Estimation of canopy-average surface-specific leaf area using Landsat TM data

Specific leaf area (SLA) is an important ecological variable becauseof its links with plant ecophysiology and leaf biochemistry. Variations in SLA are associated with variations in leaf optical properties,and these changes in leaf optical properties have been found to result in changes in canopy reflectance. This paper utilizes these changes to explore the potential of estimating SLA using Landsat TM data. Fourteen sites with varying vegetation were sampled on the Lambert Peninsula in Ku-ring-gai Chase National Park to the north of Sydney, Australia. A sampling strategy that facilitated the calculation of canopy-average surface SLA (SLACS) was developed. The relationship betweenSLACS, reflectance in Landsat TM bands, and a number of vegetation indices, were explored using univariate regression. The observed relationships between SLACS and canopy reflectance are also discussed in terms of trends observed in a pre-existing leaf optical properties dataset (LOPEX 93). Field data indicate that there is a strong correlation between SLACS and red, near-infrared, and the second mid infrared bands of Landsat TM data. A strong correlation between SLACS and the following vegetation indices: Soil and Atmosphere Resistant Vegetation Index (SARVI2), Normalized Difference Vegetation Index (NDVI), and Ratio Vegetation Index (RVI), suggests that these vegetation indices could be used to estimate SLACS using Landsat TM data. [ABSTRACT FROM AUTHOR]