Spatial extrapolation has become a sine qua non and an ad hoc major research focus in applied ecology in the latter half 20^th century. Progressive innovations in data acquisition and processing technologies over the last few decades, especially in the fields of 3S (RS, GIS and GPS) and statistical modeling method, have greatly enhanced ecologists' capacity to face the challenge by enabling them to to describe patterns in nature over larger spatial scales and a greater level of details than ever before. Elaeocarpus japonicas (Japanese Elaeocarpus tree, JET) was selected for applying in the concurrent developed technology, such as ecological distribution modeling and ecological extrapolation. The GPS-located JET samples were introduced in a GIS for overlaying with five environmental layers (elevation, slope, aspect, terrain position and vegetation index derived from two-date SPOT-5 images) for ecological information extraction and model building. We created three sampling designs (SD), Tong-Feng samples for SD1, Kuan-Dau samples for SD2, and the merge of the two former datasets for SD3, according to watersheds, and the three SDs were used individually to test the extrapolation ability of predictive models. The results of the two-way extrapolation indicated it is hard to extend the predicted distribution patterns through different watersheds. The main reasons resulting in this outcome were the difference in microclimate and micro-terrain between these two watersheds. Consequently, the models built with SD3 were the more robust. The information of vegetation index in this study poorly improved the models, so we will adopt the hyperspectral data to overcome the shortage of the SPOT-5 images.