Hiromi Shiota
Graduate School of Kyoto Prefectural University, Japan
Biography
Hiromi Shiota has started his research for forestry management for 4 years after retirement from an IT vender. He is interested in Airborne Laser Scan of Remote Sensing technology. He is now trying to measure average tree height in wide area by using large size ALS data with Area Based Approach. To operate large data, for example, merge or divide data, change data format, or smoothing like these. He thinks, Fusion/LDV that developed by USDA is an excellent tool to analysis LiDAR data. However, he is 65 years old now, but he keeps studying with the will.
Abstract
Abstract : LiDAR data analysis with Fusion/LDV for individual tree measurement