A few weeks ago, I and roughly 8,000 other geographers attended the annual American Association of Geographers (AAG) meeting in Washington, D.C. While it can be exhausting--AAG has dozens of sessions going on at any given time--these meetings are a great chance to see friends and colleagues and meet new folks whose work I’ve only read or who I’ve only met online. (Despite the platform’s very real problems, I personally have benefited a lot from participating in #academictwitter).
One moment that stuck out: I was talking with Peter Johnson, a faculty member at the University of Waterloo, a morning reception hosted by the Digital Geographies Specialty Group. Peter does great work with open data and governance. For example, here’s one of his recent articles on the costs of open data, including the ways it subsidizes private enterprise and corporate influence on policy. Over the last decade, there’s been a strong push for open data initiatives across multiple levels, from cities up through international bodies such as the UN, which makes this work particularly salient.
Companies such as ESRI and Socrata have created platforms for hosting and sharing these datasets, and the rhetoric around these tools emphasizes transparency and community engagement. Socrata’s page, for example, references a goal of “fully connected communities,” while ESRI touts its “two way engagement platform.” In my classes, I’m particularly fond of letting students analyze NYCOpenData’s records of yellow cab taxi trips, including more than 100 million trips with details down to the tip given for each one.
Peter’s work, along with many others including Renee Sieber, Muki Haklay, Rina Ghose, Taylor Shelton, and Rob Kitchin, has examined how these projects play out on the ground, focusing on whether they live up to claims of citizen engagement and empowerment. As one might expect, results have been mixed. The people most likely to use these data are the ones with the education, training, and expertise to do so--a fairly select group. In my Community GIS class, I use this article on Data Driven Detroit as one example of this dynamic, where open data records on housing only strengthened investors’ ability to buy up vacant property.
The alternative model presented in that article is one I’ve been thinking through as well, community-based projects that facilitate residents’ ability to interact with and make meaning from public data. I asked Peter about this dynamic in our conversation, and he mentioned a project conducted by the Canadian government where trained staff would work with remote rural and indigenous communities, helping them interpret census and other government data and understand their relevance to local concerns. In recent years, the Canadian government has increased the online availability of these data, but it has cut the number of trained staff who can work with local communities. In effect, open data portals replaced these staff, providing more “access” to data but curtailing the work needed to understand and interpret it.
Recent developments in both open source and proprietary software have provided a number of tools for community-based data collection and open data for government records. But, as Alex Orenstein said at our recent community geography workshop, you also need to “check yourself before you tech yourself.” These platforms provide interfaces for accessing and visualizing these data, but they cannot fully replace the important work of helping community members articulate how the data may (or may not) match their own experience.
I’ve been thinking about this in light of my now years-long work with Georgia communities through the Georgia Initiative for Community Housing. Along with my colleague Kim Skobba, I have been helping develop a toolkit for community-based housing assessments, one that uses free and open source software such as OpenDataKit and RStudio’s Shiny platform. These technological tools make it possible for even small rural communities to collect and map out detailed data on individual housing conditions, identifying common issues and facilitating outreach to specific property owners. At the same time, communities struggle with what to do with these data once it’s collected beyond simply noting patterns on the map. Similar to Taylor Shelton’s work in Lexington, I’ve been thinking about ways to work with communities to visualize drivers of problems identified through these data. By talking about landlords, zoning, and other historical factors, we can beging to talk about the problematic history of blight as a metric and its ramifications for community development.
This isn’t work that can be solved by a platform or visualization software. It involves time and “soft skills”--listening, thinking, reading, and many conversations, before the work of data collection even gets started. Community members themselves often want to jump right into the technology, and so it is sometimes difficult to communicate the need to move more deliberately. This is hard labor, but as folks working in public participatory GIS (PPGIS) have long emphasized, it’s crucial to fostering sustainable, just change in communities.
Jerry Shannon is an Assistant Professor at the University of Georgia in the Departments of Geography and Financial Planning, Housing, & Consumer Economics. He is the director of the Community Mapping Lab.
"We do not have weapons, but now we have GIS to protect our territory. We plan to conserve our natural resources for present and future generations through the maps, our maps."
