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Umebayashi, T., Koga, S., Utsumi, Y., Inoue, S., Shiiba, Y., Nagasawa, H., Osaki, S., Kubota, K., Inoue, S., Junji, M. and Oda, K. (2011) Green Moisture Content and Basic Density of 95 Woody Species Growing in Kyushu University Forests, Japan. Bulletin of the Kyushu University Forests, 92, 33-44.

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• TITLE: Simple Relationship Analysis between L-Band Backscattering Intensity and the Stand Characteristics of Sugi (Cryptomeria japonica) and Hinoki (Chamaecyparis obtusa) Trees

  AUTHORS: Kotaro Iizuka, Ryutaro Tateishi

  KEYWORDS: SAR, ALOS/PALSAR, Forest, Backscattering, Stem Volume, Biophysical Parameter

  JOURNAL NAME: Advances in Remote Sensing, Vol.3 No.4, November 28, 2014

  ABSTRACT: In this study, we have performed an analysis between the L-band backscattering intensity derived from the slope corrected ALOS PALSAR remote sensing data and thein-situstand biophysical parameter of Sugi (Cryptomeria japonica) and Hinoki (Chamaecyparis obtusa) trees at the forests of Chiba Prefecture, Japan. Diameter at breast height (DBH), tree height, and stem volume were statistically compared with the slope corrected sigma naught backscattering in an empirical approach. It was found that the relationship between the backscattering and the stand characteristics was strongly dependent on species showing different trends between the Sugi and Hinoki trees.The Hinoki trees showed an increasing backscattering with increasing parameters (higher DBH, higher Tree height and higher stem volume), as it was mentioned on various researches, while the Sugi tree showed and decreasing backscattering with increasing parameters. Wehave also found for the Sugi trees that the backscattering is affected strongly by the number of stems. We have assumed that this is because of the characteristics of the Sugi trees which have high moisture content in the heartwood of the stem, compared with other tree species in Japan. The results pave the way to the possibility for estimating biophysical parameters within the forests of Japan by considering such trends and at highly rugged areas by using slope corrected imagery of the SAR data.