An Ecology of Technology

October 5th, 2015

Claudio Aporta and Eric Higgs (2005) present the integration of GPS into Inuit life as an example of a greater pattern of technological change on human engagement. I was taught by George Wenzel about the introduction of new technologies into Inuit life and how it affected social and cultural practices. However, this article expands my knowledge of technology as a factor that limits our understanding of the original methods behind the devices. While the Inuit example is useful due to a more spatially and culturally isolated population, the ideas from this text can be expanded to the wider world.

This piece talks about the loss of knowledge, social engagement, and connection with the local environment. We should also ask what do we gain from making our lives easier and limiting interactions with the environment? Do we gain a greater understanding of different information? Do we gain other forms of meaningful interactions? Or is the loss irreparable?

Let’s look at the evolution of human beings; is this just a result of the process – as humans evolve they evolve out of their environment? The evolution of technology is referenced many times but I wished that this piece went in an even more philosophical direction and asked questions about human evolution as well. I think that now, 10 years after this article was written, we can assume that technology has started to merge with permanent human behavioural changes. The authors allude to this by stating; “it is not unrealistic to suppose that [GPS technology] will at some point become so integrated into a larger ecology of technologies that its presence will be hardly noticed. (748)” Yet is this simply the price of evolution? Do we ever look back on a previous period of change and even recognize the loss, or, in our further evolved state just conclude it was inevitable?

I think that in this case GIScience provides hope. I see it as a way to understand the methods behind the technology or to use technology to create new, and potentially meaningful, understandings of the world around us. As the authors concluded, finding meaning in a life full of technology might be more difficult, but it is still possible.


Aporta (2005) GIS, Wayfinding, and the Device Paradigm

October 5th, 2015

The article by Aporta and Higgs examines the shift in Inuit culture from traditional means of wayfinding to GPS based navigating. In an article writing about the shift away from traditional means of wayfinding I was worried that the authors would overlook the fact that Inuit have been open to many technological developments such as the snowmobile or rifle. Therefore it was good that they qualified their argument by first giving a historical overview of Inuit adoption of technology and incorporation into their culture. The article then looks at what the GPS provides, all the obvious advantages, including safety, efficiency, simplicity, and its disadvantage, which is a disengagement with the environment. What the article fails to answer is how important this disengagement is to the Inuit experience of the environment. The article mentions that the allure of technology in reducing labour has usually resulted in more negatives. Even if I agree with the authors’ findings, I’m not sure what the point is other than lamenting a lost era. As they write about earlier, Inuit have always been quick to adopt new technologies. Their economic structures have adapted to resettlement in town, their hunting techniques have adapted to rifles and snowmobiles, their forms of protest have adapted to the internet, and now there wayfinding will change with the adoption of GPS.


The Meaning of Life cannot be found by Global Positioning Systems: Aporta and Higgs’s Satellite Culture

October 5th, 2015

The authors’ sought to shed a light on technology-induced societal changes taking place all over the world, focusing their attention on the Inuit hunters of Igloolik, Nunavut to illustrate to readers the challenges and successes that the introduction of GPS’s within the community over the last decade has had on traditional navigational practices. The authors ultimately attempt to position the situation in Igloolik to society as a whole with regards to our argued “disengagement with nature” as a direct result of increased integration of technology (or as the authors state: “machinery”) within the fabric of society.

Palmer and Rundstrom, geographers, dutifully responded to Aporta and Higgs’ article, reminding the authors that the study of technology, geography, society, and their interactions is not a new concept: GIScience has been working on these issues already for over a decade, and that important nuances tie them all together; nuances that the authors fail to recognize.

What is evident from this piece, is that the athours view GIS as a tool (not a science). They suggest that technology is contaminating “authentic” engagements with our surroundings, voicing “worry” and “concern about the effects of GPS technology”, as they claim it “takes the experience [of fully relating to the activity we perform] away” (745). This is a grand oversimplification, as there are many degrees to which society can and does interact with technology, either passively or actively.

