EO‐1 Hyperion, ALI and Landsat 7 ETM+ Data Comparison for Estimating Forest Crown Closure and Leaf Area Index

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In this study, mixed coniferous forest crown closure (CC) and leaf area index (LAI) were measured at the Blodgett Forest Research Station, University of California at Berkeley, USA. Data from EO‐1 Hyperspectral Imager (Hyperion) and Advanced Land Imager (ALI) acquired on 9 October 2001, and from Landsat 7 Enhanced Thematic Mapper Plus (ETM+) on 25 October 2001 were used for estimation of CC and LAI. A total of 38 forest CC and LAI measurements were used in this correlation analysis. The analysis procedure consists of (1) atmospheric correction to retrieve surface reflectance from Hyperion, ALI and ETM+ data, (2) a total of 38 patches, corresponding to ground CC and LAI measurement plots, extracted from data from the three sensors, and (3) calculating univariate/multivariate correlation coefficient (R 2) and root mean square error (RMSE) using CC and LAI measurements and retrieved surface reflectance data of the three sensors. The experimental results indicate: (1) higher individual band correlations with CC and LAI appear in visible and short wave infrared (SWIR) regions due to spectral absorption features (pigments in visible and water and other biochemicals in SWIR); (2) based on ALI individual band wavelengths, the R 2/RMSE produced with Hyperion bands are all better than those with ALI, except ALI band 1, due to atmospheric scattering of Hyperion bands in the visible region; (3) based on ETM+ individual band wavelengths, Hyperion is better than ALI, which is better than ETM+, especially for the NIR band group of Hyperion; (4) based on spectral region, Hyperion, again, is better than ALI which is better than ETM+, and optimal results appear in the visible region for ALI and in SWIR for Hyperion; and (5) if considering just six bands or six features (six principal components) in estimating CC and LAI, optimal results are obtained with six bands selected from the 167 Hyperion bands. In general, for estimation of forest CC and LAI in this study, the Hyperion sensor has outperformed the ALI and ETM+ sensors, whereas ALI is better than ETM+. The best spectral region for Hyperion is SWIR, but for ALI and ETM+, the visible region should be considered instead.

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International Journal of Remote Sensing, v. 26, issue 3, p. 457-474