Konferenzbeitrag
Identifying Significant Determinants for Canopy Development on an Alpine Test Site by means of Artificial Neural Networks
Vorschaubild nicht verfügbar
Volltext URI
Dokumententyp
Text/Conference Paper
Zusatzinformation
Datum
2002
Autor:innen
Zeitschriftentitel
ISSN der Zeitschrift
Bandtitel
Verlag
IGU/ISEP
Zusammenfassung
We develop a methodical approach to model structural canopy development (biomass, leaf area) of different grassland stands in the North Italian landscape. Classic punctual field measures are linked to temporal-spatial high-resolution remote sensing data using artificial neural networks in order to generate large-scale forecasts for canopy development. We find empirical evidence to support our claim that RGB (red, green, blue) colour values can contribute to a better understanding of canopy development over time and in space. We provide graphical and statistical measures to identify the form and the importance of influence factors on canopy development. This approach allows us to scale up the plot-level measurements to landscape-level measurements (e.g. from biomass data to a biomass map).