In my experience, the use of a GPS has given me more confidence when hiking in unfamiliar territory, and allowed me to successfully navigate to otherwise hidden natural wonders, thus increasing my interaction with my surroundings in a positive way.

I posit that it is the lack of institutional programs in place that teach traditional Inuit navigation systems that is to blame for the increasing reliance on GPS devices by the younger generations. GPS’s are not easy to learn how to use, as the authors suggest, as it can take months, even years, to understand all the underlying geospatial concepts and how to work with the technology within harsh environments. It is easy to learn to push buttons in a few days, yes, but to master its use, to the level that you would have to master the concepts underlying traditional navigation systems for it to be a “completely reliable” tool, would require, I argue, just as long.

The last line of the article truly highlights its lack of scientific integrity:

“ However, we believe that this fundamental premise is right: if life is lived through devices, finding meaning (personal, social, and environmental) becomes more difficult and engaging with our social and physical surroundings becomes less obvious and appropriate” (746).

Nowhere in the article do the hunters of Igloolik suggest a loss of fundamental identity; all they suggest is that their society is evolving, as do all societies; and that, yes, technology is fallible, but nonetheless important, and, dare I suggest, welcome.


Satellite Culture

October 5th, 2015

Aporta and Higgs use the example of GPS integration into Inuit culture to explore the relationship between humans and modern technology. The introduction of GPS systems into a society that had previously depended on the persistence of traditional wayfinding knowledge (incorporating wind patterns, snowdrift patterns, astronomical observation, animal movement patterns, and other natural phenomena) presented the researchers with a case where a single technology promised to “deeply modify and cause disengagement from a well-established approach […] to the environment” on which the Inuit so closely depend.

The authors invoke Albert Borgmann’s theory of technology, in particular his “device paradigm,” which holds that contemporary technologies (‘devices’) mediate our engagement with our surroundings (and arguably reality itself) by reducing the amount of complex interaction required for their use. The GPS is therefore the “perfect Borgmannian device,” according to Aporta and Higgs, in that it removes the need to engage with local conditions, it’s easy to use, and provides instantaneous results.

The authors reach a reasonable conclusion: that the introduction of new technologies ought to be analysed within ecological, relational frameworks ­that take into account the effects on society that they may wreak. My main concern is that the fundamental reasons arguing in favour of a cautious or even reactionary approach to the introduction of new technologies rests fundamentally on existential reasoning; while ‘enlightenment’ positivism ultimately argues a materialist case. The material and existential consequences of the enlightenment are innumerable, arguably ranging from brutal death machines and concentration camps to the significant extension of the human lifespan and reduction in physical pain, declines in infant mortality, etc. While the introduction of new technologies has helped to lead humanity down the darkest paths in history, I believe that reactions like Borgmann’s are indeed prelapsarian or quixotic, and tend to elevate the importance of abstract types of thought and engagement above the hard realities of material life: is there enough food? Do we have adequate leisure time? And so on.

To return to the question of GPS and the Inuit, there is a telling line where it is postulated that Borgmann ‘would counsel that GPS technology is well deployed as an adjunct to Inuit navigation instead of as the central or dominant device for wayfinding.’ Ultimately, such counsel would amount to nagging based on very abstract notions of value, and would have little place in a harsh arctic environment. While I feel that critical engagement with new technology is essential, romantic associations with the past have little to contribute to the project of liberating people from material hardship. Rather, we should be thinking about how to address the changes technology makes to the distribution of power in society, and how to maximize its numerous beneficial capacities while managing its tendency to concentrate expertise and power in the hands of the few.


GIS, Wayfinding, and the Device Paradigm

October 5th, 2015

Aporta and Higgs (2003) present a case study of Inuit hunters of the Igloolik region, examining the effects of the introduction of GPS technology to their traditional understanding and navigation of the landscape, referred to as wayfinding. They introduce Albert Borgmann’s “Device Paradigm” in consideration of the effects new technology has on old practices. The paper’s purpose is to bring more attention to considering the implications technology has on cultural perceptions of geographic space. Since it’s undeniable that this is an issue relevant to GIScience, I would like to talk more about my own thoughts regarding the philosophy of technology, specifically the device paradigm.

