GIS From the Perspective of an Undergrad

September 8th, 2014

When reading the Wright article that outlines the debate on whether GIS should be considered a science or a tool there were some very interesting points raised. The article made me think for the very first time about the significance of the definition of GIS and what it is categorized as. I had never stopped to think that the difference between the words ‘science’ and ‘system’ could be such a debate. Additionally, this seemingly unimportant word choice has a huge impact on possible grant money, tenure, and overall legitimacy in the education and scientific community. Whilst reading the article I couldn’t help but begin to wonder where I fell on the ‘fuzzy spectrum’ of GIS classification. As a undergraduate student at McGill I found myself most drawn to the argument of GIS as a tool; as this description of GIS was one I could recognize. However, I began to wonder how my position and current status as a geography undergraduate student affected how I viewed GIS. For me, GIS was always a set of equations and methods used on a set of data to store, process, and analyze it. Furthermore, one could use these results to make some rather visually stimulating maps for projects. However, reading further into the article I realized – perhaps an individual’s positionality affects how they use and thus define GIS. For a software developer such as ESRI, GIS is perhaps seen more as the second position of GIS (as toolmaking) because they focus mostly on the coding and design of the computer program. For professors or other academics, GIS may be a science as they use core concepts (usually integrated into the software) to explore hypotheses/research. Therefore, the categorization of GIS would differ based on the person doing the categorizing.

The article – while excellent at provoking a stream of thought in my mind – was also somewhat confusing in certain parts. I found that there was a general lacking in of a clear definition of GIS. In each of the three ‘positions’ one can take on GIS, I found that Wright picked elements to his liking and molded the definition of GIS to properly fit that viewpoint while completely ignoring other key elements of the ‘system’. This brings me to my next point of contention: that Wright mentioned in the introduction that the ‘s’ in the GIS stands for ‘system’ rather than ‘science’. Unfortunately, Wright never thought to indicate to the reader what he means by Geographic Information System, how it differs from ‘science’, and how it connects to the debate. Finally, I thought that the discussion on what it means to do ‘science’ was somewhat vague, as no concrete definition of science was ever described. This part of the article felt very heavily based on philosophy (concerning the ‘isms’) and didn’t feel like it was doing what it was supposed to – which was to describe what science is.

Overall I liked the article, it made me think about what I study and how it is viewed by other people. Being as I am I figured: I’ll study what I like and not worry about what other people think – now I am not so sure. It also made me think about how I will describe what I study to my friends and family, do I focus more on the scientific aspects of GIS, the toolmaking, or the tool itself? At any rate, I think this seemingly circular argument of the word ‘science’ over ‘system’ all boils down to semantics should be left to the linguists for now.

Until next time,

Nod

Posted in General | Comments Closed

On “An account of the origins of conceptual models of geographic space” (McNoleg 2003)

September 8th, 2014

An entertaining article written by an author operating under the pseudonym Oleg McNoleg on the origins of geographic space. The Tessellati live in northern Europe on the husbanding of a highly territorial, wooly, egg-laying dairy pig. Since there is only a small amount of available land and the pigs are intolerant of all other life forms, a highly-organized system was developed where each pig lived in a regulation-sized pigcell to ensure optimal packing density. The Tessellati’s story comes to a short end as their diet consisting solely of this pig-splice-product takes a toll on their health. In a far-away tropical land, the Vectules live on the edge of an angry ocean. To survive, they must rely on the absence of parrots (who were a result of a genetic experiment gone bad) on high tree branches to escape the rising of ocean waters, a result of global warming. This tribe however progressed: “they moved inland and developed a taste for barbecued parrot” (2).

Of course, the conclusions greatly aid the understanding of the article. The Tessellati represent the raster data structure (‘pigcell’ = ‘pixel’) and the Vectules represent the vector data structure (‘abscence of parrot’ = ‘poly-gone’ = ‘polygon’). This story-telling version of the theory of geographic space is definitely an interesting way of explaining it, and this article should unquestionably be assigned reading for GEOG 201. Besides, the article is wrapped-up with the most humorous corollary.

– Solfar

Posted in 506 | Comments Closed

Pigs, Parrots, and People–Oh my!

September 8th, 2014

McNoleg’s brief article gave me a whole new appreciation towards the concept of academic story telling. What does egg-laying pigs, parrots, and advanced geography information systems have in common—well, not much other than the basic understanding that geography is EVERYWHERE. This article told the story of two mystical peoples from an ancient land that struggled to survive given exceptionally unique circumstances. Although, humorous, it makes me wonder if our current society will be judged any different against the ages of time?

