Posts Tagged ‘GEOG 506’

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Will You Volunteer?

Thursday, February 28th, 2013

Goodchild’s article does a great job of giving an overview of the history, components, and some of the uses of Volunteered Geographic Information (VGI). Though he does a great job of highlighting the many benefits to this huge source of data, he also acknowledges some of the issues that arise with dependency on this type of data.

The are several issues in particular that I believe affect the future of the field. First of all, standardization of data is an issue when dealing with volunteered information. Contributors may not know the correct way to upload and cite data, which in turn could affect the results. This issue has been addressed somewhat by the use of volunteers who monitor the data, as well as agencies that have outlined the way to standardize certain types of data. Another issue is the ability of certain user to undermine the collective effort. This issue in particular is ever more relevant as larger and larger databases are compiled. Although it is generally accepted that contributors are working together for the collective good, there is a possibility that some people, with ulterior motives, could undermine the collective effort.One example of this is when anonymous users tamper with Wikipedia pages. Wikipedia allows any user to edit the content of its pages. And while there are some volunteers who monitor pages for legitimacy, there is a possibility of people propagating false information.

Overall, VGI has the ability to be a very useful field for current and future collective projects. However, there are still some issues that need to be addressed before it can be relied upon for important policy decisions.

-Victor Manuel

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Living in a Virtual World

Thursday, February 28th, 2013

As I was reading through Richardson’s article, I kept thinking to myself time and time again- why aren’t Virtual Environments and effective tool for learning the layouts of real environments? It stands to reason that if the real environment is reproduced at a digital level, a test subject should be able to gain a similar amount of knowledge about the environment as a person who walked through said environment in real life.

Therefore, as the authors outlined some of the limitations of a VE, I started to brainstorm how an accurate and effective VE could be constructed and displayed. One of the main issues withe using VE as a learning tool was the alignment effect- user of the VE could become disoriented, especially when rising sets of staircases. One potential solution to this conundrum could be the creation of a sort of “immersive” virtual environment, which visually surrounds the user. This could be achieved on a relatively portable scale through the use of some sort of “full experience” headset, which would make it appear as if the user is immersed in the real environment. Overall, the paper raises very though provoking questions about the limitations of Virtual Environments; especially how they are still not a viable substitute to experiencing said environment in real life.

-Victor Manuel

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Map memories

Thursday, February 28th, 2013

In their 1999 study, Richardson et al. compared how subjects learn to navigate their environments from maps, navigation, and virtual copies of the environments. They found that people tend to learn more effectively from maps than from virtual environments. The paper itself is thorough and describes in detail the authors’ procedure and findings. I happen to think the final discoveries, however, are not terribly surprising.

I have always thought that some people (such as myself) are naturally “map people” while others are more “trial and error” or experiential learners. While map readers are, according to Richardson et al., heavily dependent on consistent orientation, they are more aware of the greater surroundings and the bigger picture. Being aware of causality, such as “if I turn left, then I will see the elevator at the end of the hall,” enables one to form mental maps and think ahead in the navigation process. Experiential learners, on the other hand, will most likely navigate by landmark in a step-by-step process that is more shortsighted. Additionally, in terms of longer-term memory, I would not be surprised if map readers could, in a sense, recite a navigation process from memory more easily than could an experiential learner. These are just my conjectures, but if Richardson et al. had accurate conclusions, then it is fairly clear that map readers are already at an advantage.

– JMonterey

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Technology: Changing Spatial Cognition

Thursday, February 28th, 2013

Tversky et al.’s article, “Three Spaces of Spatial Cognition” places human cognition of space in an easy to understand framework of 3 understandings; the space of navigation, the space around the body and the space of the body. In GIScience, it is important to understand how human perceive the world we live in, as it determines how we create the GISystems and how they are used to display and modify geographical data.

The article seems to represent the idea of spatial cognition well from the point of view of psychology, but lacks in how new adaptive systems and digital mediums are modifying the ideas within spatial cognition and how humans see the world. For example in my research, the use of an iPad with 3D maps and real time tracking. The use of this technology has caused me to now perceive the world in a vertical and dynamic manner. To elaborate, before I would look at the world and place objects or places in relation to myself (like in the article), but now I place them in relation to other objects and view them as being at dynamic locations, moving as I move. I like to think of it in the context of a video game where game play maps were once set in a player centric way. However, because technology has changed, the game maps have evolved into 3 dimensional dynamic maps with distances and locations that change with the movement of the player, the other characters, and changes in the game play environment itself (no longer N-S-E-W maps).

