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HTenkanen

Helsinki Region GTFS-RT sample data

Dataset collected from GTFS-RT feed provided by Helsinki Region Transport. Used for educational purposes.

HTenkanen

Concave Hull in Python

A modified version for calculating concave hull (see source) based on GeoDataFrame of points

from scipy.spatial import Delaunay
import numpy as np
from shapely.ops import polygonize, cascaded_union
from shapely.geometry import MultiLineString

HTenkanen

HTenkanen

World Urban Areas

Boundaries of urban areas of the world combining data from different sources. The purpose of this dataset is to provide information about urban areas that helps to determine speed-limits for OpenStreetMap roads across the world in a more accurate manner.

Starting point for this layer is Urban Areas of the world by Stanford (2012) that uses the Oak Ridge National Laboratory's LandScan population database.

This data has been improved by replacing country specific data from:

HTenkanen

import pandas as pd
import geopandas as gpd
from sqlalchemy import create_engine
from geoalchemy2 import Geometry
from shapely.geometry import MultiLineString, MultiPoint, MultiPolygon
from shapely.wkb import dumps
import io
from pyproj import CRS
import csv
import time

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Test GTFS data for New Orleans.

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HTenkanen

from_id,to_id,walk_t,walk_d,bike_s_t,bike_f_t,bike_d,pt_r_tt,pt_r_t,pt_r_d,pt_m_tt,pt_m_t,pt_m_d,car_r_t,car_r_d,car_m_t,car_m_d,car_sl_d
5778014,5961891,-1,-1,124,78,30399,-1,-1,-1,-1,-1,-1,58,-1,51,-1,30
5778014,5963631,-1,-1,129,82,30081,-1,-1,-1,-1,-1,-1,54,-1,48,-1,30
5778014,5975375,-1,-1,127,80,31551,-1,-1,-1,-1,-1,-1,60,-1,54,-1,31
5778015,5961891,-1,-1,124,78,30399,-1,-1,-1,-1,-1,-1,58,-1,51,-1,30
5778015,5963631,-1,-1,129,82,30081,-1,-1,-1,-1,-1,-1,54,-1,48,-1,30
5778015,5975375,-1,-1,127,80,31551,-1,-1,-1,-1,-1,-1,60,-1,54,-1,31
5778016,5961891,-1,-1,135,85,32962,-1,-1,-1,-1,-1,-1,65,-1,56,-1,34
5778016,5963631,-1,-1,141,89,33191,-1,-1,-1,-1,-1,-1,60,-1,54,-1,34
5778016,5975375,-1,-1,139,88,34468,-1,-1,-1,-1,-1,-1,66,-1,59,-1,35

HTenkanen

import networkx as nx
from osgeo import ogr
import os

def load_graph_from_Digiroad_shape(filepath, direction='AJOSUUNTA', both_ways=2, against=3, along=4, strict=True):
    """Generates nx.MultiDiGraph() object from Digiroad 2.0 Shapefile. 

    Parameters
    ----------