The four self-evident truths precipitated from this article were: “(1) watch your diet, (2) beware of global warming, (3) do not mess with genetic engineering, and (4) if a system starts to extol the virtues of owning something that does not actually exist, it is time to change the system”. At face value, these four recommendations come across as ambiguous and overly generalized. However, I believe that there might be some teaching value to each of these given the correct context.

The first truth, may be correlated to our current expansion of monoculture of agriculture crops across much of the world. It wouldn’t be difficult to relate our over dependence on soy or corn to the Tessellati people dependence on that bizarre pig creature. Point 2 is a bit more forthright and applicable given our current climate trends. However, I struggle to understand why this obvious point is even mentioned given the aforementioned stories. Point 3 can be fiercely argued on a techno-optimist vs. anti-GMO platform, however for the sake of geography, I feel that this may be loosely translated to the fact that severely altering a species (i.e. pig), may limit our geospatial distribution and genetic fitness. Finally, point 4 can be simply be transposed into H.G. Wells saying, “Adapt or perish, now as ever, is nature’s inexorable imperative”.

–BreadPool

 

Posted in 506 | Comments Closed

On “GIS: Tool or Science” (Wright et al. 1997)

September 8th, 2014

According to Wright et al., the GIS: tool or science debate is an important one in the daily lives of geography departments. The article uses the online 1993 GIS-L discussion as the starting point for this “tool versus science” debate. The article claims the “length and intensity of the discussion made it clear that the ‘tool versus science’ debate sparked an interest among many scientists, technicians, and practitioners, whatever their discipline” (347). Although I wouldn’t call “64 postings from 40 individuals in 8 states and 6 countries” (347) “intense” (although things were different in 1993), the “tool versus science” debate is valid nonetheless.

In the GIS-L discussion, I think that the people who claim that GIS is a science understand the arguments of the people who believe GIS is a tool, and simply disagree with them. However, I wonder if the opposite is true. Many of the “GIS is a science” arguments are more intellectual and difficult to understand, and given the informality of the GIS-L discussion, it may not be too far-fetched to think that at least a few of the “GIS is a tool” people do not fully understand the implications that the “GIS is a science” people are making. I include myself in this bundle since, after reading the article, I am still on the fence since I have trouble understanding many of the “GIS is a science” arguments myself. Could GIS be both a tool and science? The author asks if “doing GIS” is “doing science”. It seems to me the answer to this would be “sometimes”. I would think that it depends on what you are doing with GIS. If you are using it in ways described in the “GIS is a tool” side of the GIS-L discussion, then, for your use, GIS would be a tool. If you are using it in ways described in the “GIS is a science” side of the GIS-L discussion, then, for your use, GIS would be a science. I don’t quite understand why GIS cannot be both, or maybe I haven’t fully understood the debate.

– Solfar

Posted in 506 | Comments Closed

Tale of the Tessellati and the Vectules

September 8th, 2014

What on earth did I just read? The editorial piece credited to the fictional character Oleg McNoleg possesses a fine balance of creative writing and sound GIS theory – the piece was a too outré for my liking but the conclusion wrapped it up nicely.

Using two fictional prehistoric European tribes Oleg explains the two prevailing conceptual models of geographic space that are used in GIS, raster grids and vectors. The Tessellati live on arid land surviving off territorial pigs that are isolated to individual cells of equal size that cover their small kingdom – they represent the raster data structure. The Vectules are forced to occupy non-uniform spaces in trees where parrots don’t exists to seek refuge from the tempestuous oceans that rage below – this less restrictive society represent the vector data structure. It was interesting to note that the Tessellati was wiped out, however the Vectules went on to survive – I won’t speculate whether this indicates the preference of the author or not.

As bizarre as it may have been, the article was awfully effective in explaining the concepts in a memorable way, it was challenging to see the relevance of all the detailed nuances but nevertheless it grabbed my attention. The conclusions paragraph was essential to the explanation of the spatial data structures, without it the piece wouldn’t hold any water.

If anything this is a reminder of the many differences between raster and vector data structures – something worth considering in the framing of our upcoming GIS research projects.

