In [2]:

    

import json, shapely, fiona, os
import seaborn as sns
import pandas as pd
import geopandas as gpd
import networkx as nx
import matplotlib.pyplot as plt

%matplotlib inline


    

In [4]:

    

buildings = gpd.read_file('data/Building_Footprints.shp')
print("Found {0} buildings".format(len(buildings)))
buildings.head(1);


    

    




Found 45728 buildings

In [6]:

    

flood_extent = gpd.read_file('data/Flood2013Extents.shp')
flood_extent.head()


    

    
Out[6]:







  

    

      

      
OBJECTID
      
CREEK
      
MAPPING_ST
      
SHAPE_AREA
      
SHAPE_LEN
      
geometry
    
  
  

    

      
0
      
1
      
Gregory Canyon Creek
      
Complete
      
2.105969e+06
      
33078.761777
      
POLYGON ((3060082.675777227 1246067.801150128,...
    
    

      
1
      
2
      
Sunshine Canyon Creek
      
Complete
      
1.128345e+06
      
25405.394518
      
POLYGON ((3058244.465214819 1249329.027567297,...
    
    

      
2
      
3
      
Boulder Slough
      
Complete
      
1.152517e+06
      
24891.760136
      
(POLYGON ((3064533.865365639 1249084.573987961...
    
    

      
3
      
4
      
Goose Creek
      
Complete
      
2.479010e+06
      
49036.323199
      
(POLYGON ((3065561.063770562 1253580.064996973...
    
    

      
4
      
5
      
Elmers Twomile Creek
      
Complete
      
1.441207e+05
      
4564.338099
      
(POLYGON ((3067065.181169137 1254926.188617051...
    
  

In [10]:

    

flood_extent = flood_extent.to_crs(buildings.crs)


    

In [12]:

    

flooded_buildings = gpd.sjoin(buildings, flood_extent)
flooded_buildings.head()


    

In [16]:

    

with open('/home/cc/www/flooded_buildings.geojson','w') as outFile:
    outFile.write(flooded_buildings.to_json())
print("Now open http://townsendjennings.com/geo/?src=http://yetilabs.science/flooded_buildings.geojson")


    

    




Now open http://townsendjennings.com/geo/?src=http://yetilabs.science/flooded_buildings.geojson

In [ ]: