Understanding the relationship between vegetation and climate is the premise and foundation to reveal the distribution pattern of vegetation in large areas. Normalized Differentiation Vegetation Index (NDVI) has been regarded as an effective indicator for vegetation growth and distribution, especially for the large scope. To establish the accurate relationship between NDVI and climatic factors, this paper, based on the vegetation index product (MOD13Q1) relating to the Loess Plateau Area, northern China, and the climatic data observed in resent 50 years from the same area, has conducted a comparison between the two models named Geographically Weighted Regression, GWR, and Ordinary Least Squares, OLS, respectively. We analyzed the non-stationarity and scale-dependent characteristics between the two models with validation tool of corrected Akaike's Information Criterion, AICc, and calculated Moran's Index. The results showed: (1) the NDVI and the climatic factors had a strong scale-dependent relationship in the study area, and when the bandwidth approached to about 330 km in scale, they came up to a stable status. The annual mean precipitation, AMP, presented a larger fluctuation than the annual mean temperature, AMT, at the same scale of bandwidth. (2) Compared with OLS, the results of GWR showed a more accurate spatial distribution of vegetation, through validation by its model performance (AICc, R~2, R~2 adjusted) and Moran's Index of residuals (P<0.01). (3) The predicated result of GWR reflected the heterogeneity to some extent between the NDVI and the climatic factors. Precipitation had direct and positive influence on NDVI, whereas that of temperature was complicated. (4) The northeastern to southwestern distribution pattern between the NDVI and the climatic factors indicated a remarkable difference of climate- vegetation distribution pattern within the Loess Plateau. The heterogeneity between them also showed that some other factors such as human activities and/or orographic rains exerted influence on NDVI.