– Othello

Posted in 506, General | Comments Closed

On GEOGRAPHICAL INFORMATION SCIENCE FIFTEEN YEARS LATER (Goodchild, 2006)

September 8th, 2014

Did GIS ultimately gain wide acceptance and legitimacy because of, rather than in spite of its use as a tool?

“My intent was to capture those aspects of GIS research … that could drive a science that would eventually earn the respect of the academy – that would lead, for example, to election of GIS researchers to the US National Academy of Sciences or the UK’s Royal Society (the field has been successful on both counts), or to the establishment of professorships in GIS in the most prestigious insitutions (sic).” (p. 2).

“The concept of GIScience seems to have been adopted enthusiastically.” (p. 2).

“After 15 years there seems every reason to believe that GIScience is a genuine, challenging, and fruitful area for scientific research with its own unique scientific questions and discoveries.” (p. 2).

I would still question whether this condition could ever have materialized without the expanded use and application of GIS as a tool, particularly with the impact of the Internet and the Web, and therefore perhaps much of the adoption of GIScience relates less to the unique scientific questions and discoveries of GIS and more to the niche that GIS fills primarily as a tool and methodology. I see this reflected even in Goodchild’s concluding topics: Integration of processes, use by nonexperts and citizens, and application to non-geographic spaces. Each of these to me speaks to the expansion and development of GIS as a tool rather than a distinct scientific discipline. I would also ask whether fruitful and challenging epistemological questions regarding GIS as a tool remain under-emphasized in this quest for greater respect and the associated resources as a science.
Mabu

Posted in General | Comments Closed

On GIS: Tool or Science? (Wright et al., 1997)

September 8th, 2014

“The ‘tool versus science’ debate has received little mention in the published literature of geography “ (p. 348), despite the attention given to GIS. A non-issue for most practicioners and researchers? Wouldn’t it fall within the scope of any ongoing debate on epistemology and methodology (philosophy of science) that researchers and the scientific community must bring to bear on any chosen method? Shall we assign the term “science” to any methodology, or is the methodology itself one component, albeit an important one, of scientific inquiry? Would a more fruitful framing of the debate involve the appropriate application of GIS-as-a-tool to the type of research in question, again, as with any chosen method? I guess I’m confused about the nature of the debate, and whether there really is much of a debate here beyond a handful of researchers beating their fists on an open door. (In a time of viral online phenomena and 1000s of hits instantaneously, the description of 64 comments among 40 people over 34 days as an intense discussion seems quaint and severely overstated.) The authors of the article appear to have their hat in the ring on the GIS-as-science end of the spectrum. I can see that the design of GIS, as with any research instrument, can be approached scientifically and empirically, but I am not aware of a theory of GIS (I readily acknowledge my ignorance here!). I tend to agree that geography or other disciplines are the science, GIS the tool.
I agree with Wright’s comment that “GIS encompasses the way in which geographical info. is collected, perceived, managed, and used” (p. 351), but this point would apply to any scientific methodology and not cause us to redefine the methodology as a science. My sense is that doing GIS is part of doing science, but not a science unto itself. The point of Goodchild (1994) that GIS can be applied to the spectrum of scientific approaches including positivist and nonpositivist approaches to me supports the view that GIS is more appropriately understood as a tool rather than a science.
Is the question driven by a now-outdated concern that because GIS labs, courses, and GIS-based research require significant investments of resources, that such investments would be more likely if given status of science unto itself? And perhaps even a desire for greater legitimacy? It seems now that the wide acceptance of GIS as a tool has helped address both these concerns. The Goodchild update “Fifteen years on” may provide some insight.
Mabu

Posted in General | Comments Closed

Pigcells and Poly-gones

September 7th, 2014

“An Account of the Origins of Conceptual Models of Geographic Space” – Oleg McNoleg (1996)

 

A humorous writer under the pen name, Oleg McNoleg (of Noplace, USA), provides an amusing pseudo-history of the origin of geographic space. According to the author, the pigcells and poly-gone conceptions of space laid the groundwork for the pixel and polygon. The imaginary Tessellati and Vectules pay homage to the tessellation-like, uniformly-shaped cells of raster data and the “freeform spatial unit” of vector data (2). This narrative illustrates how raster and vector data types emerged through different needs and subsequently fulfill different spatial requirements. I am unfamiliar with the actual origins of the pixel and the polygon but I imagine they were not conceived under the same research conditions.

