In [2]:

    

import geopandas as gpd
import pandas as pd
import shapely
from shapely.geometry import Point, MultiPoint
from shapely.ops import nearest_points
import matplotlib.pyplot as plt
import numpy as np
import fiona
import mplleaflet
fiona.drvsupport.supported_drivers['kml'] = 'rw' # enable KML support which is disabled by default
fiona.drvsupport.supported_drivers['KML'] = 'rw' # enable KML support which is disabled by default
plt.style.use('bmh')
%pylab inline
pylab.rcParams['figure.figsize']=(20.0,20.0)


    

    




Populating the interactive namespace from numpy and matplotlib

In [3]:

    

villages_shp=gpd.read_file('./Village/VILLAGE_MOI_1070312.shp')
villages_shp.head()


    

    
Out[3]:







  

    

      

      
VILLCODE
      
COUNTYNAME
      
TOWNNAME
      
VILLNAME
      
VILLENG
      
COUNTYID
      
COUNTYCODE
      
TOWNID
      
TOWNCODE
      
NOTE
      
geometry
    
  
  

    

      
0
      
10013030S01
      
屏東縣
      
東港鎮
      
None
      
None
      
T
      
10013
      
T03
      
10013030
      
未編定村里
      
POLYGON ((120.4805919500001 22.42686214900004,...
    
    

      
1
      
64000130006
      
高雄市
      
林園區
      
中門里
      
Zhongmen Vil.
      
E
      
64000
      
E13
      
64000130
      
None
      
POLYGON ((120.3677206890001 22.49564452100009,...
    
    

      
2
      
10018010054
      
新竹市
      
東區
      
關新里
      
Guanxin  Vil.
      
O
      
10018
      
O01
      
10018010
      
None
      
POLYGON ((121.0216527890001 24.78572117700008,...
    
    

      
3
      
64000130008
      
高雄市
      
林園區
      
港埔里
      
Gangpu Vil.
      
E
      
64000
      
E13
      
64000130
      
None
      
POLYGON ((120.3732513370001 22.49123186400004,...
    
    

      
4
      
64000100010
      
高雄市
      
旗津區
      
上竹里
      
Shangzhu Vil.
      
E
      
64000
      
E10
      
64000100
      
None
      
POLYGON ((120.2897623490001 22.57316931000008,...
    
  

In [4]:

    

villages_shp.plot(cmap='Paired')


    

    
Out[4]:





<matplotlib.axes._subplots.AxesSubplot at 0x206d9fbd438>






    

In [5]:

    

tainan_villages_shp=villages_shp[villages_shp['COUNTYNAME']=='臺南市'].copy(deep=True)
tainan_villages_shp=tainan_villages_shp[['COUNTYNAME','TOWNNAME','VILLNAME','geometry']]
tainan_villages_shp.head()


    

    
Out[5]:







  

    

      

      
COUNTYNAME
      
TOWNNAME
      
VILLNAME
      
geometry
    
  
  

    

      
780
      
臺南市
      
歸仁區
      
六甲里
      
POLYGON ((120.2724993920001 22.95868469300007,...
    
    

      
781
      
臺南市
      
歸仁區
      
崙頂里
      
POLYGON ((120.2990937200001 22.96324021500004,...
    
    

      
782
      
臺南市
      
新市區
      
大社里
      
POLYGON ((120.3223493930001 23.09963833500007,...
    
    

      
783
      
臺南市
      
安南區
      
青草里
      
POLYGON ((120.117587175 23.08386983000008, 120...
    
    

      
784
      
臺南市
      
七股區
      
溪南里
      
POLYGON ((120.121032655 23.13549890300004, 120...
    
