HOTOSM map-viz

Prototype for HOTOSM Outreachy project

Local development

• npm install
• browserify js/app.js > dist/bundle.js
• python -m http.server

How does it work?

relations ways nodes

• By default, time period is set for current date and current time
• Map area in view is by default taken to be the bounding box for the query
• Choose the right map view by navigating the map
• Choose in the time period, both start and end period
• On hitting Submit, all data changes, within a given time period, over a specific geographic area is obtained from OSM using overpass query. This is then rendered on map.

Approach

Objective is to view the edits made in a particular geography after a mapping event, something like Total number of buildings touched or Total kms of highways touched.

Data Extraction

This is like questioning OpenStreetMap on Hey, show me all the edits made in Bangalore today. This question can be put to OpenStreetMap in several ways.

1. Query OpenStreetMap directly from user interface using Export option
2. OpenStreetMap API
3. Use a third party tool like Overpass
4. Using planet/geofabrik/metro extracts and then write a script to extract specifc data from downloaded extracts

All the above options have their merits in different situations. Let's dig our question Hey, show me all the edits made in Bangalore today to understand which option is better.

This question has three parts to it:

1. all the edits - this is inclusive of all the feature types - buildings, highways. This part can be made very specific to say all building edits or all highway edits
2. edits made in Bangalore - question is specific to a place
3. edits made today - edits made from the start of the day to the current time.

All the three factors - kind of features edited, geography and timeframe are variable. We've to choose an option that could fit in these three factors.

Obvious choice is Overpass API. In general Overpass is great for:

• Querying features by OSM tags
• Looking for features that was edited within a time range
• Find features added by a particular user or group of users
• Querying rectangular bounding boxes and polygon boundaries

But before we go ahead, it's necessary to understand limitations to Overpass like:

• Complex queries fetching a large volume of data (>20MB) usually fails
• Queries that span a really large area of the map fails
• Queries that span a bigger timeframe also fails as it involves bulk data
• There's a cap on number of queries that could be sent to Overpass from a particular IP at a given time. If two people from the same Wi-fi network try to query Overpass, only one query is accepted, other automatically fails.

Implementing Data Extaction

Geography filter - Start with a rectangular bounding box form map view, that is get the bounds of the map from the current map view on the right pane. Use this bounds to construct a rectangular bbox This should be extended to accomodate any polygon boundary

  let bounds = map.getBounds()
  let north = bounds['_ne'].lat
  let east = bounds['_ne'].lng
  let south = bounds['_sw'].lat
  let west = bounds['_sw'].lng
  let bbox = south + ',' + west + ',' + north + ',' + east

Time filter - Provide two fields to gather start date and end date for the query. Default sets to today's timeframe.

Tag filter - Yet to be implemented

On hitting Fetch Data, overpass query is constructed on the fly. Eg:

https://www.overpass-api.de/api/interpreter?data=[out:xml][timeout:25];(node (changed:'2018-03-21T18:30:01.000Z','2018-03-22T06:25:14.000Z') (12.227550060708552,76.3482848025194,14.011214271757382,78.9857151974922));(way (changed:'2018-03-21T18:30:01.000Z','2018-03-22T06:25:14.000Z')(12.227550060708552,76.3482848025194,14.011214271757382,78.9857151974922));(rel (changed:'2018-03-21T18:30:01.000Z','2018-03-22T06:25:14.000Z') (12.227550060708552,76.3482848025194,14.011214271757382,78.9857151974922));out body;>;out body qt;

This is sent to the overpass API and the result is obtained in xml format. Other options include json and csv format. Whatever be the format, response data has to be processed further to get geojson data. From xml format, data is converted to geojson using [osmtogeojson](https://github.com/tyrasd/osmtogeojson) module.

Visualising data

Processed data is separated into three layers(node, way, relation) for map viz using mapbox-gl js and the count for each geometry is shown in the side bar.

relations ways nodes

This layering will change when tag filering comes into play.

View by geometry/feature - Each geometry type has a checkbox next to it. Based on what is checked, layers should display/disappear on the map