This may be stretching the allegorical meaning of this parody, but perhaps the narrative’s absurdity is meant to draw attention to the weird ways in which people conceptualize, use, and are dependent on space. McNoleg mentions that the Vectules’ ‘poly-gone’ industry made it “possible to sell somebody absolutely nothing and get away with it” (2). We now live in an age where mapping technologies are sold for millions or even billions of dollars e.g. Apple’s acquisition of Embark and Google’s purchase of Waze.

On a side note, I believe this article may set a record for oddest list of keywords.

– BCBD

Posted in General | Comments Closed

A GIS Time Capsule

September 7th, 2014

“Geographical information science” – Michael F. Goodchild (1992)

 

Written in 1992, Michael F. Goodchild’s paper, “Geographical information science” is an intriguing time capsule of how one GIS researcher characterized the discipline. Now—some 22 years later—we are in an exciting position to assess how much GIS has evolved. Unfortunately, we still “tend to treat our GIS displays as if they were virtual sheets of paper,” however, I am happy to report that technologies such as Google Earth have improved the representation of the spheroid (33). Global-scale applications such as Google Earth & Maps and open-source projects such as Open Street Maps must have been unfathomable to researcher in 1992. Additionally, three-dimensional graphics are improving steadily and filling out the z-axis, previously limited by aerial stereoscopy and elevation isolines. Three-dimensional projections are even finding their place in the abovementioned Internet applications and are being incorporated in public platforms such as YouSayCity. In “Geographical Information Science Fifteen Years Later,” Goodchild acknowledges that he completely underestimated “the impact of the Internet” (2007).

The accessibility of technology is another major way breakthrough that flew under Goodchild’s radar. Goodchild, circa 1992, mentions that a “digital field geology notebook” could be a possible future technology for research (35). Goodchild believed such a technology would be niche product for academics and industry. The capability and proliferation of smart phones was an unimaginable event that would change the ways through which people utilize geographic information. I believe Goodchild would stand by naming Google Maps the “Killer App of the 21st Century.”

On the topic of accessibility, it is interesting to point out that Goodchild addressed the ethical issue of GIS’ relationship with society. In particular he questions whether GIS will empower those already with power or if it will be used to redistribute power to those without it. It surprises me that GIS researchers were already considering this issue in 1992. I wonder what Goodchild thinks of the emergence of grassroots mapping projects.

– BCBD

 

Posted in General | Comments Closed

Geographic Information “Science”

September 7th, 2014

“Geographical Information Science Fifteen Years Later” – Michael. F. Goodchild (2007)

 

Michael F. Goodchild is a staunch believer in GIS as a science. He notes how GIS researchers have been elected to the US National Academy of Sciences and the UK Royal Society, and GIS has proliferated within academic institutions. Additionally, as with other sciences, GIS is characterized by research subdivisions. Goodchild’s analysis of the state of GIS seems sound, however, I am left with the question of what his ontological quest is aiming to achieve. What is to be gained by being labelled a science and what could be lost?

Goodchild’s campaign to validate GIS as a science may have undesirable consequences. Entrenching GIS’s place in the rigid, evidence-based confines of science may cement the multifaceted “S”, which may have an exclusionary effect on the diverse GIS community. GIS researchers that exist beyond the realm of academic science are most at risk of exclusion. The way I see it, GIS could lose its creativity, flexibility, and uniqueness if the focus on scientific endeavour becomes all encompassing.

An anecdote from the 19th century can shed light on the issue of ontology within a discipline. In late 19th century France the Académie des Beaux-Arts was the ultimate authority in fine art. One was called an artist only through the validation of the cultural institution. Early impressionists, such as Monet, Manet, and Cezanne sought affirmation from the Académie, but under the scrutiny of the institution their work was rejected. Understanding that the Académie placed them outside the realm of fine art, the Impressionists began to exhibit their work independently, seeking credibility outside formal settings. By forgoing the Académie and committing themselves to abstraction, unusual subject matter, and a disregard for orthodoxy the Impressionists revolutionized the art world. The movement transgressed the boundary of fine art and initiated a paradigm shift paved way for the conception of fine art as we know it today. Instead of trying to pigeonhole GIS within present-day science, perhaps GIS is better of on its own path.

– BCBD

Posted in General | Comments Closed

Placing GIS in a box: Wright or Wrong?