The device paradigm refers to how technology is perceived and consumed. It suggests that as technology becomes more advanced, commodities and services become more available and the processes and meanings behind the technology become less understood. In the case of GPS, as examined by the authors, the Inuit people’s tradition of wayfinding has become less necessary to learn and pass down because GPS simplifies and increases the accuracy of navigation across the arctic landscape. Many anthropologists take this to be a bad thing, because replacing traditional methods with new technology makes it harder to find meaning in what it is that someone is actually doing, because they are interacting with the technology instead of the environment that they are using it in.

This is obviously true, but I feel like for the sake of technological advancement and the progress of the human race, we have to be willing to forego the meaning behind certain aspects of life. This is because learning takes time, and it is only possible to learn so much within one’s own lifespan. Technology offers shortcuts that allow us to reach our destination faster than if we had to learn and memorize every single step along the way. These sorts of shortcuts are everywhere in GIS, from data management and spatial analysis tools to the computers we use to run the software that includes them. But then again, we need people around who know what to do when these devices fail us.


Only one more post on Rundstrom

October 5th, 2015

Just a reminder that only one more of you can post on Rundstrom before you switch over to the other article.

First to post gets Rundstrom.

Indigenous Epistemology and Forced Assimilation

October 5th, 2015

What Rundstrom has done in this paper is highlight the large rift between Euro-North American and Indigenous American school of geographic thought. I find it quite obvious that these differences exist, but never would I have thought to compare the methods of spatial cognition used by natives such as the Inuit and Hopi to those used by proponents of GIS and GI Science. I am a product of colonialism and the Euro-American school of thought, and more recently the Euro-Canadian school of GIS, so to me it seems obvious the only way of analyzing spatial phenomena is to treat nature as non-human objects to be taken out of context and subdivided into layers and databases.

Rundstrom compares this Spatial analyst way of thinking with Native American practices of spirituality and the passage of knowledge. An example of these two practices would be how the Hopi treat water as a spiritual entity, and the selective process through which Native Americans pass down geographic knowledge. At first, I found this ridiculous. Why compare an advanced technological system with the teachings of my high school history classes? I was well aware of the Native’s oneness with nature and their uncanny abilities to communicate with their surroundings, but how can their primitive technology compare to the advanced methods we use today and at the time of this papers publishing?



Ethical Implications of GIScience

October 5th, 2015

In his article, GIS, Indigenous Peoples, and Epistemological Diversity, Rudstrom expounds upon the power hierarchies that contextualize doing GIS. He boldly asserts that doing GIS as a “technoscience” reinforces and perpetuates narratives of dominance that disenfranchise indigenous ways of thinking. Therefore, if GIS adheres to Western epistemology, then is it really appropriate to apply these systematic ways of knowing to indigenous ways of being? Any process that involves structuring and classifying the world around us are inherently exclusive in nature. Therefore, how can we ethically claim that our way of mapping the world could encompass the entirety of non-western ontologies? I’m not sure if these questions will ever be answered fully, but as GIS users we must entertain the the possibility that how we do GIS may have extreme ethical implications. For example, if certain geographic knowledge is privileged in indigenous societies, then do we have the right to map them for the sake of the long term preservation of knowledge and culture?

In addition, generalizing indigenous communities suggests that there is an inherent nature to indigenous epistemologies. However, indigenous communities in Northern Quebec have very different ways of perceiving and managing their environment compared to indigenous communities in Central America. Conflating indigenous epistemologies does a disservice to the complexity and diversity of how space and processes of thought engage with one another.

I hope that more community participation in GIS and the geospatial web may tackle some of these problems. Such work will be crucial for understanding the ethical and practical implementations of doing GIS in the future.


