Derivation of a soil albedo dataset from MODIS using principal component analysis: Northern Africa and the Arabian Peninsula

Details Derivation of a soil albedo dataset from MODIS using principal component analysis: Northern Africa and the Arabian Peninsula Derivation of a soil albedo dataset from MODIS using principal component analysis: Northern Africa and the Arabian Peninsula

Nov 2005

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2005georl..3221407z&link_type=abstract

Geophysical Research Letters, Volume 32, Issue 21, CiteID L21407

Physics

1

Global Change: Climate Dynamics (0429, 3309), Global Change: Remote Sensing (1855), Atmospheric Processes: Boundary Layer Processes, Atmospheric Processes: Land/Atmosphere Interactions (1218, 1631, 1843), Atmospheric Processes: Global Climate Models (1626, 4928)

Scientific paper

This paper analyzes MODIS 1 km albedo kernels of 7 spectral bands over Northern Africa and the Arabian Peninsula and through these kernels develops a new high quality dataset that provides a simple statistical method to scale up spectral and broadband albedos from pixel to arbitrary coarse resolution grid square for use in climate models. This dataset significantly improves characterization of spatial and spectral variability and solar zenith angle dependence of soil albedo relative to simple grid means from MODIS data. The statistical method based on minimum noise fraction rotation transforms is able to not only successfully capture most of the MODIS albedo variance but also to extract large-scale spatial structures of albedo patterns from the original MODIS data while improving the data quality and reducing the number of parameters needed to represent the data.

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