Error-aware spatio-temporal aggregation in the model web

Stasch C., Pebesma E., Graeler B., Gerharz L.

Forschungsartikel in Sammelband (Konferenz)

Zusammenfassung

Spatio-temporal aggregation of observed or predicted values for environmental phenomena is needed for fusing sensor data or coupling sensors and environmental models. However, estimates from sensors or environmental models can never represent our world precisely and are subject to errors. Hence, there is uncertainty in the estimates that needs to be considered in environmental model workflows. This chapter presents an approach for an error-aware spatio-temporal aggregation in the Web, where probabilistic uncertainties are used within a Monte Carlo simulation. The approach is applied in a Web-based model chain that provides uncertain crop yield predictions on field parcel level that are aggregated to larger regions.

Details zur Publikation

Herausgeber*innen:
Seiten: 18
Veröffentlichungsjahr: 2013
Verlag: Kluwer Academic Publishers
ISBN: 9783319006147
Sprache, in der die Publikation verfasst ist: Englisch
Link zum Volltext: http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84939635888&origin=inward