Rundstrom 1995

October 5th, 2015

For me the most striking aspect of this article relates to differing attitudes toward uncertainty. I have done extensive reading on uncertainty for my upcoming seminar and uncertainty is regarded in textbooks as something to be “aware of” and “open about”, as if it were an affliction. By contrast, Rundstrom points out that many indigenous cultures consider uncertainty (in particular ambiguity) to be a key enriching element of existence. Of course, this idea is not alien to western cultures, as we also find that the deepest of meanings are intangible. Furthermore, we are theoretically aware that in reality most strict boundaries and definitions are socially constructed. However, GIScience still seems to be fundamentally incapable of helping us to view uncertainty positively, because ultimately a GIS must work with either objects or pixels. Taking this into consideration, we should certainly heed Rundstrom’s warning that the effort to promote GIS in indigenous communities is likely to further suffocate indigenous worldviews. On the other hand, we must take care not to look at indigenous communities as passive entities with no agency. In many situations indigenous people may feel that in order for their communities to thrive while surrounded by non-indigenous civilization, they must forge a connection with us so that they can “manage” us. GIS could easily fit into this type of strategy. Ultimately, I think that as GIS practitioners we will have to scrutinize every application of GIS to indigenous culture to so as to discern whether it is truly a decision made by indigenous communities to use GIS or if it is imposed on them from outside with a colonial mindset.

- Yojo



October 5th, 2015

One of the central themes in Rundstrom’s text on GIS, Indigenous Peoples, and Epistemological Diversity is the idea that indigenous epistemologies and current GIS technologies are inherently incompatible.  He cites the fundamental difference in the western world’s definition and understanding of energy and matter to that of the indigenous peoples as well as differences in temporal change as two of the reasons for this.  I immediately connected this to my research topic for this course, geospatial ontologies.  Epistemologies are concerned with how one procures knowledge while ontologies more are concerned with defining the nature of being.   Both work to inform us on how we’ve come understand what we do.  More specifically geospatial ontologies aid us in the defining and the reasoning of real world spatial phenomena.

Though I agree with Rundstrom’s point that indigenous people’s geographic knowledge should be separated from GIS for ethical purposes (and I am not advocating the disenfranchising of indigenous communities by any means), I disagree with the idea that they are fundamentally incompatible.  By utilizing indigenous knowledge into geospatial ontologies (perhaps creating indigenous specific geospatial ontologies) I think it is possible to combine the two.  This will not be achieved without difficulty since our current GIS framework is centered on the Western world view, as specified by Rundstrom.   However, I think that by acknowledging this we have the potential to develop a new framework where a new understanding of environment may be incorporated.

Rundstrom very well may argue that my position towards this is part of the problem and that I am a symptom of the insensitivity of the western world.  I would argue that since 1995 we have made advances in GIS, GIScience, and the world’s valuation of Traditional Ecological Knowledge (TEK).  On behalf of both parties, whom ought to find common ground and work together to protect the environment, these two world views must be integrated and I think GIS is the most feasible platform to achieve this.




GIS: Just another means of colonization?

October 5th, 2015

Rundstrom’s 1995 article “GIS, Indigenous Peoples and Epistemological Diversity” is an insightful critique of how geospatial technologies and Western science are fundamentally incompatible, exclusive and oppressive to indigenous epistemologies. For me, this has been the most thought-provoking topic yet. It made me reflect on just how pervasive and deeply-rooted colonialism is, how indigenous epistemologies have survived, and how that implicates me as a student of GIScience.

Rundstrom states that he understands GIS as a “technoscience,” which “modify and transform the worlds which are revealed through them” (46). Rundstrom actually highlights the division between GIS as a science and a tool. As a science, GIScience is fundamentally incompatible with indigenous worldviews. For centuries, Western science has actively invalidated indigenous ways of knowing. The legacy of colonization lives on through our settler society, which continues to inhabit stolen indigenous land. Western science’s desire to know more, to represent more, to describe more of our world is the means to exploit more, expand more and take more. As a tool, GIS is a technology, which have historically been used for assimilation and continue colonization. The technical capability, language (jargon) and education required to participate in the use of technologies also exclude indigenous people and their ways of knowing. Undeniably, our tools hold power over other people.

