Title
Evaluating Remotely Sensed Phenological Metrics in a Dynamic Ecosystem Model
Abstract
Vegetation phenology plays an important role in regulating processes of terrestrial ecosystems. Dynamic ecosystem models (DEMs) require representation of phenology to simulate the exchange of matter and energy between the land and atmosphere. Location-specific parameterization with phenological observations can potentially improve the performance of phenological models embedded in DEMs. As ground-based phenological observations are limited, phenology derived from remote sensing can be used as an alternative to parameterize phenological models. It is important to evaluate to what extent remotely sensed phenological metrics are capturing the phenology observed on the ground. We evaluated six methods based on two vegetation indices (VIs) (i.e., Normalized Difference Vegetation Index and Enhanced Vegetation Index) for retrieving the phenology of temperate forest in the Agro-IBIS model. First, we compared the remotely sensed phenological metrics with observations at Harvard Forest and found that most of the methods have large biases regardless of the VI used. Only two methods for the leaf onset and one method for the leaf offset showed a moderate performance. When remotely sensed phenological metrics were used to parameterize phenological models, the bias is maintained, and errors propagate to predictions of gross primary productivity and net ecosystem production. Our results show that Agro-IBIS has different sensitivities to leaf onset and offset in terms of carbon assimilation, suggesting it might be better to examine the respective impact of leaf onset and offset rather than the overall impact of the growing season length.
Year
DOI
Venue
2014
10.3390/rs6064660
REMOTE SENSING
Keywords
Field
DocType
phenology,remote sensing,dynamic ecosystem model,Agro-IBIS,MODIS
Vegetation,Terrestrial ecosystem,Remote sensing,Normalized Difference Vegetation Index,Temperate forest,Enhanced vegetation index,Geology,Phenology,Ecosystem model,Ecosystem
Journal
Volume
Issue
Citations 
6
6
5
PageRank 
References 
Authors
0.65
0
3
Name
Order
Citations
PageRank
hong xu150.65
tracy e twine250.65
Xi Yang3515.53