I feel that the article would have benefited from more computer scientist and geographer input into how GI programs and geographical education can help, hinder or change the perception and way we see our space and place. Furthermore, the addition of AI research ideas into how robots navigate (maps, gps, image navigation, range finders, etc.) would have provided a better understanding of spatial cognition in the digital world of today and not just a psychology interpretation.

C_N_Cycles

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AR: The issues left behind

Thursday, February 21st, 2013

Hedley’s article, although a great summary of the progress made in AR does not truly convey the issues of use. One of the biggest down falls for AR, currently, is that sensory feedback to the user is lacking. Although, a lot has been done to try and get input to and from the user (the creation of mice and touch screens; Both Steve Jobs inventions) that combine and provide physical (touch of tool), auditory (clicks), visual (screen illumination), nothing is 100% satisfactory. The “Holodeck” from Star Trek is an example of how feedbacks entertain all senses and provide a full range natural feedback; i.e. you can physical feel the change, hear the change, see the change, and smell the change.

Ipad screens and Microsoft connect modules may provide a link to the computer and bridge the gap in what is reality and how we can understand our surroundings, but lack that basic human need for satisfaction of a response. To elaborate even if physical objects can be manipulated to create change in the presented reality they are not perfect. The objects that are used are generic, such as balls or cubes, and do not provide a universal design for all settings or sensations. Basically, the texture of what is viewed is not necessarily the same as the object being manipulated. To correct for this an infinite amount of objects would have to be stored in order to represent the same object in reality and within an AR system. One solution I believe to this problem may be the use of non-Newtonian or electromagnetic fluids feedback mechanisms that can be altered to many states and textures.

Finally, Hedley’s article seems a little out of date as 3D no longer requires glasses and tough screen interfaces are leaps above what is discussed (Thanks to Apple’s and Steve Jobs’ push for natural interfaces). As a last note, I feel there is also a lack of discussion on digital representation of images in AR and how they can be too cartoony or not real enough.

C_N_Cycles

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Critical GIS: Ethics, a Ghost of the Past

Thursday, February 21st, 2013

Robert Lake’s article “Planning and applied geography…” take the idea to have transcending ethics between field to the extreme. I believe that the type of ethics, or extent, is unique to a field of study and common and should not be pushed into areas where grey zones outnumber the black and white. This article seems to try and force the idea of practitioners as absent minded of ethics, void of the knowledge of technology’s impact on society. Maybe it is my “laissez-faire” attitude or ideals of “I do not care what you believe in, but just do not push it on me ” that is speaking, but I do not believe practitioners have forgotten ethics and their applicability to structuring research in the digital realm. I would argue that it is how the ethics are applied that has changed and is causing this misunderstanding. For instance equal access to GIS data is not truly flawed, as inferred by Lake, as this data can be altered by user and re-published as a modified version, i.e. multiple users can use the data and modify it for themselves to create multiple ethical data sets, that correspond to the user’s ideals and background.

When Lake talks about a means to an end, this is a theoretically flawed assumption, because any good researcher or user of GIS knows that there is no end only a variable set of conclusions that lead to more elaboration of data and a refinement of GIS systems. I personally consider GIS a dynamic tool for representing geographical data in a changing world. Furthermore is it not the idea to show the variety of data from differing backgrounds during analysis to create a mosaic of geographic data that can lead to new discoveries.

The way this article is written and the way GIS and the application of ethical thought are paired, seems disconnected to reality. To clarify the Ethical ideas that Lake speaks of are the old way, a ghost of past thought. Ethics, I believe are considered in a new way, a way that was never considered to older generations of researchers at the time. Ethics of how GIS is used is more loose today, as a global society with a million views cannot be held to the archaic structures of Freudian dynamics of how research is done and how the tools are used.

C_N_Cycles

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How Critical is Critical GIS?

