These choropleths show two variables at the Census tract level: percent of families living below the poverty line and percent of population that identifies as non-White. Data was taken from the 2019 5 Year American Community Survey. Tracts with a coefficient of variation greater than 40 were crosshatched in the choropleth. This is to show what tracts have highly unreliable data.
Data for land surface temperature (LST) in Celsius, albedo, and normalized difference vegetation index (NDVI) were all calculated from Landsat 8 imagery via Google Earth Engine. The rasters were then processed in Python using RasterIO and sampled for each Census tract polygon. The median value of all the pixels in each polygon object was taken. These maps show the distribution of those values aggregated at the Census tract level.
This interactive web map helps you visualize the relationship between demographic variables and variables like LST, NDVI, and albedo.
In order to go ahead with morphological analysis of the built environment in Brooklyn, NY, you need some foundational “building block” data. The most fundamental is building footprints and the street network. From these, you are able to tessellate shapes around each building footprint bounded by the street network. From these tessellations and the street network, you are able to create blocks. These “building blocks” of building footprints, street network, tessellations, and blocks are what we calculate morphological characteristics off of.
Morphological metrics were calculated off of blocks, streets, tessellations, and buildings. There were up to 75 metrics, and spatially lagged metrics were also calculated. However, for simplicity’s sake, we show only 10 building metric variables in this interactive web map. The data itself was created by spatially joining the building polygons to Census tracts and then aggregating the metrics by the mean for each Census tract. Thus, this map shows the average value of each metric by Census tract. These metrics show larger patterns afoot in Brooklyn. There seems to be a split between the morphology of north Brooklyn and south Brooklyn.
|Variable||Pearson Correlation Coefficient|
|Building Perimeter Wall||-0.146870|
|Street Network Closeness||0.144760|
|Building Volume Facade Ratio||0.144430|
|Tessellation Circular Compactness||0.114319|
|Building Shared Walls Ratio||-0.103934|
|Building Perimeter Wall||-0.0003460|
|Street Network Closeness||51832.6334535|
|Building Volume Facade Ratio||0.8523624|
|Tessellation Circular Compactness||0.0272492|
|Building Shared Walls Ratio||0.2961113|
The adjusted R2 of the regression is 0.1895.