python 转换KMZ,KML,Shapefile
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# Author:
# Linwood Creekmore III
# email: valinvescap@gmail.com
# Acknowledgements:
# http://programmingadvent.blogspot.com/2013/06/kmzkml-file-parsing-with-python.html
# http://gis.stackexchange.com/questions/159681/geopandas-cant-save-geojson
# https://gist.github.com/mciantyre/32ff2c2d5cd9515c1ee7
'''
Sample files to test (everything doesn't work, but most do)
--------------------
Google List of KMZs: https://sites.google.com/a/mcpsweb.org/google-earth-kmz/kmz-files
NOAA KMZ: https://data.noaa.gov/dataset/climate-reconstructions/resource/13f35d9b-a738-4c3b-8ba3-a22e3192e7b6
Washington DC GIS Data/Quadrants: http://opendata.dc.gov/datasets/02923e4697804406b9ee3268a160db99_11.kml
Examples
----------
# output to geopandas
a = keyholemarkup2x('LGGWorldCapitals.kmz',output='gpd')
# plot this new file, use %matplotlib inline if you are in a notebook
#%matplotlib inline
a.plot()
# convert to shapefile
a = keyholemarkup2x('DC_Quadrants.kml',output='shp')
a = keyholemarkup2x('C:\\Users\\mcmah\\Dropbox\\Code\\Shape Files\\CTA_RailLines.kmz',output='shp')
'''
import pandas as pd
from io import BytesIO,StringIO
from zipfile import ZipFile
import re,os
import numpy as np
import xml.sax, xml.sax.handler
from html.parser import HTMLParser
import pandas as pd
from html.parser import HTMLParser
class MyHTMLParser(HTMLParser):
def __init__(self):
# initialize the base class
HTMLParser.__init__(self)
self.inTable=False
self.mapping = {}
self.buffer = ""
self.name_tag = ""
self.series = pd.Series()
def handle_starttag(self, tag, attrs):
if tag == 'table':
self.inTable = True
def handle_data(self, data):
if self.inTable:
self.buffer = data.strip(' \n\t').split(':')
if len(self.buffer)==2:
self.mapping[self.buffer[0]]=self.buffer[1]
self.series = pd.Series(self.mapping)
class PlacemarkHandler(xml.sax.handler.ContentHandler):
def __init__(self):
self.inName = False # handle XML parser events
self.inPlacemark = False
self.mapping = {}
self.buffer = ""
self.name_tag = ""
def startElement(self, name, attributes):
if name == "Placemark": # on start Placemark tag
self.inPlacemark = True
self.buffer = ""
if self.inPlacemark:
if name == "name": # on start title tag
self.inName = True # save name text to follow
def characters(self, data):
if self.inPlacemark: # on text within tag
self.buffer += data # save text if in title
def endElement(self, name):
self.buffer = self.buffer.strip('\n\t')
if name == "Placemark":
self.inPlacemark = False
self.name_tag = "" #clear current name
elif name == "name" and self.inPlacemark:
self.inName = False # on end title tag
self.name_tag = self.buffer.strip()
self.mapping[self.name_tag] = {}
elif self.inPlacemark:
if name in self.mapping[self.name_tag]:
self.mapping[self.name_tag][name] += self.buffer
else:
self.mapping[self.name_tag][name] = self.buffer
self.buffer = ""
def spatializer(row):
"""
Function to convert string objects to Python spatial objects
"""
#############################
# coordinates field
#############################
try:
# look for the coordinates column
data = row['coordinates'].strip(' \t\n\r')
except:
pass
try:
import shapely
from shapely.geometry import Polygon,LineString,Point
except ImportError as e:
raise ImportError('This operation requires shapely. {0}'.format(e))
import ast
lsp = data.strip().split(' ')
linestring = map(lambda x: ast.literal_eval(x),lsp)
try:
spatial = Polygon(LineString(linestring))
convertedpoly = pd.Series({'geometry':spatial})
return convertedpoly
except:
try:
g = ast.literal_eval(data)
points = pd.Series({'geometry':Point(g[:2]),
'altitude':g[-1]})
return points
except:
pass
try:
# Test for latitude and longitude columns
lat=float(row['latitude'])
lon=float(row['longitude'])
point = Point(lon,lat)
convertedpoly = pd.Series({'geometry':point})
return convertedpoly
except:
pass
def htmlizer(row):
htmlparser = MyHTMLParser()
htmlparser.feed(row['description'])
return htmlparser.series
def keyholemarkup2x(file,output='df'):
"""
Takes Keyhole Markup Language Zipped (KMZ) or KML file as input. The
output is a pandas dataframe, geopandas geodataframe, csv, geojson, or
shapefile.