Domingo Ankuash, Shuar Indigenous Leader
During the last five years, campesinos* (peasants) and indigenous people from Southeast Ecuador have started to use maps as a powerful tool for protect their territory against mining companies. Local people believe by mapping their biocultural ecosystem services and territorial boundaries, they are avoiding being cheated by mining companies or by the government. Between Amazon and Andes Ecuadorian region, there is located El Collay Territorial Association, that it is set up by campesino and Shuar indigenous population. 15 years ago, the Shuar communities were the first ecuadorian indigenous population in Ecuador to used participatory GIS. In order to go deeply into campesinos and indigenous Shuar's GIS experience defending their territory, I participated in some community participatory mapping workshops in the El Collay Territorial Association, for the past four years . In this article, I will talk about methodological experiences I have gained over these years and I will show a few maps about biocultural services identified by local communities actors.
El Collay Territorial Association is a political and administrative entity formed by six local municipalities. All six are autonomous, decentralized governments: Paute, Gualaceo, El Pan, Chordeleg, Sevilla de Oro and Santiago de Méndez. This Territorial Association is in the northeastern corner of the Azuay Province in Southern Ecuador. One of the most important inhabitants of this Territorial Association is the Shuar indigenous people. They represent one of the most prominent ethnic group in the Amazonian Region, with around 35,000-40,000 living mainly in the Ecuadorian provinces of Pastaza, Morona Santiago and Zamora Chinchipe, in the southeast of the country. Since 2000, Shuar’s ancestral lands have been assigned for copper mining concessions “for the sake of development”** and, as a result, indigenous communities have suffered persecution and violence. The expropriation of the Shuars’ lands and resources has forced the indigenous community to fight off industrial-scale copper mine and oil extraction and threats to their lands and way of life.
The Shuars struggle to protect their land despite peaceful marches, legal actions, and an international pressure campaign. However, in the last ten years, the Shuars have turned to mapping as a strategy in this effort. Four years ago, as part of my research process to obtain my master’s degree, I started working with campesinos and Shuars indigenous communities. In several conversations, local people pointed out that it is a need to establish community mapping workshops that allow them to delimit their ancestral territories and recognize biocultural services. Later and thanks to local governments and some Shuar leaders support, I managed few meetings and workshops where we gathered an important group of participants that contributed significantly to the project.
My experience in Participatory GIS and Indigenous communities
First, I had some meetings with local actors to explain them the objectives of this project and how Participatory GIS methodology works. There were around 30 participants between indigenous and peasants leaders, that they came from each small villages of El Collay. In a second meeting, I asked the community leaders to make a sketch of their nearest territory, that is, neighborhood or Municipality. Local people had to identify important cultural and natural sites. They used colors, pins and stickers to identify the different types of assets in the community. Once, first workshop finished, I realized that there were major criteria to characterize each small village. Therefore, we used the largest number of responses and create biocultural categories and then units of ecosystem services. As a result, we identified together the categories for important values by local people (i.e. arts, crafts and sacred sites). This outcomes helped me out to make the first map (fig 1). In addition, those decisions over their territory allowed me to integrate each biocultural category as a landscape units in order to give each small village a biocultural unique identity (see fig 2).
The last workshop, I used a local map. In order to avoid bias about indigenous boundaries, I used data from the National Institute of Statistics and Census. I asked them to locate conflict points, that is, environmental, social and cultural problems affecting their territory and changing the landscape. According to local people, the principal territorial problemas are mining companies activities and deficiente local governments administrations. Third, once I finished workshops, I moved to geocoding some biocultural assets exposed by local actors, using ArcGIS 10.5.
Finally, I made two maps about biocultural assets and biocultural ecosystem services. The first map (see fig 1) represents what local actors considered the five essential biocultural elements in their land: archeological sites or sacred sites, traditional skills, food heritage, immovable heritage, and forest (natural elements). Using the biocultural assets map base, I made a map about ecosystem services. So, I grouped characteristics of each small community and made ecosystem services landscape. However, each category can overlap each other, since each village could has all biocultural category in its territory. There are five landscape units: El Collay Forest, Ancestral Knowledge, Sense of Territory, Forbidden Place and the Heritage Food Place (fig 2). The criteria for the cultural ecosystem services classification are the following:
El Collay Forest - This area represents an important element for the El Collay inhabitants, since in addition to be a zone of protection, it is considered a sacred space.
Ancestral Knowledge - It refers to all the knowledge that has been acquired from generation to generation. As for example, the elaboration of crafts, textiles, food preparation, among others.