Where does this leave GIS, and indigenous ways of knowing and describing geography? I think Rundstrom would argue that indigenous knowledge should not be incorporated into GIS for the sake of taking what is “useful” to us and leaving the rest – which is historically what has been done, again and again, to indigenous groups through colonialism. Instead, indigenous groups could use it for their own aims, because GIS is likely to be believed by empirically-minded policymakers. For example, Operation Thunderbird uses crowdsourced mapping to display information on missing and murdered indigenous women: Although GIS still has a long way to go before it can be at all compatible with indigenous epistemologies, it has potential to be an advantageous political tool.


GIS, Indigenous Peoples, and Epistemological Diversity

October 5th, 2015

Rundstrom’s article “GIS, Indigenous Peoples, and Epistemological Diversity” (1995) discusses how indigenous cultures perceive “geographical knowledge” differently compared to North American and European Westerners (45). Even though there are different cultural perspectives on spatial knowledge, there has been a tendency for GIS to be ethnocentric, focusing on Westernized epistemology and ignoring the cross-cultural variations in understanding landscapes. As someone who studies anthropology and geography, I agree with Rundstrom’s proposition that the “GIS research agenda [should] include cross-cultural studies of knowledge transformations and culture change;” however, since Rundstrom’s article, there has been technological advancements and offspring disciplines, such as Qualitative GIS and GIScience, that consider different perspectives (45). Before I discuss how GIScience has contributed, I do want to make a point that even though GIS is known for being “eurocentric,” GIS researchers wanted to develop a systematic procedure for data collection and modeling (55). Now with improvements in technology, we can veer away from authoritative systematic analyses and allow everyday citizens, including indigenous people, to contribute their own geographic information. This is what volunteered geographic information (VGI) is, and what I am researching for my final project.

Within GIScience, VGI accepts amateur volunteers’ geographic information; this means indigenous peoples can use the internet to geotag a specific location that pertains to their culture and describe that location’s significance to them. This can be done in Google Maps or Yelp, where the geotagged area and small description can provide a more enriched epistemology that can be collected and analyzed by an outside party. Nevertheless, it is not that simple, collecting data from amateur internet users introduces topics on accuracy and how to properly validate the information as correct – there are still debates on how to define which volunteered knowledge is valid or not. In some cases, websites have volunteer monitors that check accuracy in what people write; thus, some reviewers may not objectively agree with an indigenous person’s subjective description on a certain place.

Similarly to what we discussed last class, geospatial agent based-models may also be able to show variations in geographical knowledge as technology and technical methodologies improve; maybe an agent can receive multiple attributes that can enhance how they perceive their landscape. This can allow for a more diverse epistemology. Therefore, since Rundstrom’s article, there have been improvements in GIS to account for “epistemological diversity,” but there is still room to grow (45).



Geospatial Agents, Agents Everywhere

September 28th, 2015

The first reading So go downtown gave an introduction to agent-based modelling. As mentioned in the article, one of the large limitations of the model is that pedestrians are generated according to a Poisson distribution. Similar to the train example, I would propose that it limits this model for use on campuses where large numbers of students are released at once at regular time intervals. That being said, this article is more than 10 years old and I’m sure agent-based modelling has progressed rapidly since then. Advances in CPU capabilities likely allow researchers to simulate way more agents with a more complex set of behaviors and landscapes.
Reading Prof. Sengupta and Prof. Sieber’s article Geospatial Agents, Agents Everywhere, I was excited to learn that the models have progressed and been applied to several scenarios from movement in alpine environments to shopping behavior. One of the most interesting applications mentioned in the article was a system that could vary highway tolls based on traffic density. This immediately reminded me of the car sharing service Uber, which currently varies its fares based on demand. Uber would likely be interested in traffic-predicting geospatial agent models, so that their cars could both avoid traffic and be well located to pick up passengers before they even request a lift. For example when a large event ends traditional taxis may have exclusive rights to park right outside the venue, forcing Uber cars to linger a couple blocks away. By using geospatial agent modelling, the Uber cars could predict crowd behavior leaving the concert and better distribute their cars to better compete with traditional taxis.
Fares could even become geofenced, so that zones with a high predicted agent density receive a higher fare bracket than low density zones. In this scenario Uber could entice more cars into specific areas before they are needed, and influence crowd behavior by encouraging thrifty pedestrians to enter zones of low predicted density.