Thursday, February 21st, 2013

Critical GIS attempts to combine various types of critical human geography with methods and techniques reliant on Geographic information systems. However, the field remains somewhat of a minority pursuit due to the fact that there is little evidence of critical geographers completely embracing GIS as a tool of their trade. Sullivan acknowledges seven major themes that have made Critical GIS what it is today. One of the themes that was not discussed in great detail was the “GIS and the human dimensions of global change”. I believe this field in particular has evolved tremendously since the time the article was written.  Developments in communications technologies, especially in mobile communications, web applications, and digital media, have completely transformed the way humans access information, and communicate. In addition, they have also been crucial in facilitating the availability of data, providing users with important information that allows them to educate themselves on certain fields. One only has to look at the monumental rise in average web users who know use GIS tools in their every day lives. Spatial applications such as Google Earth have expanded the field from specialists to the everyday person- who may use the application for any sort of spatial task. Thus, even though critical GIS is a relatively new field (1997), the evolution of complex technological resources has opened up many new opportunities for research within the field.

-Victor Manuel

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A Critique of the Critics

Thursday, February 21st, 2013

O’Sullivan’s critique of the critics of GIS is a good summary of the position that many people hold on the role of GIS in social sciences. The author touches on three items from a research agenda on “GIS and society,” namely the relevance of GIS in grassroots movements, GIS from a feminist perspective, and privacy issues inherent in data collection. Although there is justification for omitting discussions on the remaining four themes from Initiative 19, it would have been interesting to learn about other ways in which people are criticizing—oftentimes constructively—GIS’s role in society.

I am particularly interested in the theme of PGIS (participatory GIS), in part because I am researching VGI (volunteer-generated information) for this course. Beyond the ethical and accuracy concerns—of which I do not deny, there are many—I fail to see how PGIS might be critiqued in a social context. In fact, if the primary concern for the use of GIS in social contexts is power assertions in methods of visualization, then surely a way to collect and visualize information generated by the public is in complete contrast to this fear of authorial bias. Furthermore, if PGIS is largely volunteered (VGI), then ethical concerns are diminished, and if the data is confirmed via an objective algorithm, then the accuracy concerns are also moot. PGIS is, perhaps, the most useful method of real-time data collection possible, and it should be utilized as much as possible. As O’Sullivan notes, it is a way to empower citizens, to give them an equal voice, and I agree completely.

– JMonterey

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Augment your Reality

Thursday, February 21st, 2013

Azuma provides a great synopsis of some of the advances in Augmented Reality(AR) (in 2001), as well as raises some important points about future work that will be needed in the field. Augmented reality often brings to minded science fiction type technology. However, the reality is that advances in AR mean that widespread consumer products are not too far away. Indeed, many of the devices we now take for granted, especially smartphones, feature the use of AR technologies. Certain apps , such as Google Sky map- using the phones magnetometer, it project a view of the stars and planets in the sky, all based on where the phone is pointing. Other apps that come to mind include wikitudes, which can overlay relevant geographic detail information, based on where the camera on the phone is facing.

One exciting portion of the field concerns the use of Head Worn Displays (HWD). Azuma provides a great overview of the state of the field in 2001. However, as technology has evolved, some of the concerns and limitations have been resolved. Exciting technology, such as the new Google Glass, hold the potential to take AR technology to the next level. Problems such as size and weight have been resolved- these new “glasses” are extremely light, and really not that bad looking. In addition, with a projected cost of less than $1500, they are really not that far off from being a mainstream. One thing to keep in mind, however, is that these new technologies are far from perfect. Google Glass is dependent on wifi or a bluetooth connection to a mobile phone- not exactly the epitomy of mobility. However, they provide a product thats one step closer to making Augmented Reality technology…well, a reality to the everyday person.

-Victor Manuel

 

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Augmented Questions

Thursday, February 21st, 2013

Azuma et al. “update” (in 2001) the reader on advances, problems, and applications of augmented reality. Their intended audience appears to already be aware of the basics of registering objects and placing people in visible artificial environments. In contrast, the article we read a few weeks ago on eye-tracking technology explained seemingly advanced technological notions to the layperson much more nicely. Still, if the article’s purpose is to discuss AR from a multi-faceted perspective, discussing issues pertaining to the user, the augmented objects, and the environment, then the authors accomplished this well enough.

