Assessing the information content of multiangle satellite data for mapping biomes: I. Statistical analysis

The insights gained from present land cover classification activities suggest integration of multiangle data into classification attempts for future progress. Land cover types that exhibit distinct signatures in the space of remote sensing data facilitate unambiguous identification of cover types. In this first part, we develop a theme for consistency between cover type definitions, uniqueness of their signatures, and physics of the remote sensing data. The idea of angular signatures in spectral space is proposed to provide a cogent synthesis of information from spectral and angular domains. Three new metrics, angular signature slope (ASSI), length (ASLI), and intercept indices, are introduced to characterize biome signatures. The statistical analyses with these indices confirm the idea that incorporation of the directional variable should improve biome classification result. The consistency principle is tested with the Multiangle Imaging SpectroRadiometer (MISR) leaf area index (LAI) algorithm by examining retrievals when both unique and nonunique signatures are input together with a land cover map. It is shown that this requirement guarantees valid retrievals. Part II provides a theoretical basis for these concepts [Zhang et al., Remote Sens. Environ., in press.].