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""" |
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OSM landuse extraction and load areas creation. |
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**Landuse** |
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* Landuse data is extracted from OpenStreetMap: residential, retail, |
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industrial, Agricultural |
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* Data is cut with German borders (VG 250), data outside is dropped |
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* Invalid geometries are fixed |
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* Results are stored in table `openstreetmap.osm_landuse` |
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**Load Areas** |
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TBD |
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""" |
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import os |
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from airflow.operators.postgres_operator import PostgresOperator |
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from geoalchemy2.types import Geometry |
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from sqlalchemy import Column, Float, Integer, String |
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from sqlalchemy.dialects.postgresql import HSTORE |
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from sqlalchemy.ext.declarative import declarative_base |
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import importlib_resources as resources |
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from egon.data import db |
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from egon.data.datasets import Dataset |
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import egon.data.config |
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# will be later imported from another file ### |
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Base = declarative_base() |
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class OsmPolygonUrban(Base): |
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__tablename__ = "osm_landuse" |
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__table_args__ = {"schema": "openstreetmap"} |
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id = Column(Integer, primary_key=True) |
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osm_id = Column(Integer) |
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name = Column(String) |
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sector = Column(Integer) |
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sector_name = Column(String(20)) |
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area_ha = Column(Float) |
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tags = Column(HSTORE) |
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vg250 = Column(String(10)) |
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geom = Column(Geometry("MultiPolygon", 3035)) |
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class OsmLanduse(Dataset): |
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def __init__(self, dependencies): |
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super().__init__( |
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name="OsmLanduse", |
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version="0.0.0", |
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dependencies=dependencies, |
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tasks=( |
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create_landuse_table, |
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PostgresOperator( |
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task_id="osm_landuse_extraction", |
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sql=resources.read_text( |
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__name__, "osm_landuse_extraction.sql" |
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), |
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postgres_conn_id="egon_data", |
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autocommit=True, |
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), |
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), |
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) |
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class LoadArea(Dataset): |
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def __init__(self, dependencies): |
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super().__init__( |
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name="LoadArea", |
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version="0.0.1", |
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dependencies=dependencies, |
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tasks=( |
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osm_landuse_melt, |
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census_cells_melt, |
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osm_landuse_census_cells_melt, |
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loadareas_create, |
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loadareas_add_demand, |
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drop_temp_tables, |
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), |
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) |
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def create_landuse_table(): |
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"""Create tables for landuse data |
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Returns |
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------- |
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None. |
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""" |
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cfg = egon.data.config.datasets()["landuse"]["target"] |
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# Create schema if not exists |
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db.execute_sql(f"""CREATE SCHEMA IF NOT EXISTS {cfg['schema']};""") |
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# Drop tables |
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db.execute_sql( |
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f"""DROP TABLE IF EXISTS |
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{cfg['schema']}.{cfg['table']} CASCADE;""" |
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) |
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engine = db.engine() |
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OsmPolygonUrban.__table__.create(bind=engine, checkfirst=True) |
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def execute_sql_script(script): |
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"""Execute SQL script |
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Parameters |
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---------- |
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script : str |
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Filename of script |
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""" |
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db.execute_sql_script(os.path.join(os.path.dirname(__file__), script)) |
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def osm_landuse_melt(): |
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"""Melt all OSM landuse areas by: buffer, union, unbuffer""" |
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print("Melting OSM landuse areas from openstreetmap.osm_landuse...") |
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execute_sql_script("osm_landuse_melt.sql") |
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def census_cells_melt(): |
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"""Melt all census cells: buffer, union, unbuffer""" |
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print( |
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"Melting census cells from " |
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"society.destatis_zensus_population_per_ha_inside_germany..." |
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) |
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execute_sql_script("census_cells_melt.sql") |
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def osm_landuse_census_cells_melt(): |
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"""Melt OSM landuse areas and census cells""" |
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print( |
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"Melting OSM landuse areas from openstreetmap.osm_landuse_melted and " |
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"census cells from " |
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"society.egon_destatis_zensus_cells_melted_cluster..." |
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) |
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execute_sql_script("osm_landuse_census_cells_melt.sql") |
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def loadareas_create(): |
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"""Create load areas from merged OSM landuse and census cells: |
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* Cut Loadarea with MV Griddistrict |
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* Identify and exclude Loadarea smaller than 100m². |
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* Generate Centre of Loadareas with Centroid and PointOnSurface. |
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* Calculate population from Census 2011. |
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* Cut all 4 OSM sectors with MV Griddistricts. |
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* Calculate statistics like NUTS and AGS code. |
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* Check for Loadareas without AGS code. |
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""" |
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print("Create initial load areas and add some sector stats...") |
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execute_sql_script("loadareas_create.sql") |
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def loadareas_add_demand(): |
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"""Adds consumption and peak load per sector to load areas""" |
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print("Add consumption and peak loads to load areas...") |
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execute_sql_script("loadareas_add_demand.sql") |
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def drop_temp_tables(): |
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print("Dropping temp tables, views and sequences...") |
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execute_sql_script("drop_temp_tables.sql") |
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openego /
eGon-data