  

In [6]:

    

tainan_villages_shp.plot(column='VILLNAME', cmap='tab10_r',edgecolor='k')


    

    
Out[6]:





<matplotlib.axes._subplots.AxesSubplot at 0x206da008358>






    

In [7]:

    

rivers_shp=gpd.read_file("./Village/BASIN.kml")
rivers_shp=rivers_shp[['Name','geometry']]
rivers_shp.head()


    

    
Out[7]:







  

    

      

      
Name
      
geometry
    
  
  

    

      
0
      
老梅j溪
      
(POLYGON Z ((121.5102622960122 25.290888400759...
    
    

      
1
      
阿里磅溪
      
(POLYGON Z ((121.5521534083207 25.292825368854...
    
    

      
2
      
大坑溪
      
(POLYGON Z ((121.4842994293724 25.270784983027...
    
    

      
3
      
八連溪
      
(POLYGON Z ((121.4780624807429 25.262554960169...
    
    

      
4
      
北勢坑溪
      
(POLYGON Z ((121.4470109020607 25.239690803387...
    
  

In [8]:

    

rivers_shp.plot(column='Name', cmap=plt.cm.Blues)


    

    
Out[8]:





<matplotlib.axes._subplots.AxesSubplot at 0x206da0ccbe0>






    

In [9]:

    

river1_shp=rivers_shp[rivers_shp['Name']=='二仁溪']
river2_shp=rivers_shp[rivers_shp['Name']=='鹽水溪']
river3_shp=rivers_shp[rivers_shp['Name']=='曾文溪']
river4_shp=rivers_shp[rivers_shp['Name']=='急水溪']
river5_shp=rivers_shp[rivers_shp['Name']=='八掌溪']


    

In [10]:

    

# Convert POLYGON Z to POLYGON 
# Reference:
# https://www.google.com/maps/d/u/0/viewer?mid=1-DzOSjuIOVXc9sexecwf0Q2opTXgobuL&ll=22.918950999999996%2C120.18461500000001&z=10
observ_shp=gpd.read_file("./Village/observactory.kml")
observ_shp['geometry']=observ_shp['geometry'].centroid


    

In [11]:

    

observ_shp['Description'][0:10]='二仁溪'
observ_shp['Description'][10:16]='鹽水溪'
observ_shp['Description'][16:27]='曾文溪'
observ_shp['Description'][27:34]='急水溪'
observ_shp['Description'][34:40]='八掌溪'
observ_shp.head()


    

    
Out[11]:







  

    

      

      
Name
      
Description
      
geometry
    
  
  

    

      
0
      
南萣橋
      
二仁溪
      
POINT (120.184615 22.918951)
    
    

      
1
      
永寧橋
      
二仁溪
      
POINT (120.19397 22.925631)
    
    

      
2
      
五空橋
      
二仁溪
      
POINT (120.221618 22.927706)
    
    

      
3
      
二層行橋
      
二仁溪
      
POINT (120.225878 22.915551)
    
    

      
4
      
石安橋
      
二仁溪
      
POINT (120.297117 22.901202)
    
  

In [12]:

    

river1_villages_shp = tainan_villages_shp[tainan_villages_shp.intersects(river1_shp.unary_union)==True]
river1_villages_shp_clip = river1_villages_shp.copy()
river1_villages_shp_clip['geometry'] = river1_villages_shp_clip.intersection(river1_shp.unary_union)
river1_villages_shp=river1_villages_shp[(river1_villages_shp_clip['geometry'].area /river1_villages_shp['geometry'].area) > 0.5]

river2_villages_shp = tainan_villages_shp[tainan_villages_shp.intersects(river2_shp.unary_union)==True]
river2_villages_shp_clip = river2_villages_shp.copy()
river2_villages_shp_clip['geometry'] = river2_villages_shp_clip.intersection(river2_shp.unary_union)
river2_villages_shp=river2_villages_shp[(river2_villages_shp_clip['geometry'].area /river2_villages_shp['geometry'].area) > 0.5]

