forked from s_ranjbar/city_retrofit
added city_layers_test.py, solved bugs in gpandas importer and idf exporter
This commit is contained in:
Pilar
parent
db30870fc1
commit
23cca13359
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@ -456,20 +456,16 @@ class Idf:
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self._idf.intersect_match()
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def _add_shading(self, building):
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for internal_zone in building.internal_zones:
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for thermal_zone in internal_zone.thermal_zones:
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for boundary in thermal_zone.thermal_boundaries:
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shading = self._idf.newidfobject(self._SHADING, Name=f'{boundary.parent_surface.name}')
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coordinates = self._matrix_to_list(boundary.parent_surface.solid_polygon.coordinates,
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self._city.lower_corner)
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shading.setcoords(coordinates)
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solar_reflectance = 1.0 - boundary.outside_solar_absorptance
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visible_reflectance = 1.0 - boundary.outside_visible_absorptance
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self._idf.newidfobject(self._SHADING_PROPERTY,
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Shading_Surface_Name=f'{boundary.parent_surface.name}',
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Diffuse_Solar_Reflectance_of_Unglazed_Part_of_Shading_Surface=solar_reflectance,
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Diffuse_Visible_Reflectance_of_Unglazed_Part_of_Shading_Surface=visible_reflectance,
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Fraction_of_Shading_Surface_That_Is_Glazed=0)
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for surface in building.surfaces:
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shading = self._idf.newidfobject(self._SHADING, Name=f'{surface.name}')
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coordinates = self._matrix_to_list(surface.solid_polygon.coordinates,
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self._city.lower_corner)
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shading.setcoords(coordinates)
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solar_reflectance = surface.short_wave_reflectance
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self._idf.newidfobject(self._SHADING_PROPERTY,
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Shading_Surface_Name=f'{surface.name}',
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Diffuse_Solar_Reflectance_of_Unglazed_Part_of_Shading_Surface=solar_reflectance,
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Fraction_of_Shading_Surface_That_Is_Glazed=0)
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# todo: Add properties for that name
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@ -48,7 +48,7 @@ class SimplifiedRadiosityAlgorithm:
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for surface in building.surfaces:
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surface_dict = {
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'@id': f'{surface.id}',
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'@ShortWaveReflectance': f'{surface.swr}'
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'@ShortWaveReflectance': f'{surface.short_wave_reflectance}'
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}
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for point_index, point in enumerate(surface.perimeter_polygon.coordinates):
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point = self._correct_point(point)
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@ -58,8 +58,7 @@ class GPandas:
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if self._city is None:
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self._city = City(self._lower_corner, self._upper_corner, self._srs_name)
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for scene_index, bldg in self._scene.iterrows():
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geometry = bldg.geom
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polygon = ShapelyPoly(geometry['coordinates'][0])
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polygon = bldg.geometry
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height = float(bldg['height'])
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building_mesh = trimesh.creation.extrude_polygon(polygon, height)
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trimesh.repair.fill_holes(building_mesh)
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@ -71,7 +70,6 @@ class GPandas:
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function = cte.RESIDENTIAL
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else:
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function = cte.INDUSTRY
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surfaces = []
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for face_index, face in enumerate(building_mesh.faces):
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points = []
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81
unittests/city_layers_test.py
Normal file
81
unittests/city_layers_test.py
Normal file
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@ -0,0 +1,81 @@
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"""
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CityLayersTest
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SPDX - License - Identifier: LGPL - 3.0 - or -later
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Copyright © 2023 Concordia CERC group
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Project Coder: Milad Aghamohamadnia --- milad.aghamohamadnia@concordia.ca
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"""
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from unittest import TestCase
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import json
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import os
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import time
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import uuid
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from pathlib import Path
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from imports.geometry_factory import GeometryFactory
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from imports.usage_factory import UsageFactory
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from imports.construction_factory import ConstructionFactory
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from exports.energy_building_exports_factory import EnergyBuildingsExportsFactory
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import pandas as pd
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from geopandas import GeoDataFrame
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from shapely.geometry import Polygon
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class CityLayerTest(TestCase):
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@staticmethod
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def _prepare_buildings(bldgs_group):
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target_json = bldgs_group['target']
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adjacent_json = bldgs_group['adjacent']
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target_buildings = [f"building_{target_json['index']}"]
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adjacent_buildings = [f"building_{el}" for el in adjacent_json['Ids']]
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target_dict = [dict(
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name=f"building_{target_json['index']}",
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height=target_json['height_max'],
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idx=target_json['index'],
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uid=target_json['uid'],
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year_built=2005,
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# year_built= 2005 if target_json['year_built']==9999 else target_json['year_built'],
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coords=target_json['coords'],
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function="residential",
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# function= "residential" if target_json['year_built']>2000 else "industry",
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)]
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adjacent_dict = [dict(
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name=f"building_{el['index']}",
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height=el['height_max'],
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idx=el['index'],
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uid=el['uid'],
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year_built=2005,
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# year_built=2005 if el['year_built']==9999 else el['year_built'],
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coords=el['geom']['coordinates'],
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function="residential",
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# function= "residential" if el['year_built']>2000 else "industry",
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) for el in adjacent_json['data']]
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df = pd.DataFrame(target_dict + adjacent_dict)
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geometries = [Polygon(row['coords'][0]) for ix, row in df.iterrows()]
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gdf = GeoDataFrame(df, crs="EPSG:4326", geometry=geometries)
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gdf = gdf.set_crs('EPSG:4326')
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gdf = gdf.to_crs('EPSG:26911')
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return gdf, target_buildings, adjacent_buildings
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def _genidf(self, bldgs_group):
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t0 = time.time()
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buildings_df, target_buildings, adjacent_buildings = self._prepare_buildings(bldgs_group)
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output_path = (Path(__file__).parent / 'tests_outputs').resolve()
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city = GeometryFactory('gpandas', data_frame=buildings_df).city
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ConstructionFactory('nrel', city).enrich()
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UsageFactory('comnet', city).enrich()
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EnergyBuildingsExportsFactory('idf', city, output_path, target_buildings=target_buildings).export_debug()
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filepath = os.path.join(output_path, city.name + ".idf")
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newfilepath = filepath[:-4] + "_" + uuid.uuid4().hex[:10] + ".idf"
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print(filepath)
