The Intergovernmental Panel on Climate Change (IPCC, Geneva, Switzerland) reports that climatic zoning requires new methodologies to discriminate homogeneous areas due to new scenarios generating global climatic change. The objective of this study was to perform climatic zoning by analyzing spatial and temporal variability of land surface temperature (LST) and the normalized difference vegetation index (NDVI). The 20-yr sequence of MODIS (LST and NDVI) images was analyzed by harmonic analysis, empirical orthogonal functions (EOFs), and continuous wavelet cross-correlation functions. Annual harmonic analysis identified agroclimatic zones from amplitude and phase, this result was valid for the two first EOF modes that account for 74% of the annual signal. Wavelet cross-correlations between the NDVI and LST temporal series showed a wideband high-power spectrum associated with the annual cycle. Finally, the methodologies applied to LST and NDVI images allowed the identification of agroclimatic zones. The study area included different dryland zones (coastal, interior, and foothill), irrigated valleys, and forests.