The National Weather Service is developing several geospatial forecast visualization and analysis tools. The back end data store and WMS server is built on Open Source GIS tools: GDAL, PostGIS / Raster, Mapserver, and Mapcache.
Weather forecasts are in a constant state of flux. In the case of the National Digital Forecast Database, forecasts expire or are superseded every hour. This presents several challenges when it comes to managing forecast rasters with GIS tools, and delivering the most up-to-date, real-time forecasts with an acceptable level of performance. This presentation will examine the methods and practices weve used to optimize our data store performance, from data ingest to forecast analysis to image delivery.
* Using PostgreSQL Inheritance / Parent and Child tables to manage raster updates inside the database
* Managing an up-to-date image cache in Mapcache and Memcached, with rapidly changing source data.
* Optimizing PostGIS raster tiles and Mapserver DATA queries for faster image generation and display over Google Maps
* Future work: Expanding PostgreSQL Inheritance to work with raster overviews