|Liang, S - UNIV OF MD COLLEGE PARK|
|Fang, H - UNIV OF MD COLLEGE PARK|
|Van Niel, T - CSIRO|
|Mcvicar, T - CSIRO|
|Huemmrich, F - UNIV OF MD BALTO CO|
Submitted to: IEEE Transactions on Geoscience and Remote Sensing
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: February 19, 2003
Publication Date: August 18, 2003
Citation: Liang, S., Fang, H., Kaul, M., Van Niel, T., Mc Vicar, T., Walthall, C.L., Daughtry, C.S., Huemmrich, F. 2003. Estimation of land surface broadband albedos and leaf area index from EO-I data and validation. IEEE Transactions on Geoscience and Remote Sensing. 41(6):1260-1267. Interpretive Summary: Maps of albedo and plant foliage density expressed as leaf area index (LAI) are needed for global and regional climate models, monitoring land surface changes and measuring the earth's energy balance. The Advanced Land Imager (ALI) incorporated into new satellite technology employed by the NASA Earth Observer-1 (EO-1) satellite, was assessed for its suitability for estimating albedo and LAI using new algorithms. The additional spectral bands of ALI beyond that of the current Landsat satellites, specifically one additional blue, and two additional near infrared bands, provide better estimates of broad band albedo and LAI than prior systems. The additional blue band also provides information that improves atmospheric haze removal from the imagery. A new procedure for estimating LAI that incorporates a hybrid approach using both a physical model and a non-linear regression via a neural network was shown to be very accurate based on comparisons with ground-based measurements in Maryland and Australia. The results justify the support the inclusion of the new spectral bands of EO-1 for future satellites and validate the new technology used on board EO-1.
Technical Abstract: The Advanced Land Imager (ALI) is a multispectral sensor onboard NASA Earth Observer-1 (EO-1). It has similar spatial resolution to the Landsat-7 Enhanced Thematic Mapper Plus (ETM+), with three additional spectral bands. We developed new algorithms for estimating both land surface broadband albedo and leaf area index (LAI) from ALI data. A recently developed atmospheric correction algorithm for ETM+ imagery was extended to retrieve surface spectral reflectance from ALI top-of-atmosphere observations. A feature common to these algorithms is the use of new multispectral information from ALI. The additional blue band of ALI is very useful for the atmospheric correction algorithm, and two additional ALI near-infrared bands are valuable for estimating both broadband albedo and LAI. Ground measurements at Beltsville, Maryland, USA and Coleambally, Australia were used to validate the products generated by the algorithms.