ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume IV-4/W2
https://doi.org/10.5194/isprs-annals-IV-4-W2-3-2017
https://doi.org/10.5194/isprs-annals-IV-4-W2-3-2017
19 Oct 2017
 | 19 Oct 2017

CANOPY SURFACE RECONSTRUCTION AND TROPICAL FOREST PARAMETERS PREDICTION FROM AIRBORNE LASER SCANNER FOR LARGE FOREST AREA

Z. Chen, Z. Yang, Y. Chen, C. Wang, J. Qian, Q. Yang, X. Chen, and J. Lei

Keywords: Canopy Height Model, CHM, LiDAR, Tree Mean Height

Abstract. Canopy height model(CHM) and tree mean height are critical forestry parameters that many other parameters such as growth, carbon sequestration, standing timber volume, and biomass can be derived from. LiDAR is a new method used to rapidly estimate these parameters over large areas. The estimation of these parameters has been derived successfully from CHM. However, a number of challenges limit the accurate retrieval of tree height and crowns, especially in tropical forest area. In this study, an improved canopy estimation model is proposed based on dynamic moving window that applied on LiDAR point cloud data. DEM, DSM and CHM of large tropical forest area can be derived from LiDAR data effectively and efficiently.