Gentrification and GIS

      Gentrification is a social, economic, spatial and temporal phenomenon. It is a process of much contention. Not only is there inconsistency in the academic literature on what constitutes gentrification and how to measure it, but there are also "ethical and political cleavages" associated with its perceived existence in particular areas. (Blomely1997).
      Geographic Information Systems have come to be seen as an enabling technology capable of providing accurate, error free analysis of spatial information on which to base informed, grounded decision and policy making. (Chrisman 1997, Burrough and McDonnell 1998, Kraak 1999).
1 This is in contrast to how it is represented to the user, as a "technically overwhelming [tool] with thousands of possible commands and even more sources of errors" (Chrisman 1997).
      The obvious intended combination of the two is to provide an accurate spatial analysis of the factors at play in the processes of gentrification. The results of which are to be used to base decision and policy making or to back up political and ethical arguments and positions. There are obvious problems and limitations with such positivism. Despite this, the vision is made clear in an article in the Vancouver Sun from October 1997:

To developers, the downtown eastside is an empty wilderness and a golden opportunity for real-estate pioneers. To the people who defend it, it's home to the legendary retired resource workers who made B.C. Those two images, along with what's really happening with land development and values, are the focus of a new research project by SFU professor Nick Blomley, [who] will be using the university's powerful computer facilities to create complex maps that will show the shift in land prices in the 1990s (Bula 1997).

      That being said, GIS lends itself well to both the exploration and quantification of gentrification for a number of reasons. First, GIS allows the academic definitions and measures of gentrification to be operationalized and evaluated with real data. Second, GIS allows measures to be conducted at a number of different scales; and therefore, evaluations of processes and effects of gentrification at a variety of different scales. Third, it allows the visualization of measures and representations of gentrification, making it more intuitively understandable and more accessible outside the academic community. However, GIS also has some inherent problems specific to its application to gentrification. First, it can reaffirms scientific positivism and decision making with out taking real life context into account. Second, the discrete nature of GIS operations and representations can propagate the discrete nature in which gentrification has come to be represented.

      Though the actual evaluation of each of the measures considered in this study will be left to the sections dealing with that measure (see
Verbatim: Land, Amenities, Rent Gap, Social, Housing), it should be mentioned that the strength of GIS in this aspect is enhanced by its ability to integrate all of the operationalizations of the measures both analytically and spatially, as each set of the data is linked to common, discrete spatial locations or units.

      The real strength of GIS in this study, however, comes in its ability to analysis and display data at a number of different scales accurately and reliably. This is a method that seems largely absent in most of the literature on gentrification. It should be noted that though scale is most often described as the level of geographic detail (Goodchild & Proctor 1997), scale is being used here to reflect the level at which analysis is being conducted, which in turn reflects the scale of the data on which the analysis is based. The scales of data present in this study include lot level, for the land value assessment, urban amenities and lot vacancy; sub-area level, for social and housing data; and census tracts level, for social and housing data, and census subdivision level for the social and housing data. Analyzes were conducted at the lot level, block level, sub-area level, census tract level and sub-division level.
      These analyses at different scales were done essentially through aggregation of data to a coarser scale. Therefore, no analysis was done working down from a coarse scale to a finer one. The reason for this is the obvious problems associated with making specific observations based on general trends (i.e. the ecological fallacy). However, there are problems associated with the aggregation of data to a coarser scale as well, namely - that generalizations reflect a loss of information (Goodchild and Proctor 1997). Taking this into account, all analyses was conducted and displayed at the finest scale possible to maintain the level of detail of the information, while broader trends were analyzed and displayed at coarser scales to facilitate more general comprehension of the trends present. Reflecting the vision of Anne Raus (1998), an attempt was made to create a process by which derivations of multi-scale analyzes could be created at an appropriate scale for the end products required.
      Conducting analyses at different scales also made it possible to detect and evaluate the processes and effects of gentrification at different scales. That is, though a particular sub-area may show little gentrification, specific blocks or portions of that sub-area may show a great deal of gentrification. These trends would be missed if analyses were only conducted at the sub-area level. This becomes particularly important when different interest groups try to make claims or base decisions on the findings of such analysis. The different scales give a greater and broader understanding of the processes at work.

