GIS Homework

GIS Homework.md

GIS Homework

Prepared by: @DenisCarriere

A few libraries to know about for doing Geospatial analysis using primarily OpenStreetMap Data & Vector Tiles.

• TurfJS
• Tile Reduce
• OSM QA Tiles
• Tippecanoe

TurfJS

TurfJS is an advance GeoSpatial analysis/computing library for the web (written ES5 Javascript).

• Simple: Modular, simple-to-understand JavaScript functions that speak GeoJSON
• Fast: Takes advantage of the newest algorithms and doesn't require you to send data to a server
• Modular: Turf is a collection of small modules. You can require just what you use with browserify

For example, a very powerful and utility module would be @turf/meta which allows you to iterate easily over your geospatial data:

• coordEach

Iterate over coordinates in any GeoJSON object, similar to Array.forEach()

• propEach

Iterate over properties in any GeoJSON object, similar to Array.forEach()

• featureEach

Iterate over features in any GeoJSON object, similar to Array.forEach.

• geomEach

Iterate over each geometry in any GeoJSON object, similar to Array.forEach()

• flattenEach

Iterate over flattened features in any GeoJSON object, similar to Array.forEach.

• segmentEach

Iterate over 2-vertex line segment in any GeoJSON object, similar to Array.forEach() (Multi)Point geometries do not contain segments therefore they are ignored during this operation.

• lineEach

Iterate over line or ring coordinates in LineString, Polygon, MultiLineString, MultiPolygon Features or Geometries, similar to Array.forEach.

$ npm install @turf/meta

import {coordEach, propEach} from '@turf/meta' // Using Babel or Typescript
// const {coordEach, propEach} = require('@turf/meta')

const dataset = {
  type: 'FeatureCollection',
  features: [
    {
      type: 'Feature',
      properties: { foo: 'bar' },
      geometry: { type: 'Point', coordinates: [10, 10] }
    },
    {
      type: 'Feature',
      properties: { hello: 'world' },
      geometry: { type: 'Point', coordinates: [20, 50] }
    }
  ]
}

coordEach(dataset, coord => {
  //= [10, 10]
  //= [20, 50]
})

propEach(dataset, properties => {
  //= { foo: 'bar' }
  //= { hello: 'world' }
})

For all updates on releases, check out the release GitHub tag.

Tile Reduce

TileReduce is a geoprocessing library that implements MapReduce to let you run scalable distributed spatial analysis using JavaScript and Mapbox Vector Tiles. TileReduce coordinates tasks across all available processors on a machine, so your analysis runs lightning fast.

OSM QA Tiles

OpenStreetMap data as Mapbox Vector Tiles in an MBTiles file for data analysis.

Includes:

• (almost) unsimplified geometries
• all OpenStreetMap tags
• additional properties like changeset, time, and user ids
• zoom 12
• no buffer around individual tiles

Tippecanoe

Build vector tilesets from large collections of GeoJSON features.

Examples using all platforms

Cross Street Indexer

Blazing fast tile based geocoder that matches cross street (road intersections) entirely sourced by OSM QA Tiles.