Sense of Territory - It implies a closeness and an intimacy that is a product of experience, history and time. It demands that people develop an aesthetic sensibility that one gains only when population lives in one place for a long time. This service is mostly located in the Shuar indigenous territory, because for them the sense of territory is linked to the land where their ancestors were born and where future generations will belong.
Forbidden Places - They are sacred places and therefore forbidden to carry out any human activity against natural resources.
Heritage Food - They are characteristic places at local and national level for their gastronomy.
Conclusion and Future projects
There is still much left to do. I plan to continue working over this process in this summer 2019, using counter-mapping approach. The main future objectives are to map sites at risk and conflict, and resilience and resistance areas lead by local communities to mining companies impacts. In conclusion, the maps that have been generated from this participatory GIS process with indigenous and campesinos communities, provide a new way of understanding the world from different worldviews. PGIS maps also demand the integration of these new conceptions of territory, in local territorial planning and national protect biocultural heritage politics of ancestral populations.
*I use campesinos in Spanish because the word peasants has a negative connotation in English language
**This phrase was part of the neo-extractivism speech by ecuadorian government, during 2014
Estefania Palacios-Tamayo is a PhD student in Geography at the University of Georgia. Her research focuses on biocultural landscape dynamics for territorial planning and conservation of local heritage.
As the saying goes: you can’t have your cake and eat it too. In a project for the Community Mapping Lab, I worked with a representative for the United Way of Northeast Georgia’s 2-1-1 program to develop a web application that allows for visual interaction with services offered in Athens, Georgia. Along the way, I had to weigh the pros and cons such as reproducibility and ease of use of different web application development software. I found that it was impossible to have everything I wanted in a single web framework for software development.
The United Way of Northeast Georgia is a non-profit organization that aims to ensure access to quality education, financial stability, and healthy lifestyles for residents of its service region. They work with stakeholders from different sectors such as schools, businesses, financial institutions, and local governments across the state to promote and improve community conditions. Their 2-1-1 program offers residents the opportunity to speak with or text a representative of United Way about services they may be looking for.
In the fall of 2018, I worked with a representative for the United Way’s 2-1-1 program to develop a web application that allows users to locate services offered in Athens, Georgia through a map interface. Although the call line offers callers the ability to speak with someone who is knowledgeable about the services offered, a web application allows users to explore services at their own pace and see details about the services up front as opposed to hearing about them over the phone.
The web application had 5 important requirements:
I looked for ways to meet the requirements listed above, managed data from United Way’s database, and researched the best way I could develop a web application. I did this through an internship with the Community Mapping Lab which actively works to provide students with the opportunity to work with community members as well as apply their knowledge to solve practical problems.
I chose to use ESRI’s Web AppBuilder to develop my web application because it was the best tool for me considering my skill set and complete lack of coding experience. I was able to develop a web application with unique visualization features and useful filtering tools. With this app, the users could explore the agencies in Athens, search for service by language availability, visualize the route(s) agencies are on, access contact information, and determine eligibility.
One of the advantages of my web app is that all agencies which offer services for the general public are listed on its map. Unlike Google or other search engines, the web app shows all the services available from all service categories at once. Google is more likely to display agencies whose names match the keywords input in the search bar. Some of the agency names are not representative of all the services they offer, and because of that, a search engine can be limiting. Additionally, a search engine may not offer as much information as clicking on one of the service icons on my web application may offer. For example, by clicking on a service icon, I can see all the information shown in figure 1, and more.
In a previous blog post, Jiaxin developed her own web application using the Leaflet API to map areas in the state of Georgia that had high percentages of population eligibility for UGA SNAP-Ed programs. Like her, I wanted to develop a web application that allowed users to explore services and visualize eligibility geographically. I know about the importance of using open-source software for reproducibility of a project. I know that ESRI products are expensive to license and thus difficult to access for those who do not have hundreds of dollars to spend on licenses.
So why did I choose the Web AppBuilder? In the end, we have to pick our battles. My app may not be easy to reproduce, but it had the basic features I needed. I wrote instructions on how to download data from United Way’s internal database. I used R to write scripts to prepare the data I had extracted. Even though I was not able to complete this entire project in a way that promotes accessibility to the entirety of my work due to limitations in my knowledge, I gained the skills that could help me produce a Shiny app in the future. It is interesting to consider how “open” open source data or software is if it requires a significant amount of time, knowledge, and experience to be able to use it.
