Faculty Publications
Document Type
Article
Abstract
Vegetation is an important factor in global climatic variability and plays a key role in the complexinteractions between the land surface and the atmosphere. This study focuses on the spatial and temporalvariability of vegetation and its relationship with land–atmosphere interactions. The authors have analyzedthe vegetation water content (VegWC) from the Advanced Microwave Scanning Radiometer for EOS(AMSR-E), the leaf area index (LAI), the normalized difference vegetation index (NDVI), the land surfacetemperature (Ts), and the Moderate Resolution Imaging Spectroradiometer (MODIS). Three regions,which have climatically differing characteristics, have been selected: the North America Monsoon System(NAMS) region, the Southern Great Plains (SGP) region, and the Little River Watershed in Tifton,Georgia. Temporal analyses were performed by comparing satellite observations from 2003 and 2004. Theintroduction of the normalized vegetation water content (NVegWC) derived as the ratio of VegWC andLAI corresponding to the amount of water in individual leaves has been estimated and this yields significantcorrelation with NDVI and Ts. The analysis of the NVegWC–NDVI relationship in the above listed threeregions displays a negative exponential relation, and the Ts–NDVI relationship (TvX relationship) isinversely proportional. The correlation between these variables is higher in arid areas such as the NAMSregion, and becomes less correlated in the more humid and more vegetated regions such as the area ofeastern Georgia. A land-cover map is used to examine the influence of vegetation types on the vegetationbiophysical and surface temperature relationships. The regional distribution of vegetation reflects therelationship between the vegetation biological characteristics of water and the growing environment.
Publication Info
Published in Journal of Climate, Volume 20, 2007, pages 5593-5606.
Rights
Hong, S., Lakshmi, V., & Small, E. E. (2007). Relationship between vegetation biophysical properties and surface temperature using multisensor satellite data. Journal of Climate, 20, 5593-5606.