Computers, Society, and Nature

I feel that Aitken and Michel are slightly overreacting. “GIS Hegemony in Planning”? Those are some strong words right there. I feel that this article may be a bit outdated, having been written in 1995. Indeed, the cited predictions about the future net worth of the GIS industry were gross underestimates. 600mn systems and 6bn USD global industry worth? That’s nothing. According to a Wikipedia article (original source no longer available – yea I know), the GIS industry is was valued at 400bn yuan (63bn USD at current exchange rates) in 2007 in China alone. I don’t know whether the authors were truly appreciative of what GIS has done for us, and so instead chose to focus on criticising it.

One of their issues, if I understood correctly, was that GIS systems give too much ‘authority’ to those that use them. GIS has made doing analysis and making maps very quick and easy to do, and increased accessibility of GIS software/hardware has enabled more people to do such analysis. The authors worry that we trust in the output from the people using GIS too much. That we don’t scrutinise the underlying methods and assumptions, and that we are merely pushing buttons instead of thinking about what we are doing. In response to their urban planning examples of failures due to over reliance on GIS models, I would say that it is merely a matter of education. The kinds of models and assumptions you get in GIS are based on other domains such as urban planning, so blaming GIS will only get you so far. If you know your urban planning theory or ecology or whatever subject, you will be able to look more critically at: whether the output matches established theory, and whether the computations done in the GIS was appropriate. If you want people to truly understand what’s going on, then they have to educate themselves. GIS though, can still be useful to those with rudimentary knowledge. Many make use of statistical tests without trying to remember the exact formulas behind them. All they have to remember are the required inputs and how to interpret the results. In terms of planning – there will still be an urban planning expert sitting behind that GIS, doing the analysis. For that person, the GIS will be an extension for the field of urban planning; an enabler for the researcher to do more things more quickly. Even if they look at GIS as simply a tool, they will still understand how it works. If they don’t, then the city council should hire someone else.

Another problem they had was that the ‘interested citizen’ does not get fed all the details, but instead just gets filtered information prepared by others. Again, this is another area where the article may be out of date. Right now, it is much easier to get hold of data than in 1995 due to the internet. Whether or not information is released is not a reason to blame GIS – rather, these tend to be more legal issues that should not be in the scope of CGIS.

-Peck

The article written by Couclelis on models and their role and integration into land use planning states that the “systematic effort to understand what makes certain things about the future predictable and others not, or how to prepare for genuinely unpredictable futures, have so far had only a negligible impact on land-use planning and modeling” (p.1360). This statement suggests to me that land-use planning and modeling are not considering the complete picture in that the assumptions held are that one can predict the future and that when one is not successful, some reasons for the failure are not considered. The two issues mentioned in the quote both relate to our acceptance and greater consideration of uncertainty in the future which I feel should be very carefully examined when attempting to plan for the future. Relating this a little to critical GIS, if we fail to consider all factors underlying a system, it would be negligent particularly from the science side with the modelling, and the final product could be altered and manipulated to send a particular message.

-Outdoor Addict

I enjoyed reading this article and see many parallels between the author’s arguments and the goals of critical GIS. Couclelis argue that planning has lost its future-oriented approach and is absorbed by operational and managerial tasks. She urges planners and modelers to incorporate scenario writing, visioning and storytelling into PSS. Although I understand the gist of PSS, it would have been helpful if the author had offered a description of what the system consists of. How is it different for conventional GIS software? Are there functionalities that allow easy integration of scenarios?

The 3 methods advocated in the articles are qualitative in nature. “Models are based on science; planning is about policy” (1359) indicate a tension between quantitative and qualitative approaches. This exact tension experienced by GIS practitioners and social theorist is what gave rise to Critical GIS. Large amounts of work is being done in Qualitative GIS with the goal to incorporate different types of data into GIS, such as in-depth interviews, ethnography studies, emotions and even sounds. Some researchers have also employed mixed methods, that is, using quantitative and more personal qualitative datasets. I will refrain from saying too much here because I will be taking about it tomorrow. This are in Critical GIS is definitely promising for scenario writing, visioning and storytelling.