September 7th, 2014

We naturally gravitate towards labeling things, placing them in categories so as to make our world a more organized and orderly one and GIS (geographic information systems) are no exception to this way of thinking. In the article titled “GIS: Tool or Science?” Wright et. al, address the “ambiguity of GIS as a tool or as a science”, introducing in third position of GIS as a toolmaker with advancements in capabilities and usability.

Albeit a trivial question, it speaks to the identity crisis GIS and its practitioners may have experienced in its early years, and even still today. The implications of whether GIS is a tool, tool-maker or a science are wide spread. Most noticeably for the quest for academic legitimacy of GIS as a science – as a student without this legitimacy what place does my GIS-related or GIS-driven research have, if any?

It was a sound article that effectively introduced the three positions. I feel it lent itself more as prompt to engage the reader in the on-going conversation sparked by the online forum discussion that tackled the issue back in 1993. A lot can happen in 20 years, I do wonder what would the GIS community and others would have to say on the topic over a decade since the publication of this journal article. The Journal of Geographical Information Systems publishing since 2009 perhaps satisfies the academic merit GIS would need to be considered a science by some of the forum participators. This said, I would say that Wright’s proposition that the phenomena of GIS is ‘a continuum between tool and science’ rings strong and true today.  My response to the question, you may ask? D. All of the above, GIS is ever evolving, and can’t be placed in a discrete category.

– Othello

Posted in 506, geographic information systems | Comments Closed

Week 1_GEOG 506: GIS: Tool or Science?

September 6th, 2014

System, science, or something in-between; geospatial practitioners have been diligently compartmentalizing the true definition of Geographic Information Systems (GIS). The Wright article takes an open source approach to capturing the thoughts, perspectives, and beliefs towards this debate, by providing a framework of discussion through an online forum. The underlying basis between differentiating GIS as a science or tool stems from the authors apparent desire to establish a greater understanding to the academic and science community.

Throughout reading this article I struggled with the understanding of ‘why’ any of this matters? The article even goes so far as to mention that this purpose of this debate relies on the subtle reality that one classification (i.e., science) might have a greater apparent “superiority” over another (i.e., tool). The authors goes to great depth to explain that all GIS users must find an equilibrium between “falling into scientism” and “dragging it off its (science) pedestal”. As per the recommendations, academic institutions might have to alter their teaching approaches to adequately represent their GIS objectives. However, for the every-day GIS practitioner, little of this article would sufficiently change their program use or career objectives. For those who use GIS as a tool, tool-maker, or science, it may not necessarily matter the nomenclature. Such as an architect may not agonize over the perceived differences of their work for the intrinsic physical purpose or overall artistic value.

The article itself was in-depth and offered a bias-adverse perspective communicated through the numerous contributing forum members. Although, this article was written almost two decades ago, the argument remains valid and remains useful towards the ever-changing field of geographic information systems and science.

–BreadPool

 

Posted in 506 | Comments Closed

Remote sensing uncertainty in GIS

April 5th, 2013

The article of G. G. Wilkinson is dated, and this is significant in a field that is rapidly evolving. Nonetheless, in my point of view, the author’s argument is still valid today. He talks about uncertainty and data structures in remote sensing and GIS. Sophisticated technologies and remote sensing don’t automatically solve the problem of delimitating boundaries. Even with technology development, classification is still a complex task. It is like trying to create boundaries where the world is actually maybe more like a continuous landscape. We are trying to define distinctive class of land cover or topographic zones for example, but in reality is there a frontier between different types of land? It partially explains why uncertainty is attach to any kind of techniques in remote sensing. Taking the limits of remote sensing techniques into account, the author evaluate different procedure and use of data structure. He thus suggests that part of the further development is to identifying the best techniques and technology development that will allow the best representation of the phenomenon that is intended to be represented by the remote sensing data. Although the problems of errors and uncertainty are unlikely to be solved easily even with technical development in data structures or with visualization techniques such as 3d environment and virtual reality.

S_Ram

Posted in 506 | Comments Closed

Certainty of Uncertainty!

April 4th, 2013

Helen Couclelis wrote an article called Certainty of Uncertainty and I think that David J. Unwin is making a similar point. The problem of uncertainty is not merely technical. Uncertainty doesn’t only come from data and information but it is also about geographical knowledge that is sometimes inevitably uncertain. There are things that we simply can’t know. The literature focus on finding technical solutions, but the author explains that “at the heart of all the contributions is a concern for exactly how we can usefully represent our geographic knowledge in the primitive world of the digital computer”.

