HR: 0800h
AN: B41A-0084    [Abstracts]
TI: Climate Related Vegetation Characteristics Derived From MODIS LAI and NDVI
AU: * Zhang, P
EM: zhping@crsa.bu.edu
AF: Depat of Geography, Boston University, 675 Commonwealth Avenue, Boston, MA 02215 United States
AU: Anderson, B
EM: brucea@bu.edu
AF: Depat of Geography, Boston University, 675 Commonwealth Avenue, Boston, MA 02215 United States
AU: Barlow, M
EM: mbarlow@aer.com
AF: Atmospheric and Oceanic Diagnostics, AER. Inc, 131 Hartwell Avenue , Lexington, MA 02421 United States
AU: Tan, B
EM: tanbin@crsa.bu.edu
AF: Depat of Geography, Boston University, 675 Commonwealth Avenue, Boston, MA 02215 United States
AU: Myneni, R
EM: rmyneni@bu.edu
AF: Depat of Geography, Boston University, 675 Commonwealth Avenue, Boston, MA 02215 United States
AB: MODIS-based Leaf Area Index (LAI) and Normalized Difference Vegetation Index (NDVI) are used to examine detailed information regarding growing season and total annual production across the globe. Overall, MODIS LAI has larger variability and demonstrates more information regarding the evolution and structure of the seasonal vegetation characteristics. In contrast, the NDVI saturates around 0.7 and tends to overestimate the length of the growing season in regions where it is already long. Next, a Climatic Impact Index (CII) is derived to provide additional information regarding the potential sensitivity of vegetation to changes in climatic variables by accounting for the length of growing season. By normalizing the growth rate to the biome-average growth rate, this index can identify fractional loss of annual production during a given month, as opposed to the absolute loss which may be strongly weighted by the overall growth rate for different ecosystems. Our index provides a quantitative framework for assessing the importance of the length of the growing-season in determining climatic vulnerability and highlights regions such as the Sahel, eastern Africa, and central southwest Asia, which are highly susceptible to climate-induced variability during their short but intense growing seasons. In the last part of the paper, we use the long time series AVHRR products as a substitute for the MODIS products, and test the temporal characteristics of the CII, which is termed the CVII (Climate-Variability Impact Index). Major drought events are well-captured by the CVII, suggesting potential use as a monitoring and evaluation tool. Furthermore, the strong positive correlation between the CVII and the Vegetation Condition Index (VCI) suggests that the CVII can quantitatively identify the effects of climatic variability upon vegetation activity. Finally, CVII is used to generate models to monitor and predict the crop production at different temporal and spatial scales. Overall, these results demonstrate that the LAI-based CVII can be applied as a possible monitoring tool in agriculture applications.
DE: 3322 Land/atmosphere interactions
DE: 1812 Drought
DE: 1620 Climate dynamics (3309)
DE: 1640 Remote sensing
SC: Biogeosciences [B]
MN: 2004 AGU Fall Meeting