Lab 4- Corey Rovzar

Maps of Madagascar

































































































































Data Source: Wikipedia

Lab 3- Corey Rovzar

For my photosynth project, I chose to map out the living room of my apartment. Although mapping part of the interior of my apartment may seem to be trivial compared to the many other places and things that could be mapped, it contains a great deal of information that gives insight into my local environment. Displayed in my photosynth are the front door, walls of my living room which contain artwork, furniture, and even my roommate. From these images, anyone can gain some understanding into my personal life. For example, the tidiness of the room might indicate whether I am a neat or messy person. Additionally, the artwork could reflect my personal tastes or things that interest me. The image of my roommate could give insight into my personal relationships and people I associate with, whether someone personally knows her or simply by judging her appearance. In essence, this photosynth is one of many maps that could be a representation of my life and could be a method for others to gain an understanding of myself.

While my photosynth could provide useful information for other to gain an understanding of my life, it is important to acknowledge the problems surrounding this type of technology. Based on the images of my living room, many assumptions are made about my personality and local environment. The tidiness of the room could indicate that I am a neat person; however, in reality, I could live very messily while my roommates are neat. Additionally, the colorful artwork on the walls was contributed by my roommates and therefore, reflects their personal tastes which could be entirely different then my own. Lastly, the images of my roommate might lead someone to believe that I have similar style and appearance when in reality, our personal styles are very different. Thus, it is very easy for images and maps to be incorrectly interpreted by the reader depending on their personal biases and perceptions.

Another problem associated with mapping technology, and more specifically volunteered geographic information (VGI), is that the geographic data can often be represented incorrectly. Another term that is commonly associated with VGI is asserted geographic information because the creator will assert the data without citing, referencing, or having the authority to assert such information (Goodchild 2007). As a result, incorrect information can be contributed to sites such as Wikimapia and Flickr, and users of these sites would receive false information about the geographic location. Not only is data incorrectly asserted by individuals, but also by larger organizations such as GOOGLE. Because GOOGLE has established itself as an efficient database, users will trust its authority and not question the geographic data it generates. However, even GOOGLE misrepresents geographic information and has been noted to misrecord geographic coordinates of locations (Goodchild 2007). Although the assertion of incorrect geographic information is most likely unintentional, Goodchild suggests that increasing popularity and reliance on VGI could result in intentional input of false information much like viruses and spam associated with the Internet (Goodchild 2007). For example, in my photosynth I could say that the images represented my living room, when in reality I could be in someone else’s apartment. Therefore, I would be contributing false information that would mislead users. Other problems associated with these types of technology are that people have different motives for contributing to VGI and not everyone, specifically in the developing world, has access to geographic information resources. Having different motives will ultimately impact the precision of geographic information whether the goal is self-promotion or the desire to contribute to geographic knowledge. Additionally, less use of these technologies in the developing world results in less geographic information about these places.

Despite the negative effects of image and mapping technologies as well as VGI, there is great potential for these resources to contribute to our overall understanding of the world and increase awareness of natural disasters. Sites such as photosynth and Flickr allow users to view a location and gain insight into the environment without actually visiting the place. This could provide information about places people might want to visit and also act as a directional aid so people get a visual representation of their destination. In my photosynth example, having an image map of my living room or any part of my apartment would allow my friends and family to see my living environment without physically having to visit. Geographic technologies are also vital for military and commercial intelligence. Knowing the locations of different places allows for strategic combat planning and can also help commercially when considering places to advertise or set up stores. VGI can benefit geographic databases by providing an extensive network of individuals to cover more geographic locations and ultimately contribute an abundance of geographic information. Additionally, VGI is cheap and provides and inexpensive way to attain geographic information. Regarding natural disasters, geographic technologies can help predict and assess the impact of events in order to mitigate their overall impact to the environment and population in a region. Incorporating VGI into evaluating possible natural disasters could prove beneficial because often times geographic systems such as satellites and digital imagery are masked by local conditions and might miss the onset of a weather system. Relying on people who are familiar with the area to report any inconsistencies in local conditions could prove as a valuable tool for minimizing the impacts of natural disasters.