As mentioned in previous discussion about ontology, we conceptualize the world as field or object based which correspond to raster or vector in GIS. The author shows that both representation comes with specific uncertainties. Furthermore, we discussed how delimitating boundaries is often a difficult task and uncertainty is inevitable. The conclusion is bringing us back to the first discussion in class about GIS as a tool or as science and the determinism of the technology. The author suggest that rethinking the way we use the technology and the way we structure problems and databases is essential to achieve sensitivity in GIS. It is about adapting the technology to represent knowledge in a way that would take into consideration our conceptualization of the world and not merely relying on GIS technology to calculate the world for us.

Couclelis, H. (2003). The Certainty of Uncertainty: GIS and the Limits of Geographic Knowledge. Transactions in GIS, 7(2), 165-175.

S_Ram

Posted in 506 | Comments Closed

Uncertainty

April 4th, 2013

Uncertainty lies at the core of GISci where MacEachren et al. acknowledges the GISci community has given more attention to formalizing approaches to uncertainty than in other communities such as information visualization communities (p. 144). The authors go through several examples of how uncertainty can be visualized from changes in hue to symbols with different transparencies to depict where uncertain data may exist. What peaked my interest was the interactive visualization techniques that users can control depictions of uncertainty. Instead of permanently adding a layer of complexity that can obstruct and confuse the readers from what the data is trying to depict, the user is in full control of how much or little information (with regards to uncertainty) is available to them. To me this seems like a better solution than to simply find a single “ideal” ways to represent uncertainty visually in a static manner – especially since every individual will have their own preferences on what they think “best” means (context matters!). What I don’t quite agree with is the authors’ assertion that humans are not adept to using statistical information to make decisions and base on heuristics (based on a study in 1974). Since the quantitative revolution, hasn’t statistics been bought to the forefront of geography such that we may rely on statistics too much at this point? That being said, visualizing uncertainty can take on many forms, from charts, changes in opacity, 3D graphics where the way in which uncertainty should be viewed will ultimately be context specific to meet the goals of the researcher.

-tranv

Posted in 506 | Comments Closed

Integrating RS and GIS

April 4th, 2013

Brivio et al. provides a case study where the integration of GIS and RS is able to compensate for limitations that may exist in each technology. The study provides a good example of how these two closely related fields can combine together to produce a more realistic representation of various phenomenon. While this case study specifically used additional GIS data as a supplementary component to improve on the RS classification of flooded areas, RS data can similarly be used to as a tool to produce GIS data (ex. land cover classification dataset derived from remote sensing data). However while there are many advantages in integrating the two, several issues come to mind. RS data is pixel based, while spatial data can be vector or raster based. To have to convert one to the other in order to do analysis would compound issues of accuracy and uncertainty. We know RS is already well acquainted with their own issues related to scale, noise and technological limitations, but these issues can quickly get amplified, and I can imagine that recognizing these sources of uncertainty will be difficult once the data thoroughly entangled in one another.  Also, what kind of data models is required for this integration? Spatial data is generally represented in 2D, while RS hyperspectral cubes are in several dimensions.  For the researcher whose interested in integrated such technologies, they have to be well versed in the inherent issues that each type of data presents to provide a comprehensive analysis – definitely no small feat.

-tranv

Posted in 506 | Comments Closed

Visualizing uncertainty

April 4th, 2013

MacEachren et als article provides a thorough overview of the current status of uncertainty visualization along with its future and its challenges. It seems to be established that uncertainty visualization is more useful at the planning stage than at the user stage of an application. This makes me think back to an earlier discussion on temporal GIS. We talked about how the important aspect of temporal GIS was in its analytical capabilities, rather than in its representational capabilities. While I do not deny the positive effect on analysis that visualization might have, I question if it should be the aspect of uncertainty that is given the most attention.

Two of the challenges proposed by the article are developing tools to interact with depictions of uncertainty and handling multiple kinds of coexisting uncertainty. Might representation in some instances prove more troublesome than its worth? Might representational practices at times be obfuscative of data that might be understood as just data? I want to note that I am asking these questions in earnest, not rhetorically. Which I guess boils down to a question I have probably asked all semsester: how do we evaluate what is important enough or useful enough to invest time in?

Wyatt

Tags:
Posted in General | Comments Closed

Are We Certain that Uncertainty is the Problem?

