Classification of Simulated And Actual NOAA-6 AVHRR Data for Hydrologic Land-Surface Feature Definition

Current ground hydrology models (GHM´s) require global distribution of bare soil and vegetation, the physical and thermal properties of soil, and the physiological and physical properties of plants to parameterize evaporation and the sensible heat flux from the land surfaces. Thus the ability to infer vegetative cover, and to some extent vegetation type, is hydrologically important because of the relationship between vegetation and evapotranspiration through the process of root-zone soil-moisture extraction. LANDSAT digital data degraded to approximately 1 km and NOAA-6 digital data have been used to study the capability and problems associated with the use of low-resolution data to provide land-surface information such as forest, grassland, agriculture, bare, urban, and water. Three LANDSAT scenes and a subscene from a NOAA-6 pass were classified using supervised and unsupervised techniques. The LANDSAT data were used initially to study classification techniques and ascertain problems associated with large-scale classification prior to the receipt of NOAA-6 data. Comparisons between the LANDSAT supervised classification (¿ground truth¿) and the unsupervised classification resulted in percentage differences between the cover types of generally less than 10 percent. The Advanced Very Hign Resolution Radiometer (AVHRR) results were similar to the LANDSAT. In both cases there was no statistical difference between the supervised and unsupervised results. The major problem encountered was consistent labeling of the various landcover categories derived by the classification methods.