Geography Survey

Introduction:

Our survey was done in the first district in the PLVI (Peak Land Value Intersection) of Vienna. In the PLVI there is a high number of shops and many pedestrians. The main strength of the first district are the historical buildings which attract many tourists. This way the tourists spend a lot of money in the PLVI. The PLVI is the center of the CBD (Central Business District) Our task was to examine the idea that shopping quality changes as we move away from the PLVI of a city.

Aims of the Survey:

The survey was done to state whether the following two statements are true or not:

- Shopping quality declines with distance from the PLVI of Vienna

- The Quality of shops is directly related to the density of pedestrians (Most people shop where the quality of shops is highest).

I think that the number will decrease (total score) as we get further away from the PLVI. This is because the land value will also decrease as we get further away. When this happens we get smaller shops and owner don't have enough money to build or rent shops around that area that are as big as in the PLVI. What I think happens is that the number of pedestrians influences the total score. Therefore the richer and financially stronger owners/companies build their shops in the PLVI, while other poorer companies/owners build their shops outside.

Method:

In groups we had to make a analysis of 4 locations. A average number of pedestrians was recorded per minute. Then the Location of which one in is rated by a scale of 1-5 where 5 is the best. They were rated on the cleanness, safety (if there were enough traffic lights for the pedestrians) , appearance, vacant buildings were added up to give a total out of 20 under "street appearance". Then the land use, Type of shops, quality of goods, shop owner ship were rated (each with a maximum of 5 points) and were added up giving a total out of 20 under "Shopping quality". Then adding both scores up we get the total score out of 40. For each section (street appearance and Shopping quality) we had to add a comment.

Interpretation:

At first you see on the graph that the total is decreasing, but there is a certain point of each group where the total results start raising.

The Scatter graph show that there is a good connection between the total score and the pedestrians. Even though there is a good connection between the total score and the pedestrians there are a few points were the total score is high but the number of pedestrians is low.

In the Isobar we see that the area does decrease as we go further away from the PLVI . In the center we see that the total scores are between 35-37, but as we leave the PLVI we see that the total scores come down to 9-20. What i also noticed with the results is that there are more pedestrians on the main street that on small roads. Here the total score is not high compared to the PLVI, but it is reasonably higher that its surroundings. This explains the results for group 9's total score. The reason why there score decreases and then at location 4 increases rapidly is because they come on to a main street which raises the score.

Conclusion:

The thesis was not correct because the quality does not necessarily decrease as we go further away from the PLVI. What I noticed is that at first it does decrease, but then, as we reach a main road (or in this case the Ring) the total score (and therefore the quality) of the shops become much higher. The reason why the land use is so high around the ring and the main roads is because many people pass that area daily. They have to pass the area so that they can get to work, public buildings, or because they have to get the public transport. The second thesis was true though, the quality of shops is directly related to the density of pedestrians. This can be proven because on the Isobar graph we see the statistics which show that wherever there are more pedestrians, the land use and land value increases.

In the scatter graph you see that the total score decreases rapidly. But then at a certain point all the total scores for each group rise. The scatter graph is very similar.

I did the Bar chart because it show the similarities between the number of pedestrians over the total score. One can see that they are very similar and relate to each other. This also proves the second thesis to be true.

Analysis: