Customer

Assisting 80 million people in around 80 countries each year, the World Food Programme (WFP) is the leading humanitarian organization fighting hunger worldwide, delivering food assistance in emergencies and working with communities to improve nutrition and build resilience.

Challenge

In 2016, World Food Programme commissioned Brains Engineering to design and build a data visualization platform to share geographical big data analysis to the public. Remote sensing data, updated every ten days, is coming from the MODIS instrument (moderate-resolution imaging spectroradiometer) on board of the NASA satellites, Terra and Aqua.
Raster data must be processed, aggregated and geo-referenced in order to build a set of indicators to show an easy to understand set of data visualization.

Among the main challenges there were:

• Build a worldwide coverage geo-spatial database with high resolution data up to administrative level 2.
• Develop an API to provide geographical data in Geo-JSON format with simplified geometries.
• Bulk data upload service to upload the huge data files (up to 5GB each) to the database.
• Build a simple web data visualization platform, with a responsive UI, able to show this large amount of data even on mobile devices and reduced bandwidth.

Solution

interesting challenge in cartography is getting data of the appropriate resolution. As Lewis Fry Richardson observed, the more precisely you measure the length of a coastline, the longer it appears; geographic shapes have infinite complexity. Digital displays, in contrast, are limited by pixels. Choosing too high a resolution increases download time and slows rendering, while too low a resolution elides important detail.
We have decided to produce a custom script to process all the polygons with a two-pass process, applying first Douglas–Peucker and then Visvalingam’s algorithm in order to reduce the geometry complexity up to 90%.

The sensors data, coming from the raster process and stored into a csv file, can easily reach 5 GBs, therefore we have built an asynch interface with a SQL bulk data import in order to be able to upload it in few seconds to the database server.

The final step has been to design a simple but effective user interface to navigate the data and plot it on simple charts, using Twitter Bootstrap v3. For drawing the charts we have choosen KendoUI, as it offered the needed features, responsivness and high level of customization.

INFORMATION

Region: Worldwide

Industry: Non-Profit - Humanitarian

Type: Geo-Spatial and Web Mapping

Engagement model: Dedicated Team

Duration: 6 Months

Staff: 1 Project manager, 1 Geo-Spatial Data Analyst, 3 Developers and UX/UI experts

Development: Visual Studio, QGIS, SQL Server 2016 Enterprise, PostGIS

TECHNOLOGIES