Figure 1: Scale Openess (Source: Scale and Hiearchy Theory from http://forestlandscape.wisc.edu/courses/Landscape565spr11/handouts/565%202011%20lec%202.5%20ScaleHierarchy18Jan2011.pdf)

On another notes, Couclelis writes, “Land-use and land-cover change are themselves issues spanning the local-to-global spectrum so that changes at one geographic scale may have significant repercussions at several other scales and times” (1358). This idea of events having effects for multiple scales was brought up during the lecture on “Scale” [Figure 1]. To be able to define and visualize these inter-scale interactions in GIS will be increasingly important as the world becomes more connected. This capability will allow us to get a more complete picture of consequences from a certain disturbance/event. For example how “open” is the city of Longueuil to changes in immigration trends from Asia? Or from changes from consumer preferences living in Germany? Analysis like these cannot be easily carried out in GIS because the system requires all the layers to be in the same scale. When will GIS be able connect places on two different map that do not match in scale?

Ally_Nash

The critical GIS article by Aitken and Michel brought forward once again the concept of homogeneity in GIS through the proposal of having a universal GIS which would be “flexible enough to accommodate the demands of locally based, micro-scale uses”. I would generally say that I don’t believe that any type of miracle universal GIS could be created to deal with planning issues anywhere on the planet particularly if the GIS were produced by a single company like ESRI or SPANS. As far as I know (feel free to let me know otherwise!) companies are out to meet user needs and to make money and to do so, they must cater to their users but arguably only the majority of their users in the interests of time and profit.

What I wonder is: could the geoweb play a role in producing a GIS that caters to a far broader variety of users and allows these users to build on the GIS to improve it for specific purposes and, in the context of planning, for specific locales? The paper does not deal with this concept likely due to technological evolution since it was written in 1995. At that time, users could access the internet but not necessarily contribute to its content in any way. Today, users can create vast amounts of information as well as software and this kind of power could be harnessed to create a universal GIS with many components for a variety of users, uses and places.

Another necessary aspect of a universal GIS is that it would have to have different possible levels of analysis to serve the experts and the naive users. This would in turn rely on both experts and naive users contributing to the online GIS, something that may not happen. Additionally, such a GIS would not be capable of ensuring naive users are using the level of analysis geared to them as opposed to a higher level for research purposes. To assist in solving this problem, I would say users need to be educated about GIS and how to use it but that perhaps if they chose not to learn all the technical details, they could still use the level of the GIS geared toward them.

-Outdoor Addict

Couclesis’s article on planning support systems appears to contradict the communicative model of Aitken’s piece on critical GIS. Couclesis argues that planning models have suffered a trade-off effect of including public sentiment in brainstorming sessions at the expense of hard expertise. The author draws a sharp distinction between the social fluidity of planning and the technical-objectivity of models.

I am uncomfortable with the assertion that participatory planning has a negative impact on the scientific and expert rigor of its products. The more relevant issue is inviting and drawing in an appropriate audience for the task at hand. Locals of an area have detailed knowledge of how processes affect them that rivals scientific knowledge. More often than not, their reporting of changes in the system is more timely and appropriate for model corrections than scientifically verified corrections (the convenience and fitness vs. rigor and accuracy argument). The challenge, as Couclesis points out, is to ensure the mutual cooperation of public and experts. As a geographer it also seems silly to paint experts as divorced from the social implications of their work; wouldn’t experts be the most aware of the limitations of their work? As GIS-users, wouldn’t experts also be grateful for the wealth of knowledge VGI and cooperation with the public produces?

Finally, the author’s suggestion that “neither the reactive response to changing circumstances nor the futile reliance on forecasts built on variations of business-as-usual scenarios can deal with the mix of pattern and noise that is the future.” initially confused me. It represents a key understanding though that linear extrapolations are insufficient for temporal analyses since one change may have a disproportionately large impact on other factors in the future. In such an unpredictable case, aggregating to a larger temporal scale is a step in reducing uncertainty. A more bold approach may be to rely on a mosaic of deep local understandings to represent a process across a larger extent. Such a method would be incredibly dynamic and may produce counter intuitive results such as those revealed by agent based modeling.

-Madskiier_JWong

The article on critical GIS strongly emphasizes the subjectivity and human fallibility in GIS. The authors call for a more communicative, open, and inclusive approach. Their concerns appear to lie in the construction of truly participatory GIS that is open to all for exploration and examination at all steps.