      GIS also lends itself well to the study of gentrification as it allows visualization of the spatial component of the processes at work. In examining the visualization strengths of GIS in this study, a differentiation between "private visual thinking" and "public visual communication" will be made (as per DiBiase cited form Kraak 1999).
      The strengths of enhancing understanding through visualization are well documented; however, the private visual understanding of the information in this study is most enhanced from the ability of the GIS to display and overlay multiple analyses at once. This aids both in an understanding of the relationships of the analyses at different scales and the relationship of the analyses between different measures of gentrification.
      However, the strength of visualization are perhaps most important in the component of public visual communication. Information empowers people both to make decisions and support claims. It was one of the stated goals of this project to make the information accessible to all possible groups. The visual nature of maps, graphs (etc.) make the results of the analysis in this study accessible to a broader range of people. In fact, part of the direction of this study, provided by the Carnegie Community Centre, was to supply information at a scale relevant to the community and in medium that was useable outside the academic community.
      There are also problems associated with using GIS to measure gentrification. First, the study of the gentrification falls under the rubric of the social sciences. However, GIS is a product of the positivist epistemology and facilitates a positivist approach to analysis in the social sciences at the expense of a more post-modern approach (Lake, 1993). This fact forces an acknowledgement of the ways in which the positivist tradition has been integrated into this analysis, and to assess if this is at the neglect of other relevant epistemologies. Considering gentrification is linked to social change in an area, as well as increased land values and sales, the process is in many respects, quantifiable. These quantifiable attributes were predominant in our analysis. The use of GIS allows an analysis of gentrification at different scales and reveals patterns that may not otherwise have been decipherable. However, we need to reflect upon what other factors are important in gentrification but are not directly measurable, and thus not predominant in this project. For example, drug use in the DTES, and fears that gentrifiers may have about moving into an area of high drug use are not easily quantifiable in a GIS. In this project we have made a deliberate attempt to talk to community organisations and the Vancouver City Hall to assess their views on gentrification. The interpretation of our results also required us to spend time in the downtown eastside to gain a sense of the area. These factors are also important to our results but are not easily represented in a GIS. The epistemology of GIS, its privileging of scientific information, limited the types of analysis we could perform using GIS to assess gentrification, but at the same time allowed the recognition of patterns and trends that may not have otherwise been decipherable.

      There are also theoretical problems associated with the way in which GIS operations and representations tend toward discretiaztion, which can only reinforce the binary way in which gentrification has come to be represented. Lees (1996) brings up a number of problems with what she terms "gentrification as sites of difference, as dualisms, as binary oppositions." These problems include an exclusion of the other others (i.e. only the dominant players are represented), a loss of the mobility of meaning (i.e. static definitions that don't allow the construction and reconstruction of what gentrification means), and a tendency toward polarity (i.e. ignoring the middle ground of the processes and effects of gentrification).
      An example she uses to illustrate gentrification as a site of difference reflects some of the problems associated with our use of GIS to measure gentrification. She points out the common use of the binary "inner city - suburb". This binary is reinforced in this study, as it concentrates on the downtown eastside and draws distinct boundaries around it. Information and analysis is limited to the coverage with which it can be linked spatially. Though it is not the intent of this study, there is therefore the implication that gentrification is either not present or not important outside the discrete, arbitrary boundaries of the coverage.
      Conversely, this study's use and evaluation of multiple definitions and measures of gentrification does address somewhat the loss of mobility of meaning referred to by Lees. Though each measure is being used, it is not taken for granted that each measure will represent the processes of gentrification. Therefore, a goal of this study is to reconstruct a number of valid operational definitions of gentrification. However, ultimately all these definitions are based on literature which emphasizes gentrification as a site of difference, and will therefore analysis and display gentrification as a site of difference (aided by the discrete nature of the GIS).

1 This positivist view of GIS is represented by The World Bank and other government funding bodies, which regularly require a GIS component as a funding prerequisite to support decision making and maintain large products (Wilson 1997).

2 This is not the only example of GIS being used to empower the community. The South of Market community in San Francisco has developed "a dynamic and interactive GIS-based living neighborhood map" as both a "grassroots planning effort to control gentrification" and as a tool to "assist people find commercial space, find a job, or arranging cooperative buying collaborations with neighboring merchants."