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print(newfilepath)
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os.rename(filepath, newfilepath)
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print(f"It took {round((time.time() - t0), 0)} seconds")
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return newfilepath
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def test_city_layers(self):
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json_path = str((Path(__file__).parent / 'tests_data' / 'city_layers.json').resolve())
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with open(json_path) as json_file:
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data = json.loads(json_file.read())
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self._genidf(data)
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363
unittests/tests_data/city_layers.json
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363
unittests/tests_data/city_layers.json
Normal file
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@ -0,0 +1,363 @@
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{
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"target": {
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"layerName": "public.building_footprint_year_built_height_max",
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"height_max": 13,
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"index": 287809,
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"year_built": 1952,
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"uid": 1039258,
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"centroid": [
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-73.59838038682938,
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45.493163447971085
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],
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"area": 119.59674983363819,
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"coords": [
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[
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[
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-73.59848499298096,
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45.49319823193981
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],
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[
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-73.59841525554657,
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45.493239596593924
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],
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[
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-73.5982757806778,
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45.49313054425838
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],
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[
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-73.59834551811218,
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45.49308541909225
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],
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[
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-73.59848499298096,
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45.49319823193981
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]
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]
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]
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},
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"adjacent": {
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"data": [
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{
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"__typename": "building_footprint_year_built_height_max",
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"index": 1586,
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"height_max": 12,
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"geom": {
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"type": "Polygon",
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"crs": {
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"type": "name",
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"properties": {
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"name": "urn:ogc:def:crs:EPSG::4326"
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}
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},
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"coordinates": [
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[
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[
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-73.59812,
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45.493495
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],
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[
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-73.598085,
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45.493525
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],
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[
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-73.598017,
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45.493487
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],
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[
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-73.59812,
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45.493398
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],
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[
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-73.59821,
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45.493449
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],
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[
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-73.598142,
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45.493508
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],
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[
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-73.59812,
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45.493495
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]
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]
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]
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},
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"year_built": 1929,
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"uid": 1039256
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},
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{
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"__typename": "building_footprint_year_built_height_max",
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"index": 11964,
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"height_max": 11,
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"geom": {
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"type": "Polygon",
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"crs": {
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"type": "name",
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"properties": {
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"name": "urn:ogc:def:crs:EPSG::4326"
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}
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},
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"coordinates": [
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[
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[
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-73.5984992790639,
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45.4929564079915
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],
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[
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-73.598462,
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45.493019
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],
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[
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-73.598313,
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45.492975
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],
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[
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-73.5983570524121,
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45.4929010354563
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],
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[
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-73.5984992790639,
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45.4929564079915
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]
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]
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]
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},
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"year_built": 1965,
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"uid": 1039090
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},
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{
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"__typename": "building_footprint_year_built_height_max",
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"index": 11965,
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"height_max": 11,
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"geom": {
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"type": "Polygon",
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"crs": {
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"type": "name",
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"properties": {
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"name": "urn:ogc:def:crs:EPSG::4326"
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}
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},
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"coordinates": [
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[
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[
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-73.5983570524121,
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45.4929010354563
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],
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[
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-73.598394,
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45.492839
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],
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[
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-73.598543,
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45.492883
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],
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[
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-73.5984992790639,
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45.4929564079915
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],
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[
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-73.5983570524121,
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45.4929010354563
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]
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]
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]
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},