I agree with ClimateNYC in that this reading seems to have circled back to our original debate of GI science vs. GI system. Through all of our class lectures, a new (to me) perspective is viewing the problem as an issue of public perception. The authors emphasize a strong divide between experts and novices to GIS, and I agree based on the learning curve of writing custom scripts/functions and variable recognition of the data’s limitations. Aitken and Michel’s call for a more “communicative rationality” seems to question the necessity of such a debate and pushes for a merging of the two. A quick note: at the beginning of the course, I stood on the GI science side of the fence.

The general trend of development in GIS functionality has been to make processes more accessible and user-intuitive. This has been shown in the cutting-edge human-computer interface examples shown by Peck. Simultaneous and interactive multi-user visualizations work towards this goal at the software level. These design challenges necessitate frequent debate and exchanges with users to optimize the systems for as wide an audience as possible.

The life-path of computers is a helpful comparison. They originally started out as expensive, feared research-oriented machines found only in the cloisters of MIT and government agencies. Curious techies got involved with programming and hardware development and became the first “hackers”. The development of games and minicomputers were truly pivotal moments in popularizing computers.The quick adoption of geospatial tools such as Google Maps and the GeoWeb is the popularization parallel for GIS. Application and theory will become increasingly intertwined with more intuitive tools available and may lead to a redefinition of the importance of place (in a digitalized world where the friction of distance has been lessened).  

At the end of the day, the increasing accessibility of data may make GIS an example of a science submerged in the social realm. Computer science still remains, and it is likely that GI science will as well. Concerns about underlying politicization and deceptive “objectivity” will fade as GIS methods become more and more ubiquitous. This reading has further shifted my views on GI science vs. GI systems towards a middle ground, and whether it is realistic to view the science-system as separate components.

– Madskiier_JWong

Often in class, there has been discussion of how much a user of GIS needs to know about the GIScience behind a particular concept or application of GIS. The HCI article by Haklay and Tobon bring this issue to the forefront once more in trying to understand how people interact with computers and GIS in particular.

My impression of this paper and the topic of HCI in general is that experiments, workshops, discussions etc. focused primarily on understanding the difficulties users encountered in working with a GIS and then adapting the software and interface to better cater to the needs of the people. Although this can certainly be helpful for users if the required improvements can be incorporated into a GIS, it does not teach the users the GIScience behind the GIS leaving them vulnerable to making assumptions or conclusions without considering such issues as the uncertainty that could be present in their final product or query response. Teaching the users of these GIScience issues falls under HCI as the method of teaching during an experiment or workshop would likely be very influential on how well participants navigated and used the GIS. As such teaching could be an important area for additional research in HCI.

Catering to different learning styles was not greatly mentioned in the paper although I think this would be another way to improve HCI. GUIs are very helpful in this regard as they cater to visual learners and to some extend those who learn best by doing and trying things as what steps or uses a tool has if it can be visualized. However, those who require explanation or a demonstration to learn may be disadvantaged by GUIs. Tutorials and video demonstrations could be incorporated into GISs to explain how to accomplish particular tasks. Incorporating various learning styles into the GIS would assist users with self-help and reduce, but likely not eliminate, the need for face to face explanation.

-Outdoor Addict

I particularly enjoyed reading Haklay and Tobón’s article, as public participation in urban planning is a topic that I take great interest in. The article notes that especially in an age of increased personal computer usage, empowering users of GIS is crucial to not only improve individual and social development in communities, but to also gain a greater understanding of the design and capabilities GIS systems.

In urban planning, encouraging public participation is often a tricky endeavor. While reasons for being unable to participate vary greatly, one cause includes the inability of individuals to travel to meetings due to, for instance, mobility issues or scheduling conflicts. As a result, it is possible that those who are able to participate represent a relatively small portion of a community. Perhaps improving GIS to be more accommodating to all types of users, from the novice to the expert, will enable participants to move up Arnstein’s “ladder of participation” to a level of greater citizen involvement and power.

The article provides two examples of citizen workshops, which both provide insight into how a GIS can be better designed to facilitate usage. From the first example, I think that one of the main points is the importance of a system’s learnability and flexibility. In this case, learnability refers to “the time it takes a person to reach a specified level of proficiency.” This process will vary for every user, and as such, a GIS tailored to improve urban planning participation may have to include many different features to involve, for example, those who have limited vision. Moreover, flexibility is defined as “the extent to which [a system] can accommodate tasks or environments it was not originally planned for.” This point very much relates to another issue Haklay and Tobón bring up, which is that creators of a GIS must be constantly involved in the design process, which may arguable be a never-ending activity.