April 4th, 2013

Unwin‘s 1995 paper on uncertainty in GIS was a solid overview of some of the issues with data representation that might fly under the radar or be assumed without further comment in day-to-day analysis.  He discussed vector (or object) and raster (or field) data representations, and the underlying error inherent in the formats themselves, rather than the data, per se.

While the paper itself is clear and fairly thorough, I can’t help but question whether error and uncertainty are worth fretting over. Of course there is error, and there will always be error in a digital representation of a real-world phenomenon. Those people, such as scientists and policy makers, who rely on GIS outputs, are not oblivious to these representation flaws. For instance, raster data is constrained by resolution. It is foolhardy to assume that the land cover in every inch of a 30-meter grid cell is exactly uniform. It is also wrong to suggest that some highly mobile data (like a flu outbreak) would remain stationary over the course of the interval between sensing/mapping. There are ways around this, such as spatial and temporal interpolation algorithms and other spatial statistics, and I feel like estimates are often sufficient. If they aren’t, then perhaps the problem isn’t with the GIS, but rather in the data collection. Better data collection techniques, perhaps involving more remote sensing (physical geography) or closer fieldwork (social geography) would go far in lessening error and uncertainty.

With all of that said, I am not about to suggest that GIS is perfect. There is always room for growth and improvement. But, after all, the ultimate purpose of visualizing data is for understanding and gaining a mental picture of what is happening in the real world. An error-free or completely “certain” data representation is not only impossible within human limitations, but it is not particular necessary.

– JMonterey

Tags: , ,
Posted in 506 | Comments Closed

April 4th, 2013

No matter how good technology becomes, we will always face challenges in data uncertainty and error; the question is, can we develop appropriate techniques to mitigate the effects of these noises, and come away with the correct signal. As MacEachren et al. (2005) point out in their article titled “Visualizing Geospatial Information Uncertainty”, we use this information to base decisions off of, and the uncertainty is inherent in the data and must be taken into account.

There are multiple dimensions of uncertainty, as the authors point out, ranging from credibility of a source to precision of a physical variable, and these will compound, effecting the amount of correctness the end result will have. They function across many scales, including the direct attribute of the information, the specific context or location of the information (which may not be what you want to apply the information to), as well as temporally. It all seems very complicated when examined through this framework… but it is important to take these into account in order to have confidence in your product.

 

Personally, i have experienced a lot of uncertainty while trying to create a global map of administrative subdivisions. Every County collects data at different resolutions and time, however these countries are supposed to be contiguous as we well know. The borders do not always align, but who is right? Furthermore, this issue is compounded when you consider the global land mass as a whole. We want to have an accurate total area of land surface, however if you trust each country to represent their land correctly and then end up with an incorrect total, who is wrong? Where do you remove land? Where do you add it? These are some of the challenges I have faced with uncertainty, and I was not qualified to make the adequate decision.

 

What I didn’t do at the time was try to quantify and visualize the uncertainty, which as the authors say, is  crucial to making sure the data is useable, and that you are confident it is correct for answering the questions you are trying to answer.

 

Pointy McPolygon

Posted in 506 | Comments Closed

What’s the hard part now?

April 4th, 2013

Remote Sensing and GIS technology has changed significantly since Wilkinson (2007) wrote his review on how the two fields overlap. Hyperspectral imagery is now commonplace, and the software is well equipped to deal with it. Currently, we still struggle with handling error and uncertainty, but there are prescribed ways for dealing with each issue. Atmospheric conditions, topography, angle, sensor, and georeferencing are now done to eliminate some of the error caused through data collections. Things like fuzzy logic help to deal with uncertainty, although it remains an issue. As data collection techniques further improve, our ability to deal with this uncertainty will become less and less important.

Most of the current issues still lie in data models. The complementary nature of GIS and Remote Sensing is evident, however these two technologies speak different languages in situations where we expect them to communicate and enforce their complimentary relationship. This becomes even more difficult when we try to represent more complex relationships that are no longer 2-dimensional with hierarchical classifications. Personally, I find that the 2 commercial softwares for each technology interact quite well when performing simple tasks, like making a supervised classification and turning that into a GIS layer. However, when the data becomes more complex, and the classifications with them, the ability of the softwares to communicate with each other becomes increasingly bad.

 

Pointy McPolygon

Posted in 506 | Comments Closed

« Older Entries
Newer Entries »