Extract Specific Geographic Data

scraping data

geospatial

Introduction

The OpenStreetMap (OSM) Overpass API is a powerful tool that allows users to query and extract specific geographic data from the vast OpenStreetMap database. Unlike traditional map APIs that focus on rendering maps, Overpass is designed for retrieving raw geospatial data, making it especially useful for developers, researchers, and data analysts. With Overpass, users can filter and fetch details like place names, amenities, and exact geolocations, all without needing to download the entire OSM dataset. This makes it an efficient and flexible solution for anyone looking to work with location-based data in real time. One of the key advantages of using the Overpass API is its ability to execute highly customized queries using OverpassQL, a query language specifically designed for OSM data. For example, if you need a list of restaurants, hospitals, or public parks in a specific city, you can craft a simple query to return only the relevant points of interest along with their names and coordinates. This is particularly useful for applications like location-based services, urban planning, or geographic analysis. Since OpenStreetMap is constantly updated by a global community, the data you get is often more current and detailed than other proprietary mapping services, making Overpass an invaluable resource for working with open geospatial data.

The Code

By calling maps.extract_spatial, we extract specific geographic data from the vast OpenStreetMap database by create specific filter such as: boundary and amenity.

boundary= [47.46, 19.03, 47.53, 19.07]
amenity_list = [('amenity','cafe'), ('amenity','pub'),]

result = maps.extract_spatial(boundary, amenity_list= amenity_list, place_at='jakarta')

This function requires the following parameters:

• boundary (list): list of longitude and latitude.
• amenity_list (list): amenity list that we want to extract.
• place_at(string): specific location

The result