Lab 4

Maps from lab 4:

Exercise 1:


Exercise 2:


Exercise 3:


Exercise 4:


Exercise 5:


Experiences with GIS:
When Professor Shin, said that GIS had a steep learning curve he wasn't kidding! The first time I went through the tutorial, it took a long time to not just familiarize myself with the program but to also understand the tutorial itself. The second time I went through the tutorial, I already had an idea of what needed to be done so I was able to focus more on the computer program itself. The third and fourth times working through the tutorial consisted of me trying to figure out the different functions of ArcGIS without consulting the steps listed in the tutorial.

The steep learning curve, requires an individual to devote a considerable amount of time to become proficient with the software which limits accessibility to GIS. This in turn creates GIS "experts" whose services are in high demand due to the relatively few people who can use GIS. ESRI can also keep tighter regulations and quality control to provide professionals requiring spatial analysis with good quality data. The downside is that GIS may not innovate as fast as other mapping applications such as those found in neogeography, due to the sheer number of people using and improving on existing neogeographical tools.

One of the notable features of GIS is its ability to layer maps over each other and manipulate data embedded within those maps. This is very powerful in that using GIS, researchers can analyze relationships and associations between relevant entities and attributes. In the tutorial it was really helpful to see which parcels were located within the noise contour and the population density in relation to the contour. The fact that one is able to see these relationship rather than just reading tables will make it a lot easier to disseminate information.

One of the pitfalls of GIS is that like any other program the information that is outputted in only as good as the data that goes into it. GIS is a tool and it can be used correctly to provide new insights and answers to questions or it can mislead. Take for example, if the noise contour level was misrepresented somehow and is shown on GIS to be smaller than it truly is. If the city makes the decision to expand the airport based on faulty information, undesirable consequences may occur such as residents protesting the additional noise from overhead airplanes and the damaged credibility of city officials. Thus as a researcher or as a consumer of GIS derived information, it is of the utmost importance to make sure GIS data inputs are accurate.