Methods & Analysis
In order to understand the vulnerability to coastal and stormwater flooding in Hope and Ascendant properties I illustrate two major relations to understand properties' exposure to floods and one correlation to understand properties vulnerability. The first relation is between the number of properties located in the current and future NYC floodplains, the second relation is between properties' exposure to current and future coastal flooding and the influence of topographic elevation of Central and East Harlem. Finally I will correlate the number of 311 service calls relating to flooding (filtered by ...) with
I used the BBL instead of the building footprint because the Bf doesn't contain basements, there are too many assumptions to be made in relationship to future floodplain and I want to use the precautionary principle b
The first map displays the number of Hope and Ascendant properties mapped at the Bor that are in the current (2015) FEMA defined floodplain and the future floodplain as projected by the New York Panel on Climate Change (NYPCC, 2014) flood maps (20, 50, 80, 100 year floodplain).
Map 1 - Process flow:
- Retrieved property data from Hope (not geo-located and with not practical BBL numbers) and from Ascendant (already geo-located but with projection issues)
- Re-coded BBL numbers for both properties from scratch through padding numbers and concatenation
- Conversion Tool - Convert Exl into Table
- Table join between properties BBL and Mapluto BBLs for Manhattan but 6/100 properties did not join. I figured out that some addresses that I had initially split into two (e.g. 242-244 East 106 Street) should be kept as one because splitting them generates a new BBL code that of course does not exist. After I joined the address back I solved 5 of 6 missing BBL which were not joining.
- Selected all null (not joint attributes) and selected inverse to obtain only BBLs in CD 10 and 11, where properties are located. Exported data selection as shapefile.
- Create 1 field per floodplain (2015, 2020, 2050) set with a short integer and all values at 0 (NOT IN FLOOPLAIN)
- Selected by location - from the BBL with condition of intersecting with floodplain 2015, 2020, 2050, 2080. Each time I selected with field calculator BBLs that intersected with each floodplain and I assigned the intersection at 1 (IN FLOODPLAIN)
- Created another column where I aggregated all numbers to understand the BBLs that fall in the floodplain at none, one, two or all projections.
- Load the NEW York City DEM (1 foot) integer raster 3.3.gb apply Z factor at correct latitude (40)
- Table for each lot with average elevation (zonal statistics as table-mean)
- Import table in GIS make join btw table (min value elevation) with the table of the floods