Model Citizens: Haklay et al, “So Go Downtown”

September 28th, 2015

Haklay et al’s article “So Go Downtown” describes an intricate model of pedestrian movement, STREETS. I began the article somewhat skeptical of the need for such a model (is it not good enough to simply collect enough data on pedestrians?) and the capacity of the model to think of everything; for example, agents deviating from their agenda, socioeconomic status, etc. Nearly every “but what about…” was answered in the article, and I was surprised by the complexity of the model and how much it takes into account. I also found the combination of raster, vector and network data to be fascinating: often in our education, these data models are taught as disparate and we do not use them in conjunction. This article started to give me an idea of the ways that these data models can, in fact, be used together.

One problem with the model that the authors raise is that the town is “spatially closed” – the town in the model is a bubble, with no competing towns or suburbs nearby. The authors recognize that adding further complexity by expanding what is a closed model would be an incredible task. It is difficult to place boundaries on what should and should not be included in a model – it requires making serious choices about what is significant enough to be included in the micro world of the model.

Clearly, there is room for expansion and improvement in the modeling and simulation realm of GIScience, as existing models are modified and new ones are created.

- denasaur

Modular, spatial ABMs: Haklay et al., 2001

September 28th, 2015

In the intervening fourteen years since “So go down town” (Hackley et al., 2001) was published, agent-based modeling has, unsurprisingly, been harnessed for an ever-expanding number of applications. In the wake of the late-2000s recession, which appeared to discredit the economistic assumption of equilibrium, influential science journal Nature published an editorial calling for the synthesis of existing ABM techniques into a modular representation of the existing economy. Spatial ABMs (such as the STREETS model) have surfaced in mainstream news as potential predictors of crowd behaviour. Needless to say, Hackley, et al. were on to something very important with the development of their modular, multi-scalar representation of pedestrian behaviour. Avoidable catastrophes such as the 2010 Love Parade disaster, in which 21 people were killed by trampling due to a dynamic feedback phenomenon now known as “crowd turbulence,” have provided fodder for the study of the effects of interrelated psychological and physical forces on large crowds.

In general, ABMs appear to be one of the most promising intersections of social science and computer science, due to its ability to model situations of staggering complexity, involving thousands or millions of agents whose dynamic interactions produce highly unpredictable results. Our last discussion about geolocated SNA produced some interesting conjecture about what could be done — for better or worse — with the datasets of Google or Facebook, which contain geolocated information on billions of real individuals. Haklay’s observation that ABM research in the 1990s was hindered by “sufficiently powerful comptuers and suitably rich data sets” points to the potential that this information has to expand human knowledge, as well as to enable much more effective control of human populations.

I would venture that combinations of current-day iterations of modular ABMs like STREETS, combined with these ever-growing, dynamic sources of socioeconomic data, hold the potential to create very well-informed models that capture the dynamism of emergence with the power of immense and ever-evolving observations of real people. With so much relevant research now being conducted behind closed doors at intelligence agencies and in corporations whose business is selling data, the current and future possibilities of spatial ABMs remain both fascinating and frightening.



Simulated Movement, an Emerging Field?

September 28th, 2015

The article by Haklay et al. from 2001 is an interesting look into simulated pedestrian movement in a closed-system urban downtown setting. Named STREETS, this module-based model shows just how complex real human movement is by detailing the ways our unconscious decision-making must be broken down by a computer in order to simply approximate pedestrian paths.

