- Title:
-
Fitting Ecological Knowledge to Remotely Sensed Long-term Monitoring Data: A framework from semi-arid grasslands of the Pilbara region of north-western Australia
- Date:
- August 2005
- Organisations
- Ecological Society of America
- Authors:
- Sadler, Rohan; Hazelton, Martin; Grierson, Pauline
-
Location:
-
USA,
United States of America
Overview
Remotely sensed data are fast being integrated into long-term ecological monitoring. In this context remote sensed data are used to detect
change in processes such as net primary productivity. However, can
remote sensed data say more about ecosystem functioning and enable us to predict future system responses to events such as fire and flood? This
paper describes methodology we are developing to fit ecological models
of space-time vegetation dynamics to a time series of remotely sensed
data. Our models produce an image of the spatial arrangement of
vegetation for a point in time, dependent on ecosystem events. Output
from our model is then compared to 'real' remotely sensed data by
applying image metrics. This approach allows for: (1) testing of
competing models of ecosystem processes; (2) exploration of possible
linkages and interactions between factors such as unpredictable fire and rainfall events; and, (3) estimation of hidden parameters in existing
autecological models that are not easily measurable in the field. Out
methodology has the potential to allow increasingly detailed models of
space-time vegetation dynamics to be applied, and can be used to relate
model predictions to real observed data.
