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3 Methods

Vegetation classification and descriptions in the USGS land cover database are built on characteristics of vegetation seasonality determined in terms of AVHRR NDVI. In the database, unique NDVI signatures and associated attributes such as terrain and ecoregions characterise large-area land cover patterns. The magnitude of integrated NDVI over the length of the temporal period helped separate successively decreasing vegetation biomass, from healthy, dense forestlands to open woodland, shrub and grass, and sparse land cover. On the other hand, seasonal variations were investigated to partially support identification of vegetation physiognomy (e.g. separating deciduous from evergreen forests). The use of both integrated NDVI and seasonal NDVI variations has been found useful in applications such as monitoring large-area vegetation inter-annual variations (Reed et al. 1994) and mapping tropical deforestation and fragmentation (Skole and Tucker, 1993).

Because the USGS seasonal land cover database was not intended to optimize for forest cover, no direct relationship exits to enable a simple conversion of the seasonal land cover classes to the six FAO classes. Rather, a two-step methodology has been designed that allows certain interactive flexibility in deriving and correcting for the FAO classes.

To provide the least atmospherically affected result, final percent forest cover is determined over the course of the year based n the maximum monthly forest cover value achieved, regardless of the methods chosen (mixture analysis or scaled NDVI). Figure 1 illustrates the two techniques used in estimating percent forest cover. The selection of endmembers and determination of what pixels are bright or dark are based on studies of the imagery and vary between regions. This modeling process is used to guide decisions on the difficult or mixed seasonal classes from the first step. The modeling process determines the level of forest fragmentation if forest density is from the modified mixture analysis; whiles separation of various types of forest and woodland from other land cover is based on results from the linear NDVI scaling. Because of varying ecological conditions within and between continents, flexible regional rules are developed according to reference data in determining forest density threshold values for the FAO forest classes.

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