The sertao of northeast Brazil is a semiarid region characterized by recurring droughts. The vastness of the area (650,000 km$ sp2)$ poses a challenge to the effective monitoring of the impacts of drought at a scale that would be useful to the inhabitants of the sertao. Remote sensing data provide a viable way of assessing the extent and nature of drought across the landscape. / The work present a more effective algorithm to estimate rainfall from both the cold and warm cloud types present. Using a decision-tree methodology, the analysis yields rainfall estimates over the 0-21 mm range. Because seasonal variations in rainfall produce differences in vegetation, soils and hydrologic responses, Principal Components Analysis was used to examine these land surface responses. Individual components and component pairings were useful in identifying variations in vegetation density, geobotanical differences and drainage characteristics. The presence of cloud cover was found to dampen the land surface information that could be extracted. Landsat Thematic Mapper (TM) imagery was then used to produce a moisture index which characterizes surface wetness in relation to other features present in a scene. The multispectral combination of TM bands 1, 4 and 6 allowed for the separation of the surface types present, in locational space. This space was defined by an open-ended triange made up of a vertical "water line", a horizontal line of equal vegetation density; and a negatively-slopping iso-moisture line. The stability of the moisture index was influenced by varying scale and seasonal conditions. / In the drought conditions that prevailed in 1991-1992, these methods provide important additions to existing drought monitoring approaches in the Brazilian northeast. Further calibration is required in order to extend their applicability to other geographical regions and time frames.

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