As someone with little to no experience with, or background knowledge of, augmented reality, I am concerned more with possible applications of the technology than with the technical side of things. Still, as someone approaching this article from a GIS-based perspective, I am intrigued by notions like georegistering and dynamic augmented reality. I’m sure the technology has advanced leaps and bounds in the past 12 years, including AR applications on smart phones that solve many of the weight and cost issues. I’m curious how AR is able to take an unprogrammed environment and situate its device so accurately within that space. Surely GPS is involved, as are internal sensors that collect aspect information, but beyond that, I am more intrigued and curious than critical.

– JMonterey

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The fence straddle

Thursday, February 21st, 2013

Another interesting paper that raises more questions for me than it answered (which likely was the point). Parts escaped me – how is feminist geography a non-spatial community? But what resonated with me the most was the advice from Goodchild that “straddle the fence” between human geography and GIS could be particularly academically lucrative. O’Sullivan interprets this statement to refer to social theory criticisms of GIS (critical GIS) and uses this anecdote to introduce the paper. I think this statement may have had broader interpretation or at least is relevant in a broader context. I think the future of GIS (and actually of many academic disciplines) may be strongest in the areas that straddle fences – with economics, with health, with resource management, with computer science, and sub-disciplines within these. And likewise, from what I understand, it seems like critical geographers do well at straddling these fences too.

[Side note: being named Pickles would be awesome (p. 784)]

-Kathryn

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Scale: Youtube videos – National Council for Geographic Education

Saturday, February 16th, 2013

Here is a video link explaining scale from Youtube:

Hope you all enjoy the awkward scale guy!

C_N_Cycles

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Spatial data mining and spatial analysis

Friday, February 15th, 2013

I am late to post and I think everyone else has already posted lots of excellent ideas about these topics! I found the spatial data mining article very interesting. I think that statistical modeling and machine learning are two disciplines which share a lot in common and in some cases may even be redundant versions of one another. When I read papers written by computer scientists implementing machine learning with data, it seems that the goal (in this case mostly through unsupervised data mining) is to improve predictive ability, often measured by area under an ROC curve, for example. The goal of models in statistics is often to estimate (causal) effects and requires a different conceptual framework for model building and selection to avoid, for example, controlling for a variable in the causal pathway.
Additionally, many of the issues in spatial data mining / spatial statistics are mirrored as well. Correlation and dependence in space and time create problems for the traditional parameter estimators in statistics and for the traditional algorithms in classification/prediction/clustering in machine learning. It’s not enough to just consider spatial dependence, it’s also important to consider nuances of spatial data which may make goals difference – such as the authors mention below figure 3.2, where they talk about how spatial accuracy should be measured not in a binary (correct/incorrect) sense but should account for how close (spatially) the classification was. I would really like to more thoroughly understand how statistics and machine learning algorithms really align and differ. It’s clear this is a highly interdisciplinary field – we need people trained in GIS, computer science, and statistics!

-Kathryn

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Scaling Issues

Wednesday, February 13th, 2013

Scale is an important issue in regards to most academic investigations, particularly within the framework of the investigation of natural phenomena. The biggest problem when dealing with these phenomena, especially environmental problems, is that these occurrences happen at various levels of scale. In addition, a single phenomena might have a particular effect on a local scale, but a completely different effect on a regional or global scale. As a result, issues arise as to best way to conduct an investigation: What scale should I use? Is the phenomena I am studying multi-scalar? How do I aggregate my results?

Marceau does a great job of identifying some of the key concepts behind scale, as well as the issues that have arisen since its evolution; most specifically within the natural and social sciences. One of the most interesting concepts identified throughout the paper was the modifiable are unit problem (MAUP) , which encompasses both the scale problem and the aggregation problem. Marceau concludes that the effects of MAUP are starting to become better understood; and this process in turn is contributing to the emergence of “scale as a science”.