river3_villages_shp = tainan_villages_shp[tainan_villages_shp.intersects(river3_shp.unary_union)==True]
river3_villages_shp_clip = river3_villages_shp.copy()
river3_villages_shp_clip['geometry'] = river3_villages_shp_clip.intersection(river3_shp.unary_union)
river3_villages_shp=river3_villages_shp[(river3_villages_shp_clip['geometry'].area /river3_villages_shp['geometry'].area) > 0.5]

river4_villages_shp = tainan_villages_shp[tainan_villages_shp.intersects(river4_shp.unary_union)==True]
river4_villages_shp_clip = river4_villages_shp.copy()
river4_villages_shp_clip['geometry'] = river4_villages_shp_clip.intersection(river4_shp.unary_union)
river4_villages_shp=river4_villages_shp[(river4_villages_shp_clip['geometry'].area /river4_villages_shp['geometry'].area) > 0.5]

river5_villages_shp = tainan_villages_shp[tainan_villages_shp.intersects(river5_shp.unary_union)==True]
river5_villages_shp_clip = river5_villages_shp.copy()
river5_villages_shp_clip['geometry'] = river5_villages_shp_clip.intersection(river5_shp.unary_union)
river5_villages_shp=river5_villages_shp[(river5_villages_shp_clip['geometry'].area /river5_villages_shp['geometry'].area) > 0.5]


    

In [13]:

    

#ax=tainan_villages_shp.plot(column='VILLNAME', cmap='tab10_r',edgecolor='k',linewidth=1)
ax=tainan_villages_shp.plot(color='white',edgecolor='k',linewidth=1)


river1_villages_shp.plot(ax=ax, facecolor='red',edgecolor='k',linewidth=1)
river2_villages_shp.plot(ax=ax, facecolor='blue',edgecolor='k',linewidth=1)
river3_villages_shp.plot(ax=ax, facecolor='green',edgecolor='k',linewidth=1)
river4_villages_shp.plot(ax=ax, facecolor='purple',edgecolor='k',linewidth=1)
river5_villages_shp.plot(ax=ax, facecolor='orange',edgecolor='k',linewidth=1)

river1_shp.plot(ax=ax,facecolor='fuchsia',alpha=0.5,edgecolor='red',linewidth=1)
river2_shp.plot(ax=ax,facecolor='lightskyblue',alpha=0.5,edgecolor='blue',linewidth=1)
river3_shp.plot(ax=ax,facecolor='palegreen',alpha=0.5,edgecolor='green',linewidth=1)
river4_shp.plot(ax=ax,facecolor='darkmagenta',alpha=0.5,edgecolor='purple',linewidth=1)
river5_shp.plot(ax=ax,facecolor='yellow',alpha=0.5,edgecolor='orange',linewidth=1)

observ_shp.plot(ax=ax,column='Description',cmap='Paired',marker='D',markersize=100,categorical=True)
tainan_villages_shp.centroid.plot(ax=ax,color='black',markersize=8)


    

    
Out[13]:





<matplotlib.axes._subplots.AxesSubplot at 0x206da1e5710>






    

In [14]:

    

river1_villages_shp['river']='二仁溪'
river2_villages_shp['river']='鹽水溪'
river3_villages_shp['river']='曾文溪'
river4_villages_shp['river']='急水溪'
river5_villages_shp['river']='八掌溪'
river1_villages_shp.head()


    

    
Out[14]:







  

    

      

      
COUNTYNAME
      
TOWNNAME
      
VILLNAME
      
geometry
      
river
    
  
  

    

      
780
      
臺南市
      
歸仁區
      
六甲里
      
POLYGON ((120.2724993920001 22.95868469300007,...
      
二仁溪
    
    

      
781
      
臺南市
      
歸仁區
      
崙頂里
      
POLYGON ((120.2990937200001 22.96324021500004,...
      
二仁溪
    
    

      
811
      
臺南市
      
仁德區
      
保安里
      
POLYGON ((120.2304346320001 22.93543616500006,...
      
