58 thoughts on “OL75 (8:30 class): POST ACT III HERE (pdf’s of map layers)”

    1. Excellent maps, Fuaad. The age category is interesting because it shows that your neighborhood is low in “dependent age groups.” This suggests that theater for retirees OR for children is probably not appropriate. It will be interesting to see what you do with this data. I don’t understand the “Commute Time” data — if it is relevant to your project please explain during the presentation. Most of the people within a 5-block distance from the theater could probably walk.

    1. You have tapped into some data that will help you with your analysis of the neighborhood, however there are some issues with the way that data is displayed. First, the buffer zone should be 5 blocks radius. You have a 10-block radius. You need to make the circle much smaller in order to get a more precise reading of the neighborhood. Also, your choice of using circles rather than polygons is not always the best way to display the data. It’s difficult to see if there are any real differences between the area around the theater and the rest of Brooklyn. For instance, if the unemployment rate is generally less than 100 per block segment all around Brooklyn, then that data doesn’t really distinguish your neighborhood from all others. You need to find data that sets your neighborhood apart. Finally, it looks like you have two maps for unemployment. You only need one.

    1. Your buffer zone is much too large. It needs to be a 5-block radius. I think you have 20 blocks! There’s no way you can give an accurate analysis of the theater’s neighborhood with such a large dataset. Also, the data on Hispanic residents isn’t really helpful, since there’s no significant difference in the Hispanic population around your theater and much of the rest of the city. If your theater was in a high-density Hispanic neighborhood then the data would be relevant. But it isn’t. You need to find data that sets your neighborhood apart from the surrounding neighborhoods.

    1. Jaida,
      Please reduce your buffer zone by half. Your zone encompasses too many separate neighborhoods. Also, when displaying your layers, you need to click off the MapPluto data when showing age, ethnicity, income, etc. Essentially, you can only display one layer at a time if you are color-coding all polygons. The data you have selected should help you think about appropriate performance genres for your theater.

    1. A great collection of map layers, David. One thing about income and zoning: you might want to do a comparison of the two. You’ll see that the area that is heavily commercial is also higher in income. But that income is then measuring fewer residents than the other area around New World Stages (to the west), where the residential population is greater AND the income level is lower. The comparison tells you more about the data. You won’t be able to include all of these maps in your final presentation — so pick the most relevant maps.

    1. Excellent maps (although the screen shots were difficult to see — better to use “screen shot” in the future rather than taking a photo with your phone). The most interesting map is the “income by race” (the fourth), but I don’t understand the symbology. In other words, I don’t understand how the colors indicate race and income. Might be good to explain in presentation.

        1. You have found some useful data, but your maps need a little work. First, your income map symbology should follow a single color pattern — the highest income should also be a shade of green. Otherwise the viewer thinks its a different category. Second, the predominant race map doesn’t really tell us very much. You should look at what the predominant race is in NYC generally. It’s probably white also, which means there’s nothing about that area that is very different than the general population. What we don’t get in that map is the granularity of data. Grey only indicates predominant “white”, but we don’t know who else lives there. Finally, I’m not sure how understanding how people commute helps you understand theater-going in the area.

      1. These are excellent maps, Joshua. The colors (zones) are distinct. The viewer can easily read and understand the data. I look forward to your final recommendations to the theater and how this data informs your recommendations.

    1. These are excellent maps. You’ll need to zoom in closer to your site for the land use map since its much too much information to analyze on a large scale. Did you minimize your buffer to .5 miles radius? The education by age map is very interesting. I don’t understand the last map you showed.

    1. Nice maps, Yan. The age/Spanish speaking layer and the median age layer will inform your analysis for the theater (about what kinds of plays to present). However the other two are very generic. There’s nothing in income and race that makes this area stand out from the surrounding areas. Perhaps you need to look at other kinds of data or look at the data in a different way.

      1. Thank you, Marialina. The first link did not work. Your maps are excellent and should tell you a good deal about the areas directly to the east and west of your site. Are these your maps or Maria’s? You need to submit Act III separately.

          1. Marialina,
            The first two maps will be helpful in your analysis. The third map on predominant ethnicity doesn’t really tell us very much about the diversity in the area. Yes, white is predominant, but what other types of people live in the area? I’m not sure how the information helps you with a recommendation to the theater. Your final map about amenities is good, but you should edit out the amenities that have no relationship to theater-going. There’s too much information for the viewer to sort through. I hope this helps.

    1. As I’m sure you can see, your buffer zone is much too large — particularly for land use. There are no conclusions you can arrive at with this amount of data (and variation). Two of your maps basically are telling us “white and wealthy”. Most people would assume that this is true of such a pricey neighborhood in Manhattan. Is there any way you can create a map analysis that looks at the data with more detail? Right now it’s very homogeneous.

      1. Some of your maps don’t really tell the full story. Look carefully at the differences between the east and west side of the theater. There are actually more significant differences that the symbology you have chosen don’t show. For instance, the race and income layers don’t say very much at all. Nor does the education level. You need to zoom in more closely to the area around the theater and work with the data so we can see the variations and patterns more distinctly.

    1. I think the kinds of data you are looking at will help you with your final analysis. However, your buffer zone is much too large. The data is far too complex and there are way too many variables within that zone. Reduce to .5 radius so that you can observe some recognizable patterns. Right now I don’t understand why you have selected the data sets that you do. Also, I don’t understand the symbology for median income by race. The color scheme doesn’t make sense (I don’t see multiple races… what races are considered?).

        1. Gerline,
          There are a number of issues that you need to fix. First of all, you need to zoom into the area directly adjacent to the theater. The buffer zone should be .5 miles radius. We don’t need to know the income levels of people in Hoboken New Jersey! Second, your Pluto data is not color coded. Once it is, we need to see a legend that tells us what each color means. Your buffer zone should not be color coded — it is obscuring everything beneath it. Poverty level and education will help your analysis, but only if you look at the neighborhood directly around your theater.

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