target="_blank" rel="nofollow" href="#litres_trial_promo">Chapter 4 addresses research ethics and the unique opportunities and challenges that incorporating spatial research methods into a research design brings. We begin the chapter with a discussion of ethical considerations when doing research in a spatial context. Researchers must keep in mind a number of important social, cultural, and political considerations, particularly when data, which may be sensitive, are linked to a map. We then discuss the use of existing or secondary data sources and potential errors that can arise when using these, owing to the data, processing operations within the software environment, or other human errors in the research process. The chapter also presents approaches for maintaining confidentiality and anonymity of data, masking data, and managing research data.
Chapter 5: Measurement, sampling, and boundaries
In chapter 5, we address issues of measurement, sampling, and boundaries. Topics include how to choose a sampling method for spatial analysis; the difference between primary and secondary data; and a discussion of concepts, variables, and attributes. From a sampling standpoint, we focus on using probability and nonprobability sampling and on spatial sampling considerations for stratification, data interpolation, and modeling. The crux of the chapter is how to incorporate spatial elements into a sampling design.
Chapter 6: Using secondary digital and nondigital data sources in research
In GIS-based research, a significant amount of time and effort goes into data acquisition and preparation. Data may come from a variety of existing sources or could be newly collected. With the widespread use of GIS, a growing number of digital data sources are becoming available. Therefore, it is common for many research projects to incorporate a substantial amount of existing, secondary data. Examples may include GIS layers or tabular data representing demographic, health, economic, or environmental information. Data may be acquired from a variety of sources, including local, regional, statewide, national, and international governments; nonprofits; and private organizations. Chapter 6 outlines how to locate, assess, and gain access to existing or secondary data relevant to the researcher’s project.
Chapter 7: Survey and interview spatial data collection and databases
Chapter 7 covers data collection via development of survey and interview instruments for use in a spatial analysis framework. It leads the reader through a series of steps and questions in the interview creation process that will allow researchers from a variety of backgrounds and disciplines to develop useful and spatially based interviews and surveys and the resulting databases. Additionally, this chapter leads the reader through how to approach data collection using ArcGIS in the field with and without a computer. Furthermore, it covers various data collection considerations, units of analysis, and factors to consider in creating a spatial database.
Chapter 8: Public participation GIS
Chapter 8 explores various aspects of spatially based public participation GIS (PPGIS) methods and volunteered geographic information. We address methods for organizing and collecting PPGIS data in the field that make use of simple, low-technology, and computer-based approaches. We highlight the collection of spatially based and spatially linked data through community engagement. We also discuss methods for integrating data from qualitative social contexts into measurable spatial variables.
Chapter 9: Qualitative spatial ethnographic field research
Chapter 9 explores approaches to conducting ethnographic research that has a spatial component. Specifically, we focus on how to accomplish spatial qualitative data collection in the field. Although GIS is a spatial computer program for ethnographic field research, we advise using a simple, low-technology process. Adopting a low-technology approach reduces the risks to data collection security and provides more data collection flexibility. In this chapter, we highlight the collection of primary, spatially based data via on-site ethnographic data collection methods, including case studies, oral histories, and participant observations. In essence, these are all forms of sociospatial documentation.
Chapter 10: Evaluation research from a spatial perspective
Chapter 10 discusses integrating spatial thinking and analysis with evaluation research. Over recent years, evaluation research has become increasingly common in many disciplines. Studies taking on an evaluation research approach seek to assess how well staff, projects, programs, and organizations accomplish and meet their goals.
Chapter 11: Conducting analysis with ArcGIS software
In chapter 11, we discuss using analytical tools in ArcGIS to analyze data prepared from both quantitative and qualitative sources. We provide examples to show how you might find the valuable geographic element in your data. We introduce various forms of analyses, including those you will likely want to apply as you begin to use GIS technology. Topics include buffers, overlays, networks, map algebra, raster analysis, interpolation, simulation, and modeling. We also provide an overview of analytical methods, extensions, and spatial statistics. The chapter addresses the means for linking external and discipline-specific quantitative and qualitative analyses with ArcGIS spatial outcomes. Finally, the chapter discusses common pitfalls to avoid when analyzing and interpreting results.
Chapter 12: Spatial analysis of qualitative data
In chapter 12, we discuss the use of qualitative analysis techniques and their link to spatial data in ArcGIS. Specifically, this chapter focuses on aspects of spatial content analysis such as coding, content, data type, manifest and latent spatial data collection, inductive approach and the deductive approach. This chapter explores how to handle qualitative data and how to analyze such data using spatial concepts. The chapter presents a series of steps used in the spatial qualitative data analysis process, including the process for data theming and coding. Different forms of qualitative data are examined such as hard-copy and digital data.
The ideas of variable definition tables and how they can be used in the analysis process are also explored.
Chapter 13: Communicating results and visualizing spatial information
Chapter 13 introduces key considerations in presenting your research findings. Communicating your message in an effective and appropriate manner and considering your audience and their needs can make all the difference to a project’s success. Of course, when using ArcGIS, one of your main means of communication will be a map. In this chapter, we present examples of excellent visualization using ArcGIS and strategies for effective communication using spatial technology. We offer guidelines for putting together a final presentation of your data that effectively incorporates cartographic visualization tools in ArcGIS. We also explore some of the other ways GIS can be used to communicate and share important research findings, including outputs beyond the map, with a variety of audiences.
Chapter 14: Linking results to policy and action
Chapter 14 explores how to translate your GIS analysis and findings into action. Throughout this book, we explore