二仁溪
    
    

      
812
      
臺南市
      
仁德區
      
三甲里
      
POLYGON ((120.234425102 22.94004600600005, 120...
      
二仁溪
    
    

      
813
      
臺南市
      
仁德區
      
田厝里
      
POLYGON ((120.2375596850001 22.94529373500006,...
      
二仁溪
    
  

In [15]:

    

def nearest(row, geom_union, df1, df2, geom1_col='geometry', geom2_col='geometry', src_column='Name'):
    """Find the nearest point and return the corresponding value from specified column."""
    # Find the geometry that is closest
    nearest = df2[geom2_col] == nearest_points(row[geom1_col], geom_union)[1]
    # Get the corresponding value from df2 (matching is based on the geometry)
    value = df2[nearest][src_column].get_values()[0]
    return value


    

In [16]:

    

observ_river1_shp=observ_shp[observ_shp['Description']=='二仁溪']
observ_river2_shp=observ_shp[observ_shp['Description']=='鹽水溪']
observ_river3_shp=observ_shp[observ_shp['Description']=='曾文溪']
observ_river4_shp=observ_shp[observ_shp['Description']=='急水溪']
observ_river5_shp=observ_shp[observ_shp['Description']=='八掌溪']

river1_villages_shp['centroid'] = river1_villages_shp.centroid
river1_villages_shp['nearest_observ'] = river1_villages_shp.apply(nearest, geom_union=observ_river1_shp.unary_union, df1=river1_villages_shp,
                                                                     df2=observ_river1_shp, geom1_col='centroid', axis=1)
river2_villages_shp['centroid'] = river2_villages_shp.centroid
river2_villages_shp['nearest_observ'] = river2_villages_shp.apply(nearest, geom_union=observ_river2_shp.unary_union, df1=river2_villages_shp,
                                                                     df2=observ_river2_shp, geom1_col='centroid', axis=1)
river3_villages_shp['centroid'] = river3_villages_shp.centroid
river3_villages_shp['nearest_observ'] = river3_villages_shp.apply(nearest, geom_union=observ_river3_shp.unary_union, df1=river3_villages_shp,
                                                                     df2=observ_river3_shp, geom1_col='centroid', axis=1)
river4_villages_shp['centroid'] = river4_villages_shp.centroid
river4_villages_shp['nearest_observ'] = river4_villages_shp.apply(nearest, geom_union=observ_river4_shp.unary_union, df1=river4_villages_shp,
                                                                     df2=observ_river4_shp, geom1_col='centroid', axis=1)
river5_villages_shp['centroid'] = river5_villages_shp.centroid
river5_villages_shp['nearest_observ'] = river5_villages_shp.apply(nearest, geom_union=observ_river5_shp.unary_union, df1=river5_villages_shp,
                                                                     df2=observ_river5_shp, geom1_col='centroid', axis=1)

river1_villages_shp.head()


    

    
Out[16]:







  

    

      

      
COUNTYNAME
      
TOWNNAME
      
VILLNAME
      
geometry
      
river
      
centroid
      
nearest_observ
    
  
  

    

      
780
      
臺南市
      
歸仁區
      
六甲里
      
POLYGON ((120.2724993920001 22.95868469300007,...
      
二仁溪
      
POINT (120.2791544829967 22.94752036333348)
      
石安橋
    
    

      
781
      
臺南市
      
歸仁區
      
崙頂里
      
POLYGON ((120.2990937200001 22.96324021500004,...
      
二仁溪
      
POINT (120.2940430726397 22.95119138482716)
      
石安橋
    
    

      
811
      
臺南市
      
仁德區
      
保安里
      
POLYGON ((120.2304346320001 22.93543616500006,...
      
二仁溪
      
POINT (120.238227967483 22.92335521973537)
      
二層行橋
    
    

      
812
      
臺南市
      
仁德區
      
三甲里
      
POLYGON ((120.234425102 22.94004600600005, 120...
      