Some features I wish I could have expanded on with ESRI’s Web AppBuilder were fonts, the flexibility in positioning of certain elements and widgets, and further customization of widget features and capabilities (Figure 2). For example, the text below the filters blended in with the background of the filter widget, and I wish I could have chosen a darker color for the text to help it stand out. Additionally, I would have liked to have the legend be on the other side of the web application to allow users to more easily find that button. Finally, I had a difficult time with the filter feature since it only took data in the wide format instead of the long format. These are the sorts of limitations that we can experience when we don’t code our own applications.
In conclusion, in developing a web application for United Way, I made the decision to use ESRI’s Web AppBuilder over R Shiny or Leaflet. There were benefits to ESRI that made developing the web app easy, but I missed out on the flexibility associated with coding my own web application. I struggled with the limits of the ESRI’s Web AppBuilder but learned valuable new skills that I can use to promote more reproducibility of my work in the future.
Aileen Nicolas is a fourth year Geography major at the University of Georgia. She will be pursuing her Master's degree in Geography starting this fall of 2019 also at UGA.
Research has found that retirement is one of three major time points that the elderly (aged 65 and up) tend to move (Litwak and Longino Jr 1987). The reasons for moving may vary: going to a place with better weather, being closer to family members, going to more affordable areas, going to a place with a slower pace, etc. The moving decision is not only related to individual characteristics, such as marital status, presence of children, education level and more, but also associated with the destination community’s characteristics, including the cost of living, climate, amenities, accessibility, and more (Clark, Knapp, and White 1996).
The United States is part of a global trend of counties facing significant aging populations. With the largest elderly population (aged 65 and over) among all developed countries, the U.S. is projected to double its elderly population in 2060, compared to 2014 (Northridge 2012). By 2030, more than 20% of U.S. residents are projected to be elderly, compared with 13% in 2010 (Ortman, Velkoff, and Hogan 2014). The increasing elderly population and proportion of the population generate questions of where and how seniors will spend their last chapter of life. For seniors who choose to move to a new location, what characteristics of the destination are associated with their move? This blog will focus on the southeastern US state, Georgia, to answer the questions about the migration pattern and the migration-related characteristics of the destination.
Using the Census Bureau American Community Survey (ACS) 2013-2017 data, I looked at the elderly migration within the 159 counties in Georgia. The ACS provides data about how many people moved to individual counties from the counties within the same state, from outside of the state, and from foreign countries with age breakdown. Within the five-year period, there were over 47,000 elderly people settled in Georgia, with 24,120 from other states or abroad and the rest moving within Georgia. Figure 1 shows the patterns that the elderly migration in general favor some particular areas, especially the north side of Georgia, including the Atlanta region (29 counties defined by the Atlanta Regional Commission. Other popular destinations are Macon, Augusta, Columbus, Savannah, and other coastal regions. The distribution matches up with the total population distribution.
Next, we then took one step further to look at the proportion of migrant population in the total elderly population for each county. This shows how much of the elderly population recently moved in, and helps to determine what places attract the seniors more after controlling the base population. Counties with high in-migration rates are labeled by name in Figure 2. In general, counties on the south side, especially some edge or neighboring counties of the Atlanta region are with the highest proportion. It may be a result of a balance of affordable living and convenience. The coastal area also attracts seniors. Long County is part of the Hinesville-Fort Stewart Metropolitan Statistical Area, and Mclntosh is included in the Brunswick Metropolitan Statistical Area.
We also apply the multiple linear regression to identify those sociodemographic characteristics and other variables most associated with high migration rates. We included the long-term care facility capacity (number of beds), total population, hospital availability, percent with disabilities, low education (less than college or equivalent) percentage, low racial diversity (using the entropy of race diversity), and more (see the full list of variables in the note). Among all four statistically significant variables (significant level < 0.01), the hospital availability has the biggest positive effect on the migration count, followed by the median house value and total LTC capacity, while the crime rate has a negative influence on the dependent variable. The disability proportion is significant at 0.1 level with a negative impact on migration. Those variables explain about 92.2% of the dependent variable, the raw count of migration population (Adjusted R2 = 0.922). By understanding the associated characteristics of elderly migration, local government and policymakers can better plan the regional development to meet the needs of elderly migrants.
More analysis can be done to separate interstate and intrastate migration since they may be attracted by different regions and different aspects of the destination. Including other variables, such as tax structure of the destination, may add more flavor to this as well. However, it is important to keep in mind that there is information not in the map or available data, thus, there are known unknown parts in this research. Data can only tell the story about numbers, and it will be necessary to have some community engagement to better understand the situation. For example, I will talk with seniors about their needs and concerns in some neighborhoods. As the starting point of my dissertation, these ideas can lead to further dive into the reasons that lying behind these patterns.
The considered independent variables for each county include: total LTC facility count, total LTC capacity (total LTC facility beds), LTC facility beds per 1,000 elderly people, total population (at 1,000), total elderly population (at 10,000), elderly population proportion, hospital availability (hospital count within 10 mile buffer of that county ), male proportion of all age, citizenship proportion of all age, disability proportion, low education (less than college or equivalent) percentage, labor force participation rate, wealthy proportion (ratio of income at or above 400% of the poverty threshold), poverty proportion (ratio of income below 100 percent of the poverty threshold), entropy of diversity, percent rural, crime rate (per 100,000), and the median home value (at $1,000).
Clark, D. E., T. A. Knapp, and N. E. White. 1996. Personal and location-specific characteristics and elderly interstate migration. Growth and Change 27 (3):327–351.
Litwak, E., and C. F. Longino Jr. 1987. Migration Patterns Among the Elderly: A Developmental Perspective. The Gerontologist 27 (3):266–272.
Northridge, M. E. 2012. The strengths of an aging society. American journal of public health 102 (8):1432.
Ortman, J. M., V. A. Velkoff, and H. Hogan. 2014. An Aging Nation: The Older Population in the United States. http://bowchair.com/uploads/9/8/4/9/98495722/agingcensus.pdf.
Author Xuan Zhang is a Ph.D. student at the University of Georgia in the Department of Georgia. Her research uses GIS to investigate the elderly migration and long-term care facility accessibility issues under the umbrella of Health Geography.
Imagine you are a project officer with an international development agency. You are charged with assessing the water resources, quality of access, and management-related challenges of a rural community in Eastern Tibet. You are provided substantial funds by your organization to facilitate a Participatory Rural Appraisal (PRA), an increasingly common method to involve community members in planning, knowledge exchange, and decision-making to address perceived local problems.
You, your development project team, and volunteers from the community work together on a map to document land and water management issues in the region. This map will be a key product for future planning with your agency and will be included in the annual report. One community mapping participant remembers seeing twice as much winter snow accumulating along the mountain ridgeline, just 10 years ago. You put it on the map. Another participant notes the declining abundance of suitable alpine grasslands for their herds of sheep and yak. You put it on the map. Every participant remembers the day they saw a dragon ascending into the sky near a glacier-fed stream. You pause. You don’t put it on the map.
For many Tibetan Drokpa, dragons are real. They’ve seen them. In the positivistic world of western science, a legacy that deeply informs our governmental, non-governmental, and academic institutions, dragons belong to folklore, to myth, and to metaphor.
As makers of participatory maps, I think we need to map the dragon. Beyond metaphor. Beyond folklore. Dragons have a place in this map because they exist in the shared cultural worlds of the map makers. Drokpa knowledge of dragons does not need a western positivist knowledge filter. It does not need to be validated by scientific objectivity, or confirmed under foreign protocols of “data” or “evidence”.
As makers of participatory maps, I think we need to challenge the space of assumptions associated with other cultural realities. Beyond fiction. Beyond myth. I think we need to interrogate the epistemological foundations of our institutions, and recognize that the edge of our maps of knowing may be the beginning (or center) of somebody else’s. After all, there are no neutral ways to represent “reality” on a map; any “reality” depicted is largely informed by ones’ intellectual and cultural predecessors.
In “Dragons, Drokpa, and a Drukpa Kargyu Master”, Diane Barker, recounts testimonies of those who have seen dragons in Tibet, positioning them alongside stunning depictions by Choegyal Rinpoche. Her article makes me pause. It forces me to re-consider the perspectives and worlds deemed legible in academia, and the constraints of the technologies we employ to help compartmentalize and categorize our complex world. Maps and map making can help us to visualize spatially complex interrelationships between social and natural forces. Relationships between water scarcity and elevation, for example, or grassland abundance and shifts in human land-use over time. Maps produced with Geographical Information Software (GIS) can take us even further and help us to measure these complex interactions by experimenting with scale-dependent variables and spatial layers. GIS, as such, is a powerfully important spatial toolset for map making. It is, however, worth recognizing both its technical and epistemological constraints.