From the second workshop example, I think that one of the key issues is the accessibility of a GIS. The development of a web-based urban planning or e-government platform meant that individuals could remotely access information or be included in decision-making. I think that this process has profound implications for those with mobility issues, as already mentioned, in that one no longer has to travel a great distance to participate.

Lastly, while increasing citizen engagement may appear at first to be entirely positive, one has to wonder to what extent should this be encouraged. On the one hand, it may not be possible to completely cater a system to the needs of every individual. In other words, at some point generalizations have to be made, which may hinder how those with varying levels of expertise or capability interact with a system. On the other hand, citizen engagement is often unquestionably considered a positive aspect that should always be fostered. Perhaps this notion itself should be questioned, because, for example, it is possible that too much public engagement can lead to the reduced capacity of organizations to operate efficiently.

– jeremy

Based solely upon the reading, I am not quite sure yet how exactly we need to be able to include temporal analysis into maps. As the article says, the digital map itself is strongly related to its analogue roots. Do we really need to be able to analyse temporally through maps? Aren’t the current discrete time step methods enough? What about the geovisualisation we saw where Hans Rosling visualises 3 socioeconomic indicators over time, on a 2D graph. Non-map based methods could be simpler to interpret than the solutions proposed. The basemap with overlays solution proposed in the article is not a good one. It is, first of all, seemingly restricted to vector data. Secondly, I think trying this approach can make things difficult to comprehend (visually), especially with many time slices. The third solution – the space-time composite could also be tricky. Accessing the data at a certain point in time may be simple enough, but if you’re comparing two or three time slices which all have a very large number of polygons, does it still make sense to visualise it. Don’t people tend to view discrete polygons as different objects? Here, the different polygons can actually represent the same thing, but just iterations of it over time. Won’t it be confusing to therefore view two time slices on the same basemap?
Somehow, I feel that looking at a time series in a graph is more intuitive than the map. We’ve already had the map metaphor ingrained in ourselves, I doubt it would be easy to teach a ‘temporal map metaphor’ to people.

I was also thinking about how this sort of thing would work technically. When data isn’t accessed a lot, it tends to get compressed and archived to save storage space. If we’re doing temporal analysis and grabbing slices from here and there, would we have to just keep all our data uncompressed? While technology has advanced very rapidly since the article has risen, we’re still present with the problem of large datasets, and performing temporal analysis with discrete time slices is still probably a chore these days.

-Peck

Time has been and continues to be a mysterious entity for philosophers and physics. It doesn’t make any sense to talk about things in space with time, since no entity can exist without also having duration as one of its attributes. We also know from special relativity that space is intrinsically tied to time through the Lorentz Transformation, but this really only comes into play when traveling at extremely high velocities. However, there are many ways in which time is considered different from space. One can move in all directions in space but only in forward in time. I really liked Table 2 where Langran and Chrisman (1988) presented the analogies of GIS concepts between space and time. It helped me to clarify my thinking about temporality and how these two concepts can be combined.

While reading the article, I found myself asking the similar questions as Outdoor Addict. What constitutes as a change? And at what temporal scale should these changes be observed? For me, the first question is closely related to cartographic scale and must be considered in tandem with the specific research question at hand. If the research is concerned with the location of maple trees then perhaps a new map tree will constitute a change worth recording. Conversely, if the research question is concerned with the expansion or reduction in the size of a maple tree forest then the growth of one additional maple tree may not be enough to count as a mutation. An “event” in the latter example would be related to a percentage change in the forest boundaries. The cartographic scale one chooses will have a direct influence on the frequency of mutations and thus, on the appropriate temporal scale. This also leads to questions about precision for temporal data. When an event occurs, how precise should the temporal records be? To the minute? to the second? To the hundredth of a millisecond? It is likely that different kinds of events will have different temporal requirements.

Although I liked the map/overlay model the authors proposed, I imagine it is not the best way to visualize the data, especially when many polygons are undergoing mutations and data is collected at very fine scales (i.e. every 5 minutes).  For me, spatial-temporal visualization must involve some sort of animation/video that enables the user to select the speed it is played. This reminds me of the Agent-Based Models we saw in class.

Ally_Nash