After reading about the various modules, my thoughts were immediately distracted by trying to think up further additions to make the model as realistic as possible.  A more complex model might include the presence of cars as another variable that would affect how pedestrians are able to cross roads, and for example, how their path might change if the time spent waiting for cars to go by allows them to focus on an alternate target destination that they originally ignored. In relation to my own project on hydrological models, the simplest Mover module could be applied to predicting overflow in river systems. If excess water flow units were given values like individual agents in the article, and the water filled certain pixels like pedestrians filled sidewalk cells, once a pixel was “full”, the excess water would have to move into the adjacent pixel and could change overflow paths.

As the modules became more specific in their control of agent movement, the final module, Planner, almost seemed like artificial intelligence. It was not until the authors directly address the difference between deliberate simulation and emergent, ‘self-organizing’ movement that I realized model simulation can become so much closer to “real-life” than exists currently. Overall, this piece was engaging and had easy-to-follow technical descriptions of the modules combined with just enough theory to relate the topic to GIScience and future implications.

- Vdev

Haklay et al 2001

September 28th, 2015

I imagine that agent-based modeling is much more complex than most models in natural sciences, such as climate models or forest growth models. While for now agent-based modeling is applicable for more simple aspects of human behavior such as commuting, further application in economics or sociology would probably require significant advances in fields such as artificial intelligence, which would improve our ability to simulate human decision-making. Since the writing of this article, however, I imagine vast advances have been made. Such advances would allow computer models to complement or perhaps replace some survey-based research. Choice experiments, for example, represent a survey-based approach that is used to understand how subsistence farmers and herders use ecosystem services based on environmental and socio-economic factors. I would be intrigued to see computer models simulate such scenarios.

I wish that the “planner” module were functional and applicable at the time that this article were written. Perhaps it would be representative of people having multiple, completely different modes of behavior. For example, would a student or worker have a “weekday” plan and a “weekend” plan that the planner module would alternate between? Also, I was very intrigued by the term “cognitive map”, but the paper did not expand on it. Furthermore, the discussion of emergence was difficult to grasp. I believe it was talking about whether we should try to look for clear behavior patterns  and systems at aggregate scales or just accept ambiguity or lack of patterns as they are.


More than ‘plausible’: pedestrian simulations and the future.

September 28th, 2015

In their 2000 article, Hacklay et. al. present a model of impressive complexity – STREETS – to simulate pedestrian movements in central urban areas, relying on the use of several different ‘modules’ to control individual agents as well as interactions with the environment and crowd dynamics. The authors outline a number of shortcomings to their methodology, notably the assumption that the town centre in the simulation is a ‘spatially closed’ (p.10).

Initially skeptical of the model’s use beyond simply confirming or denying existing ideas about pedestrian behaviour, I was reminded (as in previous articles) of our in class discussion about the quantification bias that can legitimize numerical/computational work over more qualitative approaches, and has indisputably helped maintain the relevance of GIS (and now modelling) in contemporary geography. This made me question the relevance of modelling human behaviour; I felt the assumptions in the STREETS model were too damning, and the implied complexity would never be adequately abstracted. To my surprise, this was boldly addressed by the authors through a fascinating discussion of ‘bottom up emergence’ (p.25-26).

In discussing the role of agent-based modelling and its ‘one-way notion of emergence’ (p.26), the authors detach themselves from the notion that inductive research is possible in the STREETS model, and the jump from describing pedestrian movement as ‘plausible’ to ‘self-organizing’ (p. 25) is significant. This discussion peaked my interest, for it suggests that there is more to modelling than increasing its complexity every time advances in computational power allow for it. Clearly, the addition of dozens of modules or parameters is not enough to allow reliable inductive research to be conducted. Nevertheless, the power of modelling hundreds of thousands of agents at a time far exceeds the current possibilities of qualitative research on pedestrian movement, suggesting that modelling will remain highly relevant in the study of pedestrian movement into the future.

