During the NSF's East Asia Pacific Summer Institutes (EAPSI) program, I worked with researchers at Chiba University to develop an improved method for automated mapping of forest types in Eastern Japan (tree plantations and natural broadleaf forest) using satellite imagery (ASTER imagery). The new method incorporates spatial information (using spatial interpolation) in addition to the spectral information of the different forest types to improve the accuracy of forest type maps. These forest type maps are useful for environmental, biological, climate, and economic studies, and the developed mapping methods will be useful for future land cover mapping studies in other natural environments. Results of this study were published in the journal "Remote Sensing Letters" (Johnson et al. 2012), and presented at the "Southeast Division of the Association of American Geographers" Annual conference (in Savannah, GA) as well as the "JSPS 2nd Annual Multidisciplinary Science Forum" (in Kalamazoo, MI). I had such a great experience in the EAPSI program that I decided to go back to work in Japan as a Postdoctoral Fellow at Chiba University's Center for Environmental Remote Sensing. Research Publication Johnson, B., Tateishi, R., Xie, Z. 2012. Using geographically-weighted variables for image classification. "Remote Sensing Letters 3 (6)", 491-499.