def query_construction(search_area):
nominatim_query=Nominatim().query(search_area)
query_01=overpassQueryBuilder(area=nominatim_query.areaId(),elementType=['node','way','relation'], selector=["military"],includeGeometry=True)
query_02=overpassQueryBuilder(area=nominatim_query.areaId(),elementType=['node','way','relation'], selector='"landuse"="military"',includeGeometry=True)
result_01=Overpass().query(query_01)
result_02=Overpass().query(query_02)
print("Pronađeno ukupno "+str(result_01.countElements())+" 'military' objekta")
print("Pronađeno ukupno "+str(result_02.countElements())+" 'landuse=military' objekta")
results=[result_01,result_02]
return results
from OSMPythonTools.nominatim import Nominatim
import folium
from folium.plugins.measure_control import MeasureControl
from matplotlib import cm
import sys, os
sys.path.insert(1, os.path.abspath('..'))
from helper.geoJsonHelper import groupBy
from helper.geoJsonToFolium import generateFeatureCollectionForGroups, styleFunction, cmMapColorToHex
from helper.overPassHelper import OverPassHelper
# postfix for f.i. file_names
areaName = "pieschen"
# area to query
pieschen = Nominatim().query('Pieschen, Dresden, Germany')
osmDataFiles = OverPassHelper().fetch(pieschen.areaId(),
areaName,
overrideFiles=False)
pieschenCoord = pieschen.toJSON()[0]
map = folium.Map(location=[pieschenCoord["lat"], pieschenCoord["lon"]],
tiles='Stamen Toner',
zoom_start=15)
# matplotlib colormap names
colormaps = ["hsv", "BrBG", "coolwarm"]
objectTypeTagMapping = {
"streets": "highway",
"buildings": "building",
"landuse": "landuse"
from OSMPythonTools.nominatim import Nominatim
from OSMPythonTools.overpass import overpassQueryBuilder, Overpass
import geopandas
import matplotlib.pyplot as plt
import pandas as pd
from helper.geoJsonConverter import osmObjectsToGeoJSON
areaName = "pieschen"
# area to query
pieschen = Nominatim().query('Pieschen, Dresden, Germany')
query = overpassQueryBuilder(area=pieschen.areaId(),
elementType="way",
selector=["'building'"],
out='geom')
buildings = osmObjectsToGeoJSON(Overpass().query(query).toJSON()["elements"])
buildingsGdf = geopandas.GeoDataFrame.from_features(buildings["features"])
#buildingsGdf.plot("building", legend = True)
buildingsGdf["area"] = buildingsGdf.geometry.area
dataFrame = pd.DataFrame(buildingsGdf)
#dataFrame.hist(column="area", by="building")
avgAreaPerBuildingType = dataFrame.groupby(["building"]).agg(
avg_area=("area", "mean"), count=("area", "count")).reset_index()
avgAreaPerBuildingType = avgAreaPerBuildingType.sort_values("count")
avgAreaPerBuildingType.plot.bar(x="building", y="count")
avgAreaPerBuildingType.plot.bar(x="building",
pieschen = Nominatim().query(areaOfInterest)
allBuildingsQuery = OsmDataQuery("homes", OsmObjectType.WAYANDRELATIONSHIP,
['"building"', 'abandoned!~"yes"'])
osmQueries = [
allBuildingsQuery,
OsmDataQuery("borders", OsmObjectType.WAY, [
'highway~"primary|primary_link|secondary|secondary_link|tertiary|tertiary_link|residential|motorway|unclassified|living_street"'
]),
OsmDataQuery("borders_railway", OsmObjectType.WAY,
["'railway'~'rail'"])
]
# https://wiki.openstreetmap.org/wiki/Overpass_API/Overpass_QL#By_polygon_.28poly.29 for filtering based on polygon (if borough based on openDataDresden)
# this query can take a while
osmData = overPassFetcher.directFetch(pieschen.areaId(), osmQueries)
buildings = next(osmData)
borders = unionFeatureCollections(*list(osmData))
alreadyBuiltRegions = False
if not alreadyBuiltRegions:
# Poor Mans Testing
#buildings = geojson.FeatureCollection(buildings["features"][:200])
logging.info("Fetched {} buildings".format(len(buildings["features"])))
groups, regionsPerApproach = buildGroupsAndRegions(buildings, borders)
else:
logging.info("Loading buildings, groups and regions")