The issues of MAUP bring to mind a case study I recently reviewed. This study encompassed an investigation of the effects of climate change on the Scandinavian country of Norway. An analysis of various effects such as economy, biodiversity, health etc. was performed at a multi-scalar level (national, regional, local). In their conclusion, the authors noted that at a national scale, the country was well off towards adapting to climate change. However, they noted that as scale was decreased to the regional and local scales, localized threats were discovered. This investigation serves to highlight the problem of main issues of MAUP, and how further development is needed within the “science of scale” in order to more effectively manage data at multi-scalar levels.

-Victor Manuel

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Spatial data mining: a discovery or a re-classification of knowledge

Tuesday, February 12th, 2013

Guo and Mennis speak on how data information has increased in availability making it difficult to extract the useful data, however I believe that it not just a present day problem. To clarify, although data in many fields may have once been hard to access, some fields have had an over abundance of data for decades. For example, earth related sciences have had a variety of data sets from maps and cross sections to areal photos and digital models since the 1960s, readily available. As such, earth sciences and other spatial fields of study have been data-rich for decades with vast high resolution spatial data sets. This amount of data led to the finding data a problem even before the use of digital databases and indexing.  In light of these issues, the authors may to have not considered earth science database sets when writing or had never really looked at the amount available for earth sciences, but this is just speculation.

I do have to agree, though, that the creation of data mining techniques have made data easier and more accessible to use of none experts and experts alike in many fields, even if there has been high quality spatial data for years. On the topic of fields with pre-existing data, are we then truly discovering new information or are we just re-classifying and changing the format of data to be more accessible elaborating the problem of data retrieval today. The suggestion of a framework to how data should be manipulated, stored and retrieved would solve many issues with pairing old and new data, and retrieving the data one is seeking.

C_N_Cycles

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The mountain doesn’t just get in the way

Friday, February 8th, 2013

In a largely philosophical discussion of ontology and perceptions of existence, Smith and Mark drive at some of the underlying and fundamental assumptions of cognition and geography. With the framing question “Do mountains exist?” (also the article’s title), the authors tear apart understandings of existence—boundedness, independence, universal acceptance—and conclude that how we approach that simple question lies at the base of how we perceive, and therefore visualize our environment.

This article is a fairly fascinating discussion that lends a psychology, as well as a philosophy, to GIS, a field that is largely empirical and filled with concepts we take for granted. For instance, the authors write, “Maps…rarely if ever show the boundaries of mountains at all…[capturing] an important feature of mountains…namely that they are objects whose boundaries are marked by gradedness of vagueness” (Smith et al. 2002). For something to exist, does it have to be independent, bounded, and universally accepted as such? We know that there is a mountain in a given place, but can we easily demarcate its boundaries? If not, can we truly say that the mountain exists or that it is a feature of the surrounding landscape?

The truth is that in an empirical analysis, i.e, for policy makers, these notions matter immensely, but from a geographic and informal perspective, we can understand the mountain as an object in a larger system. Thus, the mountain can exist, but its exact location does not matter and perhaps should not be of primary concern in a visualization of the landscape.

– JMonterey

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Spatial statistics analysis integration with GIS

Friday, February 8th, 2013

Anselin and Getis authored a 1992 paper on spatial statistics and the problems that persisted in the critical analysis portion of GIS. They divide GIS into four stages – input, storage, analysis, and output – and discuss the interface between storage and analysis and output and analysis. This area of GIS is where, according to the authors, many of the pitfalls of the process of transforming reality to visualization occur. One issue of concern is the integration of a database with the tools to analyze the data. Anselin and Getis offer three possibilities, including full integration in the GIS software, tools that analyze from outside the GIS, and a common format to easily switch between the spatial analysis and the GIS.

One of my primary concerns in reading an article on the fallbacks of technology is that technology changes so rapidly as to make the article nearly obsolete not long after its publication. I mention this here because in the 21 years since the publishing of the article, GIS has advanced leaps and bounds in its toolbox and user interface. Regarding the database-spatial analysis concern noted above, for instance, ArcGIS now includes at least two of the three offered possibilities. Arc is able to read several spreadsheet formats that allow for the integration of Excel if desired. Otherwise, Arc comes with a multitude of analysis tools, ranging from simple geometry calculation to more complex map algebra and interpolation methods. While databases are, for the most part, easier to organize within Excel, there is often little need to work outside of the GIS at all. Arc (and other software) comes with complicated and useful spatial algorithms that make many of the issues noted by Anselin and Gertis largely antiquated.