二仁溪
      
POINT (120.2391489559594 22.93128623474225)
      
五空橋
    
    

      
813
      
臺南市
      
仁德區
      
田厝里
      
POLYGON ((120.2375596850001 22.94529373500006,...
      
二仁溪
      
POINT (120.2418300572598 22.93867944083052)
      
五空橋
    
  

In [17]:

    

river_villages_shp=pd.concat([river1_villages_shp,river2_villages_shp,river3_villages_shp,river4_villages_shp,river5_villages_shp])
river_villages_shp.head()


    

    
Out[17]:







  

    

      

      
COUNTYNAME
      
TOWNNAME
      
VILLNAME
      
geometry
      
river
      
centroid
      
nearest_observ
    
  
  

    

      
780
      
臺南市
      
歸仁區
      
六甲里
      
POLYGON ((120.2724993920001 22.95868469300007,...
      
二仁溪
      
POINT (120.2791544829967 22.94752036333348)
      
石安橋
    
    

      
781
      
臺南市
      
歸仁區
      
崙頂里
      
POLYGON ((120.2990937200001 22.96324021500004,...
      
二仁溪
      
POINT (120.2940430726397 22.95119138482716)
      
石安橋
    
    

      
811
      
臺南市
      
仁德區
      
保安里
      
POLYGON ((120.2304346320001 22.93543616500006,...
      
二仁溪
      
POINT (120.238227967483 22.92335521973537)
      
二層行橋
    
    

      
812
      
臺南市
      
仁德區
      
三甲里
      
POLYGON ((120.234425102 22.94004600600005, 120...
      
二仁溪
      
POINT (120.2391489559594 22.93128623474225)
      
五空橋
    
    

      
813
      
臺南市
      
仁德區
      
田厝里
      
POLYGON ((120.2375596850001 22.94529373500006,...
      
二仁溪
      
POINT (120.2418300572598 22.93867944083052)
      
五空橋
    
  

In [18]:

    

ax=tainan_villages_shp.plot(color='white',edgecolor='k',linewidth=1)

river_villages_shp.plot(ax=ax, column='nearest_observ', cmap='tab10_r',edgecolor='k',linewidth=1,categorical=True)

river1_shp.plot(ax=ax,facecolor=(0.9804, 0, 0.9804, 0.15),edgecolor='red',linewidth=1.5)
river2_shp.plot(ax=ax,facecolor=(0.5294, 0.8078, 0.9803, 0.15),edgecolor='blue',linewidth=1.5)
river3_shp.plot(ax=ax,facecolor=(0.5960, 0.9843, 0.5960, 0.15),edgecolor='green',linewidth=1.5)
river4_shp.plot(ax=ax,facecolor=(0.5450, 0, 0.5450, 0.15),edgecolor='purple',linewidth=1.5)
river5_shp.plot(ax=ax,facecolor=(1, 1, 0, 0.15),edgecolor='orange',linewidth=1.5)

observ_shp.plot(ax=ax, column='Name', cmap='tab10_r', edgecolor='k',linewidth=2.5, marker='D',markersize=100)

tainan_villages_shp.centroid.plot(ax=ax,color='black',markersize=2)

#tainan_villages_shp['coords'] = tainan_villages_shp['geometry'].apply(lambda x: x.representative_point().coords[:])
#tainan_villages_shp['coords'] = [coords[0] for coords in tainan_villages_shp['coords']]
#for idx, row in tainan_villages_shp.iterrows():
#    plt.annotate(s=row['VILLNAME'], xy=row['coords'],
#                 horizontalalignment='center')


    

    
Out[18]:





<matplotlib.axes._subplots.AxesSubplot at 0x206db5e9a20>






    

In [132]:

    

river_villages_shp.head()


    

    
Out[132]:







  

    

      

      
COUNTYNAME
      
TOWNNAME
      
VILLNAME
      
geometry
      
river
      
centroid
      
nearest_observ
    
  
  

    

      
780
      
臺南市
      
歸仁區
      
六甲里
      
POLYGON ((120.2724993920001 22.95868469300007,...
      
二仁溪
      
POINT (120.2791544829967 22.94752036333348)
      
石安橋
    
    

      
781
      
臺南市
      
歸仁區
      
崙頂里
      
POLYGON ((120.2990937200001 22.96324021500004,...
      
二仁溪
      
POINT (120.2940430726397 22.95119138482716)
      
石安橋
    
    

      
811
      
臺南市
      
仁德區
      
保安里
      
POLYGON ((120.2304346320001 22.93543616500006,...
      
二仁溪
      
POINT (120.238227967483 22.92335521973537)
      
二層行橋
    
    

      
812
      
臺南市
      
仁德區
      
三甲里
      
POLYGON ((120.234425102 22.94004600600005, 120...
      
二仁溪
      
POINT (120.2391489559594 22.93128623474225)
      
五空橋
    
    

      
813
      
臺南市
      
仁德區
      
田厝里
      
POLYGON ((120.2375596850001 22.94529373500006,...
      
二仁溪
      
POINT (120.2418300572598 22.93867944083052)
      
五空橋
    
  

In [133]:

    

river_villages_shp=river_villages_shp.drop(['COUNTYNAME'],axis=1)


    

In [134]:

    

river_villages_shp.columns=['town', 'village', 'geometry', 'river', 'centroid','nearest_observ']
river_villages_shp=river_villages_shp.groupby(['river','nearest_observ','town','village']).sum()


    

In [135]:

    

river_villages_shp


    

    
Out[135]:







  

    

      

      

      

      

      
geometry
      
centroid
    
    

      
river
      
nearest_observ
      
town
      
village
      

      

    
  
  

    

      
二仁溪
      
二層橋
      
龍崎區
      
石[曹]里
      
POLYGON ((120.40688116 22.97246177100004, 120....
      
POINT (120.4083251893035 22.95697010222046)
    
    

      
龍船里
      
POLYGON ((120.432797818 22.96004082800005, 120...
      
POINT (120.4191799771744 22.9471814583167)
    
    

      
二層行橋
      
仁德區
      
中洲里
      
POLYGON ((120.2666803090001 22.92634352300007,...
      
POINT (120.2512606007372 22.90946381222238)
    
    

      
二行里
      
POLYGON ((120.221606595 22.92721279000006, 120...
      
POINT (120.2212941459547 22.91964009658454)
    
    

      
保安里
      
POLYGON ((120.2304346320001 22.93543616500006,...
      
POINT (120.238227967483 22.92335521973537)
    
    

      
五空橋
      
仁德區
      
三甲里
      
POLYGON ((120.234425102 22.94004600600005, 120...
      
POINT (120.2391489559594 22.93128623474225)
    
    

      
上崙里
      
POLYGON ((120.2700718030001 22.94836669000006,...
      
POINT (120.2590635469002 22.93643630748741)
    
    

      
仁和里
      
POLYGON ((120.2234028040001 22.96181586100005,...
      
POINT (120.2239772200365 22.95943301390753)
    
    

      
仁愛里
      
POLYGON ((120.221576883 22.96203628200004, 120...
      
POINT (120.2196890431181 22.95188765342725)
    
    

      
後壁里
      
POLYGON ((120.2383312410001 22.96024872400005,...
      
POINT (120.2466239169225 22.94969513021107)
    
    

      
成功里
      
POLYGON ((120.2250866490001 22.96158763700004,...
      
POINT (120.2215704354477 22.94237293228882)
    
    

      
田厝里
      
POLYGON ((120.2375596850001 22.94529373500006,...
      