At what point will models transition into ‘self-organizing emergent structures’ (p.26)? I honestly cannot say, and my level of understanding doesn’t even allow for an educated guess – all I know for sure is that it won’t be exclusively dependent on computational power. In any case, I look forward to seeing how the field develops.



Are all Trip Generators Created Equal?

September 28th, 2015

In their article “So go downtown: simulating pedestrian movement in town centres”, Mordechay Haklay et al describe ways in which “agent-based modelling” have produced superior models of pedestrian behaviour, by taking into accout variability in the preferences and behaviour of pedestrians based on the purpose of their trip, their demographic characteristics, and a variety of other considerations. However, one aspect of earlier pedestrian traffic modelling–from which the assumptions of agent-based modelling are derived–underlined some of the limitations of the agent-based modelling approach. Haklay et al indicate that pedestrian models typically incorporate two elements of a place (typically a city block, tract, or some similar defined area) to predict the volume of pedestrian activity: the “population at [the] location” and the “measure of the attraction of facilities at [the] location” (Haklay et al 7). However, this begs the question: are all attractors created equal? In less abstrsct terms, can the number of trips generated by commercial and employment nodes be considered with equal weight as a trip generator as the relative permancy of a residential population at a particular location? In my opinion, they surely cannot. The variablity of pedestrian trips–particulary to retail–cannot be overlooked. While the “attraction of facilities” (7) at a location can vary on an hourly basis, residential populations fluctuate significantly only over several years at a time. Some factors that affect pedestrian trips to facilities at a location–particularly retail facilities–include: variablity in the seasonal commerce (e.g.: Christmas shopping, tourism season, etc.); variable personal preferences from person-to-person in different weather conditions (e.g.: a shop may see less clients during inclement weather, while a movie theatre might benefit); personal preferences in walking speed and environment (e.g.: some people may prefer quieter streets so they can walk faster, while others prefer busier, slower streets); and variable tolerance to environmental conditions, such as the urban heat island effect. Although incorporating these elements into agent-based modelling would be arduous and expensive, the potential benefits to countless urban environments is unimagineable. For instance, pedestrian modelling which incorporates pedestrian behavioural response to changing weather conditions could correspond to public transit network, deploying more or less vehicles during times of demand induced by weather (e.g.: several people seeking bus service during a rain storm). Models which comsidered variability in tourist traffic could help business owners make educated decisions about their investments (e.g.: where to locate, what hours to have etc.). But perhaps most intriguigly of all, pedestrian models could ipactually show what factors in the environment affect pedestrian behaviour adversely, allowing for targeted investments that enhance the walkability of an area and maintain the vitality of pedestrian-oriented neighbourhoods.


Role of Geospatial Agents in GIScience

September 28th, 2015

In their article, Geospatial Agents, Agents Everywhere…, Sengupta and Sieber (2007) demonstrate how the paradigm of agents in AI both serve and benefit from research in GIScience. I found it interesting that Artificial Life Geospatial Agents (ALGAs) are relevant to our previous discussion about the importance of spatializing social networks. ALGAs are relevant to spatial social networks in that they model “rational-decision making behavior as impacted by a social network” (486-487).  Therefore, applying our knowledge about spatial social networks (as opposed to just social networks) to ALGA development could perhaps help us better understand and model social interactions and information passing between individual agents.

In addition, the interoperability of Software Geospatial Agents (SGAs) across software and hardware platforms informs us about ontology, representation, and semantics in GIScience. Therefore, SGAs might unlock answers concerning key questions surrounding geospatial ontologies and semantics. This is because SGAs have the key responsibility of determining the standards to interpret semantically. These standards may help with important GIScience tasks of expressing topology and geospatial data in GIS. Therefore, the fact that SGAs are “geospatial” in nature will impact the extent of how we “do GIS” as geographers.

I am interested to know the extent that ALGAs are able to incorporate temporal dimensions within its frame of development. I suspect that adopting the added dimension of time into these platforms and models would be a crucial challenge for ALGA research in GIScience.