Geographic information technology continues to expand and provide more geographic information about different locations, objects, and events. While geographic information systems were initially restricted to proficient users, large geographic information sites such GoogleMaps, Wikimapia, Flickr, etc. have allowed for public use of geographic information systems and has also led to the establishment of VGI. Although it has some downfalls with regard to accuracy, VGI provides useful information primarily at a local level that is often overlooked by the media (Goodchild 2007). Overall, combining both geographic information attained by professionals as well as volunteers will allow for an increase in the information within geographic databases while maintaining a high level of accuracy and precision.

Lab 2- Corey Rovzar

Created Map

Original Map (from New York Times)
















Improving the Map

Although the above map may represent accurate information, there are better ways in which the data can be visually represented. While it may appear that McCain won the popular vote because he won the most states, it is important to acknowledge population densities within these states. Obama won states that had higher populations of people, and therefore won the popular vote. In order to visually display this, it would be best to use the Garner and Newman (2004) cartogram method which distorts county sizes to represent the relative population densities. Additionally, this map could also be improved by depicting areas where there were pretty even votes. This could be represented by the color purple and would allow a more realistic understanding of how close the race truly was. Again, using the Garner and Newman (2004) cartogram method would allow for this. Lastly, the map could reveal even greater detail by including the locations of donors and showing which counties and states gave the most money to both campaigns. Understanding which campaign had the most donors, where the donors lived, and how much the donors contributed could lead to further understanding of the importance of fundraising and its impact on the outcome of a presidential eleciton. Therefore, three major changes include using a cartogram to display voting patterns by county, employing purple to represent areas with mixed voting patterns, and lastly, displaying the locations of donors and their overall contributions. There are many different elements that can be displayed in a map. For this map, we can extend the knowledge portrayed further by including race and age distribution. Mapping such data would allow for the visualization of patterns between race or age and voting tendencies. These are just some examples representing the potential for electoral maps to display more than the obvious and help identify relationships between different factors.

Lab 1- Corey Rovzar

Map Exercise

Good Map

This map of vegetation types of Africa is good because it contains a title, legend, scale bar, and additional information that helps to visually display Africa vegetation data in a clear and understandable way. The title gives the reader an understanding of what data the map is visually displaying. In this example, "Natural Vegetation in Africa" suggests that the map is displaying data about different vegetation types in Africa. The legend acts as a guide to interpret different aspects of the map and in this case, provides a key of vegetation types that match the colors on the map. The scale bar provides insight into the scaling of the map and an understanding of the actual area of the region. The map projection is also given to provide information regarding the possible discrepancies in the shape, size, distance, or area of the projected region. Additionally, the cartographer has included textual information. By labeling the lines of latitude and longitude, Indian and Atlantic Oceans, the different seas, and nearby countries, the cartographer helps orientate the reader with the relative location of Africa. Countries within Africa are also labeled as well as major rivers which provides information regarding vegetation type within specific countries and allows for greater understanding of vegetation types in Africa. Overall, the map is clear and organized in a manner that is not overwhelming or confusing and uses color well in order to display vegetation types in Africa.

Bad Map

In contrast with the first map, this vegetation map of Africa is not very good because it lacks a title, legend, scale bar, and additional information that orientates the reader with the area. Without a title, the purpose of the map is unclear which prevents the reader from understanding the meaning of the map. Additionally, lacking a legend creates further confusion as it is unclear what each color of the map represents. Even if there was a title indicating that the map displays vegetation types in Africa, the distribution of vegetation types would still be unclear without knowledge of what type each color represents. Without a scale bar, the scale of the map is unknown and does not give any insight into the actual size the area. Lastly, without labeling nearby countries, bodies of water, and countries within Africa, it is more difficult for the reader to understand the relative location as well as basic geography of Africa which will further hinder their understanding of the data. Overall, this map is bad because it does not present the data clearly. A primary reason for creating a map is to present data in a way that is easier to understand then for example, a table. By excluding informative components, this map creates confusion and does not succeed in making the data on vegetation types in Africa easier for the reader to understand. Although the data may be accurate, the presentation of the map ultimately makes it more difficult to understand.


Census 2000 Exercise