POINT (120.2418300572598 22.93867944083052)
    
    

      
東區
      
大智里
      
POLYGON ((120.233204011 22.96589728700008, 120...
      
POINT (120.2325416129247 22.96284423430318)
    
    

      
東智里
      
POLYGON ((120.217005781 22.96058606200006, 120...
      
POINT (120.2235481999355 22.96281507759139)
    
    

      
南萣橋
      
南區
      
佛壇里
      
POLYGON ((120.1747451690001 22.91170775300009,...
      
POINT (120.1785367657243 22.91875063728222)
    
    

      
同安里
      
POLYGON ((120.187879942 22.92640428900006, 120...
      
POINT (120.1881169398381 22.92313991136196)
    
    

      
松安里
      
POLYGON ((120.175366369 22.92612485200004, 120...
      
POINT (120.178455717361 22.92451446296843)
    
    

      
南雄橋
      
關廟區
      
布袋里
      
POLYGON ((120.349563676 22.93179368600005, 120...
      
POINT (120.3375346473909 22.91166313362174)
    
    

      
東勢里
      
POLYGON ((120.332022532 22.95800301100007, 120...
      
POINT (120.3415567128484 22.95112205794322)
    
    

      
松腳里
      
POLYGON ((120.3526931680001 22.96152399500005,...
      
POINT (120.34330698002 22.95780778327464)
    
    

      
深坑里
      
POLYGON ((120.34870388 22.94649154800004, 120....
      
POINT (120.3363869146617 22.93366439777812)
    
    

      
田中里
      
POLYGON ((120.3717613880001 22.91075750000005,...
      
POINT (120.3582093896866 22.90159014272346)
    
    

      
龜洞里
      
POLYGON ((120.345510008 22.91072922600006, 120...
      
POINT (120.3454111769759 22.89717713962554)
    
    

      
龍崎區
      
中坑里
      
POLYGON ((120.3541329560001 22.96324020900005,...
      
POINT (120.362424399793 22.9485571300656)
    
    

      
楠坑里
      
POLYGON ((120.379699648 22.94739124300008, 120...
      
POINT (120.3663643178941 22.92712284755545)
    
    

      
古亭橋
      
龍崎區
      
大坪里
      
POLYGON ((120.3866781300001 22.95101579500005,...
      
POINT (120.3874290628308 22.93140194396365)
    
    

      
牛埔里
      
POLYGON ((120.429478162 22.94428151200009, 120...
      
POINT (120.4125267797126 22.92900977286267)
    
    

      
永寧橋
      
仁德區
      
大甲里
      
POLYGON ((120.21018799 22.93337848900006, 120....
      
POINT (120.2080013398754 22.92188019882346)
    
    

      
南區
      
興農里
      
POLYGON ((120.199991877 22.93368823400004, 120...
      
POINT (120.190666316084 22.92958158534336)
    
    

      
石安橋
      
歸仁區
      
六甲里
      
POLYGON ((120.2724993920001 22.95868469300007,...
      
POINT (120.2791544829967 22.94752036333348)
    
    

      
...
      
...
      
...
      
...
      
...
      
...
    
    

      
鹽水溪
      
鹽水溪橋
      
安南區
      
海東里
      
POLYGON ((120.1908609660001 23.04567655500006,...
      
POINT (120.1882050186764 23.03823548228013)
    
    

      
海西里
      
POLYGON ((120.178756787 23.04317273500004, 120...
      
POINT (120.1767809226788 23.03341870901626)
    
    

      
淵中里
      
POLYGON ((120.1594793050001 23.04502295700007,...
      
POINT (120.1692056972109 23.04433301616037)
    
    

      
淵東里
      
POLYGON ((120.1741320750001 23.06142640500008,...
      
POINT (120.1760790924916 23.0557956348511)
    
    

      
淵西里
      
POLYGON ((120.171371603 23.06155712200007, 120...
      