# TODO: index seems to be messed up when loading?
with open("out/data/buildings_pieschen.json",
namedShopsThings = OsmDataQuery(
"osm_named_shops", OsmObject.WAYANDNODE,
["name", "shop", 'amenity!~"."', 'leisure!~"."'], "")
namedCraftThings = OsmDataQuery(
"osm_named_crafts", OsmObject.WAYANDNODE,
["name", "craft", 'amenity!~"."', 'leisure!~"."', 'shop!~"."'], "")
namedCompaniesThings = OsmDataQuery(
"osm_named_companies", OsmObject.WAYANDNODE, [
"name", "company", 'amenity!~"."', 'leisure!~"."', 'shop!~"."',
'craft!~"."'
], "")
osmQueries = [
namedAmenitiesThings, namedCompaniesThings, namedCraftThings,
namedCompaniesThings, namedShopsThings
]
osmData = OverPassHelper().directFetch(areaId=pieschen.areaId(),
osmQueries=osmQueries)
unionData = unionFeatureCollections(*osmData)
osmFeature = geoFeatureCollectionToFoliumFeatureGroup(
unionData,
"pink",
"Named amenities/leisure/shops/craft/companies in osm",
switchLatAndLong=True)
osmFeature.add_to(map)
# buildingRegions
file = open("out/data/apartmentRegions_pieschen.json", encoding='UTF-8')
handelsRegisterCompanies = json.load(file)
import json
from OSMPythonTools.nominatim import Nominatim
import folium
from folium.plugins.measure_control import MeasureControl
import sys, os
sys.path.insert(1, os.path.abspath('..'))
from helper.geoJsonHelper import groupBy
from helper.overPassHelper import OverPassHelper
from helper.OsmDataQuery import OsmDataQuery
from helper.OsmObjectType import OsmObjectType
pieschen = Nominatim().query('Pieschen, Dresden, Germany')
osmQuery = OsmDataQuery("streets", OsmObjectType.WAY, ["'highway'"], "highway")
all_streets = next(OverPassHelper().directFetch(pieschen.areaId(), [osmQuery]))
street_types = groupBy(all_streets, ["highway"])
piescheonCoord = [pieschen.toJSON()[0]["lat"], pieschen.toJSON()[0]["lon"]]
streetMap = folium.Map(location=piescheonCoord,
tiles='Stamen Toner',
zoom_start=15)
icon = folium.Icon(icon="pills", color='lightgray', icon_color='red')
folium.Marker(location=piescheonCoord, tooltip="test",
icon=icon).add_to(streetMap)
for type, streets in street_types.items():
properties = list(streets["features"][0]["properties"].keys())
folium.GeoJson(
import geopandas
import matplotlib.pyplot as plt
from OSMPythonTools.nominatim import Nominatim
import sys, os
sys.path.insert(0, os.path.abspath('..'))
from helper.overPassHelper import OverPassHelper
plt.rcParams["figure.figsize"] = (25, 25)
pieschen = Nominatim().query('Pieschen, Dresden, Germany')
OverPassHelper().fetch(pieschen.areaId(), "pieschen")
highWayFrame = geopandas.read_file("out/data/streets_pieschen.json",
driver='GeoJson')
print(highWayFrame.size)
print(highWayFrame.keys())
plot = highWayFrame.plot(column='highway', legend=True)
plt.show()
buildingsFrame = geopandas.read_file("out/data/geoPandas_Example.json")
print(buildingsFrame.size)
print(buildingsFrame.keys())
plot2 = buildingsFrame.plot(column='building', legend=True)
plt.show()