Rundstrom (1995) suggests that “GIS technology, when applied cross-culturally, is essentially a tool for epistemological assimilation, and as such, is the newest link in a long chain of attempts by Western societies to subsume or destroy indigenous cultures”. Perhaps it is, in certain contexts. This point is considered in depth by Dr. Kenneth Bauer (2009) who notes that embracing GIS, and the worlds we create through mapping, means embracing a “mode of thinking”.
Bauer argues that “one’s knowledge of the environment lies not in the ideas in our heads but in the world that our predecessors reveal to us”. If our intellectual predecessors are international development officers, who focus on the material and societal needs of the “developing” world, not only will our maps reflect these priorities, but the edge of our maps will hold epistemologically particular metaphorical dragons. If our predecessors are geospatial scientists, many of whom focus on the scalar dynamics between social and natural systems, the edge of our maps will hold equally specific metaphorical dragons. And if our intellectual predecessors are nomadic Drokpa herders, the center of our maps might include real, non-metaphorical dragons. Then, the edge of our map, the boundaries of our known world, may hold something entirely different. Something as foreign as Participatory Rural Appraisal (PRA). Something as foreign as “development”, “geospatial science” or “conservation”.
“Dru gu Choegyal Rinpoche's painting of a dragon sucking up water from a stream in Tibet, 2012” Dragons, Drokpa, and a Drukpa Kargyu Master
In the end, local Drokpa knowledge of dragons may not be commensurate with western knowledge mapping traditions; spatial frameworks that we, as academically-inclined map makers, can know and interpret: 2D, cardinal direction, cartographic maps. Unless we expand our definition of “map”, perhaps Choegyal Rinpoche’s paintings can simply remind us that the edge of our mappable world does not mean the world’s end. Certain cultural realities and worlds of knowing may simply be invisible to us, unless we choose to radically challenge our own preconceptions, trusting and supporting the deeply held realities of our community mapping partners.
Indeed, there are different worlds in each of us. There are also shared cultural worlds that invisibly govern our institutions, design our technologies of visualization (i.e. GIS), and condition what we deem “mappable”. What if, when reaching the boundaries of our own mappable knowledge, we consider how to support other worlds of knowing in our work. We must ask ourselves how we diminish other worlds of knowing by assimilation into our own. Perhaps we can recognize our privileged positionality as map-makers and practice radical epistemological reflexivity, challenging our categories of “data” and “evidence” to produce new maps. Maybe we map the dragon. As mappable as increasing annual glacial snow melt. As mappable as declining range and extent of alpine grasslands.
But can we truly re-consider and re-evaluate our core perspectives, biases, and beliefs during this process? The worlds we know and occupy? Perhaps not completely. What’s more, would such radical reflexivity necessarily dis-empower our scientific perspective in a post-truth world? I don’t think so. I think it broadens our capacity as social scientists to engage in and practice epistemological humility rather than epistemological assimilation.
In my research in Bhutan, known as the Land of the Thunder Dragon, we use participatory mapping as a medium to talk about spatially-explicit, place-based deities, spirits, and divinities that reside and preside over forests, lakes, trees, rivers, and mountains. These more-than-human beings have significant bearing on the ways people make land-use decisions, and conceptualize foreign concepts of development, conservation, and natural resource management. By including dragon sightings in the Drokpa community map, without pause, without filter, our Participatory Rural Appraisal (PRA) will not simply pay lip service to aspirations of “participation”. Instead, the map will be a better reflection of the different worlds that reside in each participant, and more representative of the worlds inherited by our intellectual predecessors.
When the map is complete, it will inevitably be incomplete. Maps will always hold unknowns & uncertainties, assumptions and biases, at their edges. If our aim is to challenge these assumptions, we must put the dragon on the map. Beyond myth. Beyond metaphor. We must challenge who has the power to define the “we”: the voices and viewpoints at the table. A map of this type, however partial, may be a stepping stone to increasingly egalitarian representations of our respective cultural worlds: as academics, international development officers, geospatial scientists, and Drokpa herders.
David Hecht is a PhD candidate in the Integrative Conservation & Anthropology program at the University of Georgia. His research explores the intricacies of sacred landscapes and lived religion in relation to community-based conservation programs for priority bird species in Bhutan. Follow him on Twitter at @davidmhecht.