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"year_built": 1965,
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"uid": 1039088
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},
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{
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"__typename": "building_footprint_year_built_height_max",
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"index": 252931,
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"height_max": 22,
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"geom": {
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"type": "Polygon",
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"crs": {
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"type": "name",
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"properties": {
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"name": "urn:ogc:def:crs:EPSG::4326"
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}
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},
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"coordinates": [
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[
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[
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-73.598625,
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45.492713
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],
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[
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-73.598668,
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45.49268
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],
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[
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-73.598755,
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45.492735
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],
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[
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-73.598659,
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45.49281
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],
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[
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-73.598521,
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45.492723
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],
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[
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-73.598575,
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45.492682
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],
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[
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-73.598625,
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45.492713
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]
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]
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]
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},
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"year_built": 1983,
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"uid": 1039086
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},
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{
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"__typename": "building_footprint_year_built_height_max",
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"index": 275748,
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"height_max": 12,
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"geom": {
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"type": "Polygon",
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"crs": {
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"type": "name",
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"properties": {
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"name": "urn:ogc:def:crs:EPSG::4326"
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}
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},
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"coordinates": [
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[
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[
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-73.597909,
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45.493307
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],
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[
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-73.598014,
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45.493349
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],
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[
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-73.597928,
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45.493454
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],
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[
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-73.597823,
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45.493412
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],
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[
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-73.597909,
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45.493307
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]
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]
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]
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},
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"year_built": 1929,
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"uid": 1039091
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},
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{
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"__typename": "building_footprint_year_built_height_max",
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"index": 308721,
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"height_max": 15,
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"geom": {
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"type": "Polygon",
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"crs": {
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"type": "name",
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"properties": {
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"name": "urn:ogc:def:crs:EPSG::4326"
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}
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},
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"coordinates": [
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[
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[
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-73.598655,
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45.493348
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],
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[
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-73.598681,
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45.493326
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||||
],
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||||
[
|
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-73.59876,
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||||
45.493373
|
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],
|
||||
[
|
||||
-73.598652,
|
||||
45.493462
|
||||
],
|
||||
[
|
||||
-73.598595,
|
||||
45.493427
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||||
],
|
||||
[
|
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-73.598621,
|
||||
45.493406
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||||
],
|
||||
[
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-73.598571,
|
||||
45.493376
|
||||
],
|
||||
[
|
||||
-73.598627,
|
||||
45.493331
|
||||
],
|
||||
[
|
||||
-73.598655,
|
||||
45.493348
|
||||
]
|
||||
]
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]
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},
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"year_built": 1950,
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"uid": 1039163
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||||
},
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{
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"__typename": "building_footprint_year_built_height_max",
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"index": 312417,
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"height_max": 14,
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"geom": {
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"type": "Polygon",
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"crs": {
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"type": "name",
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"properties": {
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"name": "urn:ogc:def:crs:EPSG::4326"
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}
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},
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"coordinates": [
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[
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[
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-73.598836,
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45.49324
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],
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[
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-73.598723,
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45.493191
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],
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[
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-73.598873,
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45.493021
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],
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[
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-73.598985,
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45.493069
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],
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[
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-73.598836,
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45.49324
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]
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]
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]
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},
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"year_built": 1890,
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"uid": 1039165
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}
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],
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"Ids": [
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1586,
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11964,
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11965,
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252931,
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275748,
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308721,
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312417
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]
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}
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}
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Block a user