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  • 标题:Estimation of Forest Structural Parameters from LIDAR and SAR Data
  • 本地全文:下载
  • 作者:Z. Zhang ; W. Ni ; A. Fu
  • 期刊名称:ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
  • 印刷版ISSN:2194-9042
  • 电子版ISSN:2194-9050
  • 出版年度:2008
  • 卷号:XXXVII-B8
  • 页码:1121-1126
  • 出版社:Copernicus Publications
  • 摘要:Vegetation spatial structure including plant height, biomass, vertical and horizontal heterogeneity, is an important factor influencing the exchanges of matter and energy between landscape and atmosphere, and the biodiversity of ecosystems. Regional and global forest biomass and forest structure estimation is essential for understanding and monitoring ecosystem responses to human activities and climate change. Lidars with capabilities of recording the time-varying return signals provide vegetation height, ground surface height, and the vertical distribution of vegetated surfaces intercepted by laser pulses, while radar responds to the amount of water in a forest canopy, as well as its spatial structure. Large footprint lidar has been shown to be an effective technique for measuring forest canopy height, and biomass from space. Data from these sensors contain information relevant to different aspects of the biophysical properties of the vegetation canopy. Synergy of lidar's vertical profile sampling and radar's mapping capabilities provides new opportunity for regional and global mapping of forest structural parameters.Field sampling data, lidar data, PALSAR and InSAR data were obtained and processed in our study area in Changbai Mountain area, northeastern China. The capabilities for forest height and biomass estimation through combined use of lidar and radar data with lidar footprints scale were investigated. The results show that combined lidar and radar data improved the prediction accuracy by individual sensors, which was validated using field measurements and forest inventory data
  • 关键词:Forest structure; Lidar; Radar; GLAS; PALSAR
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