SUMMARY
Rainfall is one of climate elements that influence the spatial and temporal variation of plant cover in any region and, in particular, in the caatinga semiarid Northeast. Before this, there was a need to examine relations of seasonal rainfall in the semiarid region of the State of Pernambuco with classes of use and soil cover and changes in vegetation Index (NDVI) for Normalized Difference, using principal component analysis and remote sensing techniques, being these determinations the main goals of this work. Four images of the Thematic Mapper (TM) sensor, the satellite Landsat 5, dated 12/12/1991, 12/9/1996, 12/13/2003 and 11/27/2009, formed the experimental unit, whose variables were estimated using the algorithm Surface Energy Balance Algorithms for Land (SEBAL), in addition to the daily rainfall data of 1996 and 2009 and the series 1975 to 2010. The main results indicated that the amount and distribution of rain influenced on the surface temperature and the values of the indexes of reflection and NDVI, excelling by high recovery power plant, as the coverage that occurred in the year 1996, and expressed by the greatest value of NDVI. It is concluded that remote sensing techniques associated with those of main components were efficient to quantify the spatio-temporal variability of climate and vegetation index of the normalized difference of semiarid conditions.