose to live (dashed arrow) in addition to their environmental concern (solid arrow). Proximity to parks or wilderness is also expected to have an influence on environmental concern (dotted arrow).