POINT (120.1640210585676 23.05474972330176)
    
    

      
溪墘里
      
POLYGON ((120.1926303830001 23.02932030500006,...
      
POINT (120.1926137797817 23.02455873572563)
    
    

      
溪心里
      
POLYGON ((120.1834247180001 23.06086240700006,...
      
POINT (120.1846589256742 23.05247561345312)
    
    

      
溪東里
      
POLYGON ((120.1989491750001 23.02898645400006,...
      
POINT (120.2017640409874 23.02560909983474)
    
    

      
理想里
      
POLYGON ((120.191110231 23.04131829000005, 120...
      
POINT (120.1914309699523 23.03623137063388)
    
    

      
顯宮里
      
POLYGON ((120.141912756 23.06060058300005, 120...
      
POINT (120.1412789648085 23.04614455419246)
    
    

      
鹿耳里
      
POLYGON ((120.1332237300001 23.04290877500006,...
      
POINT (120.1269589473348 23.03150676062764)
    
    

      
安平區
      
億載里
      
POLYGON ((120.163563831 22.99735129400005, 120...
      
POINT (120.1599970075414 22.99099197379468)
    
    

      
國平里
      
POLYGON ((120.1653425110001 22.97203739100007,...
      
POINT (120.1694787247644 22.98268761131835)
    
    

      
平安里
      
POLYGON ((120.180125202 22.99910735200007, 120...
      
POINT (120.1759743603053 22.99885010295113)
    
    

      
平通里
      
POLYGON ((120.168815859 22.99826279100006, 120...
      
POINT (120.1677087109145 22.99490565137893)
    
    

      
建平里
      
POLYGON ((120.182134754 22.99793705600007, 120...
      
POINT (120.1828090251043 22.99355968205091)
    
    

      
怡平里
      
POLYGON ((120.1793677740001 22.99796563800004,...
      
POINT (120.1772042049055 22.99413568635669)
    
    

      
文平里
      
POLYGON ((120.1794278210001 22.99008333400008,...
      
POINT (120.1817345408139 22.98653898396358)
    
    

      
海頭里
      
POLYGON ((120.158274224 23.00572737000005, 120...
      
POINT (120.1616330800606 23.00304302687389)
    
    

      
港仔里
      
POLYGON ((120.1619971280001 23.00076855500004,...
      
POINT (120.164452178021 22.99912526053937)
    
    

      
漁光里
      
POLYGON ((120.1554351630001 22.96750297300008,...
      
POINT (120.1562620921824 22.98043271550462)
    
    

      
石門里
      
POLYGON ((120.165006479 23.00272024500009, 120...
      
POINT (120.1661525869892 23.00089649084019)
    
    

      
育平里
      
POLYGON ((120.1640186400001 22.99185749100008,...
      
POINT (120.1663878760121 22.98860058313892)
    
    

      
華平里
      
POLYGON ((120.172726969 22.99763310100008, 120...
      
POINT (120.1735205023927 22.99430712728919)
    
    

      
西門里
      
POLYGON ((120.157843007 23.00581678500004, 120...
      
POINT (120.1556466562269 23.00199009550671)
    
    

      
金城里
      
POLYGON ((120.1401115790001 22.99806948500009,...
      
POINT (120.149964946305 22.99603873892513)
    
    

      
東區
      
大同里
      
POLYGON ((120.211895138 22.98881609800009, 120...
      
POINT (120.2125200667653 22.98450428966482)
    
    

      
大德里
      
POLYGON ((120.215211683 22.97991667600007, 120...
      
POINT (120.2147735879682 22.97823052877517)
    
    

      
大福里
      
POLYGON ((120.216131139 22.97703255200008, 120...
      
POINT (120.2155634392679 22.97474020409799)
    
    

      
路東里
      
POLYGON ((120.2147968620001 22.98122628500005,...
      
POINT (120.2136643234075 22.98030871505973)
    
  

607 rows × 2 columns