In Part I, I took you through the data gathering and compilation required to rank Census tracts by the four features identified by Jane Jacobs as the foundation of a great neighborhood:

在第一部分中 ，我带您完成了根据简·雅各布斯(Jacobs Jacobs)所确定的作为大社区基础的四个要素对普查区域进行排名所需的数据收集和汇总：

• Density
  密度
• A mix of uses
  多种用途
• A mix of building ages, types and conditions
  混合建筑年龄，类型和条件
• A street network of short, connected blocks
  短而相连的街区的街道网络

Now that we have our data, we’re going to test it against some other metrics of urban quality of life and see if it is a strong predictor. I am going to test the Jane Jacobs Index and it’s component pieces against the following data:

现在我们有了数据，我们将针对城市生活质量的其他一些指标进行测试，看看它是否有力预测。 我将根据以下数据测试Jane Jacobs索引及其组成部分：

• Crime statistics from the King County Sheriff’s Department
  金县警长部门的犯罪统计
• Immunization rates at King County schools
  金县学校的免疫率
• Housing affordability
  住房负担能力
• Commute mode share
  通勤模式分享

I’m going to focus on King County in this post because my Ada County dataset, while interesting, turned out to be too small to provide meaningful results.

在这篇文章中，我将重点介绍King County，因为我的Ada County数据集虽然很有趣，但由于它太小而无法提供有意义的结果。

犯罪 (Crime)

I was very curious to see the results of this one. A lot of Death and Life is focused on the right urban design to naturally prevent crime. Jacobs’ recommendations made a lot of sense in the context of the 1950s as it focused on making the streets an interesting place to be and to simply watch from apartment windows. City streets are cool and all, but more interesting than Netflix?

我很好奇看到这一结果。 许多《 生死攸关》专注于正确的城市设计，以自然地预防犯罪。 雅各布斯(Jacobs)的建议在1950年代的背景下非常有意义，因为它的重点是使街道成为有趣的地方，并且可以从公寓的窗户直接观看。 城市街道很酷，但是比Netflix还有趣吗？

I’m going to compare the JJI to the Seattle Police Department’s publicly available crime database. I took this dataset, performed a spatial join with a Census tract shapefile, counted the incidents within each tract, then normalized it by area to get a per mile crime density. Plotting this against the Jane Jacobs Index and it’s components yields the following:

我将把JJI与西雅图警察局的公开犯罪数据库进行比较 。 我获取了此数据集，使用人口普查区域图形文件进行了空间连接，计算了每个区域内的事件，然后按区域对其进行归一化以得到每英里犯罪密度。 根据简·雅各布斯指数及其成分来绘制，得出以下结果：

I’m going to avoid over-statistics-ing my analysis in this post and just look at the pictures. Remember that the components of the JJI are rankings of census tracts based on their scores in the four qualities identified above, and the JJI is an average of those four rankings, so a low score is the Jacobs-y-est. Under the DaLoGAC hypothesis, we would see the lowest crime density in the tracts with the lowest JJI, and the dots moving upward from left to right. Interestingly, we see the opposite pattern emerging in all except the measure of housing age homogeneity. My theory on why: homelessness is the primary driver of crime in Seattle. Places that have been allowed to organically evolve and replace older, smaller buildings with newer, denser places are better able to naturally meet the housing demand, thus enabling people to meet their needs without resorting to criminal activity.

在这篇文章中，我将避免过度统计-我的分析只是看图片。 请记住，JJI的组成部分是根据人口普查区域在上述四种质量中的得分来进行排名，而JJI是这四个排名的平均值，因此，Jacobs-y-est得分较低。 在DaLoGAC假设下，我们将看到JJI最低的区域中犯罪密度最低，并且点从左到右向上移动。 有趣的是，除了住房年龄同质性的衡量标准外，我们看到了相反的格局。 关于以下原因的我的理论：无家可归是西雅图犯罪的主要驱动因素。 被允许有机发展的地方，可以用较新的，更密集的地方代替较旧的较小建筑物，从而更自然地满足住房需求，从而使人们能够满足自己的需求而无需诉诸犯罪活动。

免疫率 (Immunization Rates)

This one was more out of curiosity and because the data was there than any real hunt for urban design solutions. I am curious because trust in governments, scientific research, and similar institutions has been shown to correlate with immunization rates, and I wanted to see if there was a correlation between this trust and urban design. King County publishes immunization coverage rates by school, so I again joined that to census tract, then took an average. Here are the results:

这更多是出于好奇，因为数据在那里，而不是真正寻找城市设计解决方案的机会。 我很好奇，因为对政府，科学研究和类似机构的信任已显示与免疫接种率相关 ，并且我想看看这种信任与城市设计之间是否存在相关性。 金县按学校发布免疫覆盖率 ，因此我再次将其纳入普查范围，然后取平均值。 结果如下：

No correlation. Crazy theory set aside for now…

没有相关性。 疯狂的理论暂时搁置了……

住房负担能力 (Housing Affordability)

For this, I took the Census Bureau’s data on median household income and median housing cost to get a percent of income spent on housing for each census tract.

为此，我采用了人口普查局关于家庭收入中位数和住房成本中位数的数据，以获取每个普查区在住房上花费的收入的百分比。

Some correlation, but not much. Seattle is pretty uniformly expensive, so it might not be the best place for this particular research. I suspect some Midwestern cities like Chicago where parts of the city have very high housing costs while other neighborhoods are still cheaper would yield different results.

一些相关性，但不多。 西雅图非常昂贵，因此可能不是进行这项特定研究的最佳地点。 我怀疑像芝加哥这样的中西部城市，其中部分城市的住房成本很高，而其他街区仍然较便宜，它们会产生不同的结果。

通勤模式分享 (Commute Mode Share)

Getting people out of their cars has been a challenge for planners for as long as there have been cars. The results of this one are cool, so I’m going to take a deeper dive into them. The Census surveys how people are getting to work in the following high-level categories:

只要有汽车，就将人们带出汽车对计划者一直是一个挑战。 这个结果很酷，因此我将更深入地研究它们。 人口普查调查人们如何在以下高级类别中工作：

• Drove Alone
  独自开车
• Carpooled
  拼车
• Public Transit
  公共交通
• Taxicab
  出租车
• Motorcycle
  摩托车
• Bicycle
  自行车
• Walking
  步行
• Other
  其他

I’m going to compare these percent of respondents who use the various modes against the JJI, as well as the pre-ranking versions of the components. First off, here’s the population density per square mile:

我将比较使用JJI的各种模式以及这些组件的预排名版本的受访者百分比。 首先，这是每平方英里的人口密度：

A lot of stuff starts happening when you get past 10,000 people per square mile, specifically people stop driving and start walking and using transit. This really isn’t new information, but it’s still interesting to see how strong that relationship is.

每平方英里超过10,000人时，就会发生很多事情，特别是人们停止开车，开始走路和乘公交。 这确实不是新信息，但是看到这种关系有多牢固仍然很有趣。

Next, the relationship between age of construction homogeneity and transportation:

接下来，建筑同质化年龄与运输之间的关系：

I’m not surprised that this one is scattershot.

对于这一点，我并不感到惊讶。

Next, street network design:

接下来，街道网络设计：

There’s a lot of hockey-stick going on here. Remember that the street score is the average length of each block divided by the average number of streets at each intersection, so a low score is more Jacobs-y. Clearly people in neighborhoods with a score under 50 are much more likely to use active transportation methods. This relationship is especially strong with walking and biking.

这里有很多曲棍球棒。 请记住，街道得分是每个街区的平均长度除以每个路口的平均街道数量，因此得分较低的雅各布斯(Jacobs-y)更大。 显然，得分低于50的社区居民更有可能使用主动交通方式。 这种关系在步行和骑自行车时尤其牢固。

Next, the percent of daily needs within one kilometer:

接下来，在一公里之内的每日需求百分比：

If your daily needs can be met by walking, you tend to walk more. Shocking!

如果步行可以满足您的日常需求，那么您倾向于走更多的路。 令人震惊！

Finally, putting them all together, the Jane Jacobs Index:

最后，将它们放在一起，简·雅各布斯索引：

The strong correlation continues here between Jacobs-y places and active transportation.

Jacobs-y场所与活跃交通之间的这种强相关性仍在继续。

结论 (Conclusion)

• If you want less car dependence, build dense, mixed use neighborhoods with a short interconnected street network.
  如果您希望减少对汽车的依赖性，则可以使用短而互连的街道网络来建立密集的混合用途社区。
• If you want lower crime, support incremental development.
  如果您想减少犯罪，请支持渐进式发展。
• Listening to Jane Jacobs is unlikely to have negative impacts on your community.
  倾听简·雅各布斯的声音不太可能对您的社区产生负面影响。