We are more than a decade removed from the national foreclosure crisis. Homeownership rates languish near all-time lows. Housing prices have surpassed pre-Recession highs. And a crowd of corporate actors have entered the single-family housing market in the wake of more than 9 million foreclosures during the Great Recession. Yet, there is limited research on the intra-metropolitan geography of large corporate landlords (Raymond and Moore 2016, Abood 2017).
In this blog post, I map the geography of one such corporation, Invitation Homes, in Gwinnett County. Specifically, I discuss some of the demographic trends in ten census tracts where Invitation Homes owns more than 1,000 properties. I find these neighborhoods are becoming less white, more Black, and exhibiting a decline in homeownership, offering a few examples of how the Great Recession continues to affect housing markets in suburban Atlanta.
Single-family corporate landlords are one example of a broader trend in post-Recession housing markets. The single-family rental (SFR) rate in Atlanta (i.e. the number of single-family homes occupied by renters compared to the total number of occupied single-homes) increased from 11.5% to 19.2% between 2006 and 2016, one of the highest increases among large metropolitan areas (Immergluck, 2018). Immergluck suggests the growth of SFRs may expand the housing options and neighborhoods available to renters in Atlanta. The geographic concentration of land by a single corporation, however, creates problems for jurisdictions at multiple scales and complicates assumptions about who is benefitting from the current housing price recovery.
Invitation Homes: What and Where?
Invitation Homes is a subsidiary of private equity giant Blackstone. It markets itself as offering quality homes in “desirable neighborhoods across America”. Classified as a single-family Real Estate Investment Trust, Invitation Homes is part of an emergent group of corporate landlords active in the single-family rental market. Invitation Homes owns 12,500 homes in Atlanta – their largest market. They are active in 19 counties in the Atlanta metropolitan area.
In this post, I focus on Gwinnett County, where they own more than 3,000 properties. According to Dr. Elora Raymond’s analysis in the popular Atlanta Studies blog, Invitation Homes owned 983 properties in Gwinnett as of 2013 (Raymond and Moore 2016). Thus, Invitation Homes acquired more than 2,000 units between 2013 and 2018.
Map 1: Total Invitation Homes' properties by neighborhood
Of their more than 3,100 parcels, 1,147 are concentrated in just ten census tracts along the county’s eastern border. In Map 1 above, you can see these neighborhoods near Dacula to the south of Loganville. There are 113 census tracts in Gwinnett County. Meaning, more than 35% of their Gwinnett County portfolio is concentrated in fewer than 10% of the census tracts. Additionally, these tracts contain only 15.5% of the county’s population.
Map 2: Invitation Homes rental market share by neighborhood
As one attempt to, “uncover stubbornly persistent blind spots in geographic research,” I compare the number of Invitation Homes properties to all occupied rental housing in Map 2. Invitation Homes owns more than one out of five rental units across four contiguous census tracts in the southeast corner of Gwinnett County.
The demographic changes happening in these census tracts suggest IH neighborhoods are becoming less white, more Black, and exhibit an above average but declining homeownership rate. Based on data from the U.S. Census’ American Community Survey, the median Black share of the population of these tracts increased nearly ten percentage points from 36.6% to 45% in the past seven years, while the median white share of the population decreased 11.7 percentage points, from 54.3% to 42.6%. Finally, the average homeownership rate declined roughly five points from 85.1% to 79.9%.
As a diversifying suburb, these trends aren’t necessarily surprising to anyone familiar with demographic changes in Gwinnett County, but the geographic concentration of land ownership by an institutional investor is a post-Recession reality that impacts communities across the Atlanta metropolitan area, many of which are dealing with a lack of affordable housing. The similar trajectories of demographic change among the IH neighborhoods along Gwinnett County’s eastern edge suggests that the concentration of corporate landlords is an important component in evaluating the post-Recession housing geographies of Atlanta. As a part of my dissertation, I’m thinking about how landlords at this scale can manipulate housing markets, shift demographics, and transform metropolitan spaces (maybe a future post!)
Abood, M. 2017. Securitizing Suburbia: the financialization of single-family rental housing and the need to redefine risk. Massachusetts Institute and Technology. Department of Urban Studies and Planning.. http://hdl.handle.net/1721.1/111349
Immergluck, D. 2018. Renting the Dream. The Rise of Single-Family Rentership in the Sunbelt Metropolis. Housing Policy Debate. DOI:
Raymond, E. & Zaro-Moore, J. 2016. Financial Innovation, Single Family Rentals, and the Uneven Housing Market Recovery in Atlanta. Atlanta Studies Journal.
Taylor Hafley is a PhD student in the Department of Geography at the University of Georgia. His dissertation focuses on how single-family REITs influence urban-suburban change.
Jerry Shannon and CML members
The margins of medieval European maps are home to some fantastic creatures. These beasts were based on actual accounts by sailors, demonstrating the ways mapmakers relied on first hand accounts of regions that (at least for them) remained unnamed. This article, published by the Smithsonian in 2013, details a few of them: an ichthyocentaur (human, horse, and fish), a sea pig, and a lobster several times larger than the ships it swallowed.
Popular legend holds that the phrase “Here Be Dragons” (or “Hic sunt dracones”) was added to some of these ancient maps in regions deemed particularly dangerous. While probably apocryphal, the phrase remains in the lexicon of our cartographic imaginations, appearing in fantasy novels, multiple films, and even code for the open source Firefox web browser. In many of these instances, the phrase refers to areas where the world becomes unfamiliar, at least to sailors and mapmakers. These paper dragons are are a reminder to practice epistemological humility, recognizing the limits to our ability to know and name the world.
In the current era, big data and informatics promise a panoptic understanding of social and environmental processes, where algorithms and massive datasets can supposedly help us see into every corner of the world. We--members of the Community Mapping Lab--hope to use this blog to uncover stubbornly persistent blind spots in geographic research, dragons that underscore the continued partiality of our knowledge. Contemporary maps may often draw from larger and more complex datasets than these medieval efforts, but this may simply mean that the dragons--unspoken assumptions, biases in the data, extractive research practices--are more artfully hidden.
Adapting Haraway’s famous phrase, maps are always a view from somewhere. Dalton and Mason-Deese similarly describe an “and, and, and…” approach to mapping, resisting a single authoritative perspective in favor of “continual questioning and the production of alternative knowledges” (p. 460). By working through multiple ways to frame and map the world, such as the the Counter-cartographies Collective’s campus disorientation guide, we highlight the useful, if limited, insight each map provides. We study maps understood both literally (e.g., online and print maps) and metaphorically (e.g., theories of community development), in all cases understanding ways these name and produce the world.
Our group of authors is, at least initially, comprised of students and faculty at the University of Georgia, and our perspectives are inevitably shaped by our daily lives within that institution. This blog is, in part, an effort to make that explicit in our research--to be reflexive, in scholarly terms. Just as early cartographers drew on first hand accounts from sailors, we also develop partnerships with local communities to collaboratively develop alternative ways of mapping the world. We work toward research practices that are inclusive of marginalized groups, reveal the social processes that shape inequality, and promote social and environmental justice. We critically examine the conditions that produce geographic knowledge, placing maps in their social and historical context.
More specifically, the posts on this blog will cluster around four core themes. First, we are interested in community engaged and participatory research practices and their use in both spatial analysis--maps and number crunching--and qualitative research--interviews and participant observation. Second, we critically examine how gender and race matter to the ways research in geographic research is conducted, drawing from work in feminist and black geographies. Third, we explore new forms of data collection and alternative tools for analysis and scholarly conversation. This includes the ways free and open source software can be used within geographic research, the use of volunteered geographic data (VGI) and citizen science as sources of knowledge, and the potential of open science practices--such as shared code, data, and publications--to encourage transparency, public engagement, and reproducible research. Lastly, we highlight the ways that maps and other forms of geographic research are employed to support social activism and promote progressive public policy goals.
Our posts will vary in format, including reports from our own research, reflections on recent work by others, reports from conferences or workshops, and walkthroughs of new tools or methodological techniques. While our posts will often explicitly mention mapping and GIS, they are seldom just about these tools, and many of us regularly use multiple methods in our research. Through our posts, we hope to spur public conversation about maps and mapping within and outside of the academy.
In sum, Here Be Dragons is a blog focused on emergent ways of mapping the world, ones that are more participatory and inclusive. It’s a blog about the ways geographic research makes our world and its potential role in activism for social and environmental justice. Just like the maps we make, we’re not sure exactly where this blog will go, but we welcome everyone along for the journey.
Jerry Shannon is an Assistant Professor at the University of Georgia in the Departments of Geography and Financial Planning, Housing, & Consumer Economics. He is the director of the Community Mapping Lab.