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Abstract

In central Amazonian white-water floodplains (varzea), different forest types become established in relation to the flood-level gradient. The formations are characterized by typical patterns of species composition, and their architecture results in different light reflectance patterns, which can be detected by Landsat TM image data. Ground checking comprised a detailed forest inventory of 4 ha, with Digital Elevation Models (DEM) being generated for all sites. The results indicate that, at the average flood level of 3 m, species diversity and architecture of the forests changes, thus justifying the classification into tile categories of low varzea (varzea baixa) and high varzea (varzea alta). In a first step to scale up, the study sites were observed by aerial photography. Tree heights, crown sizes, the projected crown area coverage and the gap frequencies provide information, which confirms a remotely sensed classification into three different forest types. The structure of low varzea depends on the successional stage, and species diversity increases with increasing age of the formations. In high varzea, only one successional stage was found and species diversity is higher than in all low-varzea formations. The more complex architecture of the high-varzea forest results in a more diffuse behaviour pattern in pixel distribution, when scanned by TM image data.