Narrowband to Broadband Conversion with Spatially Autocorrelated Reflectance Measurements
Open Access
- 1 May 1992
- journal article
- Published by American Meteorological Society in Journal of Applied Meteorology and Climatology
- Vol. 31 (5) , 421-432
- https://doi.org/10.1175/1520-0450(1992)031<0421:ntbcws>2.0.co;2
Abstract
A new technique for estimating broadband reflectance from Advanced Very High-Resolution Radiometer (AVHRR) narrowband reflectances in channel 1 and 2 is developed. The data used are simultaneous and coincident narrowband and broadband measurements made by the AVHRR and Earth Radiation Budget Experiment (ERBE) radiometers aboard NOAA-9 during four days in July 1985 in the region north of 60°N. The limitations and inefficiency of classical regressional methods when applied to datasets with high spatial auto-correlation, which is often the case for remotely sensed data, are discussed. A statistical variable, Moran's I, is introduced, which is specifically designed for testing against a null hypothesis of spatial independence. On the basis of Moran's I and a correlogram analysis of the spatial autocorrelation of measured reflectances, the data are sampled to provide a spatially independent dataset. In addition to sampling, the data are also screened with respect to spatial homogeneity. Both scene-dep... Abstract A new technique for estimating broadband reflectance from Advanced Very High-Resolution Radiometer (AVHRR) narrowband reflectances in channel 1 and 2 is developed. The data used are simultaneous and coincident narrowband and broadband measurements made by the AVHRR and Earth Radiation Budget Experiment (ERBE) radiometers aboard NOAA-9 during four days in July 1985 in the region north of 60°N. The limitations and inefficiency of classical regressional methods when applied to datasets with high spatial auto-correlation, which is often the case for remotely sensed data, are discussed. A statistical variable, Moran's I, is introduced, which is specifically designed for testing against a null hypothesis of spatial independence. On the basis of Moran's I and a correlogram analysis of the spatial autocorrelation of measured reflectances, the data are sampled to provide a spatially independent dataset. In addition to sampling, the data are also screened with respect to spatial homogeneity. Both scene-dep...Keywords
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