visualizing large spatial/temporal data sets

Visualizing large spatial/temporal data sets

An example from the European MARS project

15 May 2013, Hendrik Boogaard

MARS project – Introduction

Monitoring Agricultural ReSources (MARS) Started early nineties, operational since 2000 Main objectives:

●Monitoring weather and crop conditions of current growing season (early warning, extreme events)

●Forecast crop yield in objective and timely manner In support of:

●European Common Agricultural Policy on commodities & subsidies (focus on Europe, Asia)

●Food aid (focus on Africa)

MARS project – Introduction

MARS project – Introduction

Operational services outsourced:●Provision weather data (stations, models)●Running and maintenance of agro-meteorological

models for Europe, Russia and Asia (CGMS) and global crop specific soil water balances

●Provision of satellite based vegetation indices and rainfall estimates

●Development and maintenance of MARS-viewers

MARS project – List of operational services

weather monitoring based on interpolated station data

Africarainfall estimates based on MSG and observed rainfallpan-Europeweather and vegetation indices based on MSG-SEVIRIpan-Europe and Horn of Africavegetation indices based on MODIS-250m sensorpan-Europevegetation indices based on METOP-AVHRR sensorglobalvegetation indices based on NOAA-AVHRR sensorglobalvegetation indices based on SPOT-VEGETATION sensorglobalcrop specific drought monitoringglobalweather monitoring based on ECMWF deterministic forecastpan-Europecrop yield forecast based on ECMWF ensemble modelspan-Europe and Asiacrop yield forecast based on ECMWF deterministic forecastpan-Europecrop yield forecast based on interpolated station datapan-Europecrop monitoring based on ECMWF ensemble modelspan-Europe and Asiacrop monitoring based on ECMWF deterministic forecastpan-Europecrop monitoring based on interpolated station datapan-Europeweather monitoring based on ECMWF ensemble modelspan-Europe and Asiaweather monitoring based on ECMWF deterministic forecastpan-Europe

MARS project – Variety of data sets

Large number of themes Different Regions Of Interest (ROIs) Different spatial resolutions

●grids, administrative regions, agro-ecological zones Different time resolutions: day, 10-day, month, year 9 TB of data stored in relational database (ORACLE)

Viewers

Viewers – Rich & flexible

Serving:●Analysts of European commission (bulletin mode)●Public e.g. universities (limited in data/features)

Online viewer to perform spatial and temporal analysis of data sets in a customized way:

●Large number data sets & indicators●Flexible period definition (on-the-fly)●Flexible region definition●Analysis types: current season, anomalies, way of

aggregation, similarity analysis (time series)

Viewers – Key functionality

Geo-linked multiple map windows Geo-linked graphs Spatial layers supporting labelling, masking Legend management Export of data and formatted maps/graphs (PDF, PNG) Favourite management (save current viewer windows

configuration for later re-use) Configuration of all chart layout settings Pre-configured graph templates for analysts

Viewers – Architecture & components

Client-server architecture, different components:●Client application (runs in Adobe Flash Player)

●RIA developed in Adobe Flex ●Application Server & WMS Server●Model Data Servers (or other apps)●Databases (data and GUI-settings)

Viewers - Architecture & components

Viewers – Application server & WMS Server

XML Communication between client and server Java servlets handle all requests to secured system parts Security check ensured at one place Geoserver (open source)

●Shape files on local hard disk of the server perform better than spatial data in the Oracle database

Viewers – GUI

User interface driven by configuration settings in DB New data / indicators / functions can be added on the fly User interface automatically changes without coding

Viewers – Model Data Servers

Respond to a request (URL) by returning data as either XML (polygon or point request) or XML + .png file (grid request)

Deliver faster thanOracle queries (through file andin-memory caching)

Viewers – Examples

Thanks for your attention!

www.marsop.info(get access after registration)