All core functionality from:
http://programmingadvent.blogspot.com/2013/06/kmzkml-file-parsing-with-python.html
Parameters
----------
file : {string}
The string path to your KMZ or .
output : {string}
Defines the type of output. Valid selections include:
- shapefile - 'shp', 'shapefile', or 'ESRI Shapefile'
Returns
-------
self : object
"""
r = re.compile(r'(?<=\.)km+[lz]?',re.I)
try:
extension = r.search(file).group(0) #(re.findall(r'(?<=\.)[\w]+',file))[-1]
except IOError as e:
logging.error("I/O error {0}".format(e))
if (extension.lower()=='kml') is True:
buffer = file
elif (extension.lower()=='kmz') is True:
kmz = ZipFile(file, 'r')
vmatch = np.vectorize(lambda x:bool(r.search(x)))
A = np.array(kmz.namelist())
sel = vmatch(A)
buffer = kmz.open(A[sel][0],'r')
else:
raise ValueError('Incorrect file format entered. Please provide the '
'path to a valid KML or KMZ file.')
parser = xml.sax.make_parser()
handler = PlacemarkHandler()
parser.setContentHandler(handler)
parser.parse(buffer)
try:
kmz.close()
except:
pass
df = pd.DataFrame(handler.mapping).T
names = list(map(lambda x: x.lower(),df.columns))
if 'description' in names:
extradata = df.apply(PlacemarkHandler.htmlizer,axis=1)
df = df.join(extradata)
output = output.lower()
if output=='df' or output=='dataframe' or output == None:
result = df
elif output=='csv':
out_filename = file[:-3] + "csv"
df.to_csv(out_filename,encoding='utf-8',sep="\t")
result = ("Successfully converted {0} to CSV and output to"
" disk at {1}".format(file,out_filename))
elif output=='gpd' or output == 'gdf' or output=='geoframe' or output == 'geodataframe':
try:
import shapely
from shapely.geometry import Polygon,LineString,Point
except ImportError as e:
raise ImportError('This operation requires shapely. {0}'.format(e))
try:
import fiona
except ImportError as e:
raise ImportError('This operation requires fiona. {0}'.format(e))
try:
import geopandas as gpd
except ImportError as e:
raise ImportError('This operation requires geopandas. {0}'.format(e))
geos = gpd.GeoDataFrame(df.apply(PlacemarkHandler.spatializer,axis=1))
result = gpd.GeoDataFrame(pd.concat([df,geos],axis=1))
elif output=='geojson' or output=='json':
try:
import shapely
from shapely.geometry import Polygon,LineString,Point
except ImportError as e:
raise ImportError('This operation requires shapely. {0}'.format(e))
try:
import fiona
except ImportError as e:
raise ImportError('This operation requires fiona. {0}'.format(e))
try:
import geopandas as gpd
except ImportError as e:
raise ImportError('This operation requires geopandas. {0}'.format(e))
try:
import geojson
except ImportError as e:
raise ImportError('This operation requires geojson. {0}'.format(e))
geos = gpd.GeoDataFrame(df.apply(PlacemarkHandler.spatializer,axis=1))
gdf = gpd.GeoDataFrame(pd.concat([df,geos],axis=1))
out_filename = file[:-3] + "geojson"
gdf.to_file(out_filename,driver='GeoJSON')
validation = geojson.is_valid(geojson.load(open(out_filename)))['valid']
if validation == 'yes':
result = ("Successfully converted {0} to GeoJSON and output to"
" disk at {1}".format(file,out_filename))
else:
raise ValueError('The geojson conversion did not create a '
'valid geojson object. Try to clean your '
'data or try another file.')
elif output=='shapefile' or output=='shp' or output =='esri shapefile':
try:
import shapely
from shapely.geometry import Polygon,LineString,Point
except ImportError as e:
raise ImportError('This operation requires shapely. {0}'.format(e))
try:
import fiona
except ImportError as e:
raise ImportError('This operation requires fiona. {0}'.format(e))
try:
import geopandas as gpd
except ImportError as e:
raise ImportError('This operation requires geopandas. {0}'.format(e))
try:
import shapefile
except ImportError as e:
raise ImportError('This operation requires pyshp. {0}'.format(e))
geos = gpd.GeoDataFrame(df.apply(PlacemarkHandler.spatializer,axis=1))
gdf = gpd.GeoDataFrame(pd.concat([df,geos],axis=1))
out_filename = file[:-3] + "shp"
gdf.to_file(out_filename,driver='ESRI Shapefile')
sf = shapefile.Reader(out_filename)
import shapefile
sf = shapefile.Reader(out_filename)
if len(sf.shapes())>0:
validation = "yes"
else:
validation = "no"
if validation == 'yes':
result = ("Successfully converted {0} to Shapefile and output to"
" disk at {1}".format(file,out_filename))
else:
raise ValueError('The Shapefile conversion did not create a '
'valid shapefile object. Try to clean your '
'data or try another file.')
else:
raise ValueError('The conversion returned no data; check if'
' you entered a correct output file type. '
'Valid output types are geojson, shapefile,'
' csv, geodataframe, and/or pandas dataframe.')
return result
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