– JMonterey

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Integrating Spatial Statistical Analysis into GIS

Thursday, February 7th, 2013

Anselin & Getis give a good overview of the issues that pertain to the integration of Spatial analysis into GIS. Although it is quite a dated paper(1992), it does a good job of highlighting exactly why better integration wold be beneficial for the entire field of GIS. As noted by the authors, one of the key functions of a GIS is the analysis portion, which in turn encompasses spatial statistical analysis. They correctly identify this function as vital for more complex and in depth case studies in the future.

Technology has evolved a great deal since the time Anselin & Getis wrote their review. Modern day GIS now include many spatial statistic tools built right into the system. For example, for several courses I have used the “spatial analyst” toolbox in ArcGIS to perform statistical analysis of raster datasets. This toolbox holds a wide array of functions, ranging from calculating the statistics of objects in a raster (zonal statistics), to combining different rasters based on the measure of central tendency of the data (cell statistics).  In addition, there are now even excellent standalone programs made to specifically analyze statistics. Some of these programs, such as R, allow the user to perform complex statistical analysis of datasets. In addition, more complex programs, such as STATA, include a spatial component that allows the user to perform spatial statistical analysis on datasets.

Overall, the authors do a good job of providing an overview of the problems, as well as the benefits of better integration between spatial statistical analysis and GIS. However, many of the issues raised throughout their paper have been solved over the years, with the evolution and growing complexity of GIS. Spatial statistical analysis is an important component in any GIS. In the present day we have the ability the perform complex spatial analysis within GIS programs such as ArcGIS, something Anselin & Getis could only dream about at their time of writing their paper.

-Victor Manuel

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Ontologies & Information Systems

Thursday, February 7th, 2013

Ontology has often been a topic of heated discussion. Specifically, the ontology of whether certain objects, theories, etc. often raises complex ethical questions. However, ontology with regards to Information Systems differs in that it focuses on the study and clarification of certain concepts, with the objective of formulating them into frameworks that are both logical and well understood.

Ontology plays an important, and often unrecognized part within Information Systems. As different people do research within their field, the way in which the gather, record, and organize their data is shaped by their onologies. More specifically, their beliefs, values, ideas, etc. influence what they perceive as important, resulting in datasets that are often unique and idiosyncratic. These idiosyncrasies make it difficult to standardize data across fields, which in turn hampers cross-field research and analysis. Therefore, an important step going forward will be to develop a sort of “Master Ontology”, a standardized and universally accepted framework. This framework would synthesize the various conceptualizations of different communities of data users in order to make data organized, standardized, and transferable.

In their conclusion, Smith and Mark remark that a complete ontology of the spatial world is needed not only to comprehend both primary theory (common sense), as well as field based ontologies that are used to model natural phenomena such as runoff and erosion. I believe this to be extremely important, as people from diverse fields must collaborate to build comprehensive, and most importantly, standardized databases in the field.

-Victor Manuel

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Ontologies and GIScience

Thursday, February 7th, 2013

“Ontological considerations in GIScience” by Agarwal states the issues of ontologies and the communication of the data contained within the various ontology types is problematic to understanding. One way I have worked with in the past to resolve the issue of relating different ontologies is setting a accessible reference grid over the different ontology of the same area and creating a cross-referencing database that links both the human and scientific data. For example, if I selected a grid a side bar would open that would display human based data (impressions, oral histories, etc.) and any other data for that same location. In addition, neighboring grid cells can be linked to see if they represent similar data, and a referencing system based on type of ontology characteristic created. This last part is similar to what I believe Agarwal maybe alluding to in the last part of his article.

Although grouping of data may be useful, the variety of ontologies and the evolution of how humans see the world and use of GIS makes this difficult and a problem for GIScience to resolve. I believe the problem is not how we group data but how databases are mostly static in form and unable to expand to new information. That is one reason why creating grids for an area to set a standard may be the best solution, where they are related to dynamic ontology data sets. To simplify, ontologies are dynamic with many ontology layer types, set to a geo-referenced grid.

C_N_Cycles

 

 

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