| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 6348580 | International Journal of Applied Earth Observation and Geoinformation | 2015 | 10 Pages |
Abstract
In the present study, we aimed to map canopy heights in the Brazilian Amazon mainly on the basis of spaceborne LiDAR and cloud-free MODIS imagery with a new method (the Self-Organizing Relationships method) for spatial modeling of the LiDAR footprint. To evaluate the general versatility, we compared the created canopy height map with two different canopy height estimates on the basis of our original field study plots (799 plots located in eight study sites) and a previously developed canopy height map. The compared canopy height estimates were obtained by: (1) a stem diameter at breast height (D) - tree height (H) relationship specific to each site on the basis of our original field study, (2) a previously developed D-H model involving environmental and structural factors as explanatory variables (Feldpausch et al., 2011), and (3) a previously developed canopy height map derived from the spaceborne LiDAR data with different spatial modeling method and explanatory variables (Simard et al., 2011). As a result, our canopy height map successfully detected a spatial distribution pattern in canopy height estimates based on our original field study data (r = 0.845, p = 8.31 Ã 10â3) though our canopy height map showed a poor correlation (r = 0.563, p = 0.146) with the canopy height estimate based on a previously developed model by Feldpausch et al. (2011). We also confirmed that the created canopy height map showed a similar pattern with the previously developed canopy height map by Simard et al. (2011). It was concluded that the use of the spaceborne LiDAR data provides a sufficient accuracy in estimating the canopy height at regional scale.
Keywords
Related Topics
Physical Sciences and Engineering
Earth and Planetary Sciences
Computers in Earth Sciences
Authors
Yoshito Sawada, Rempei Suwa, Keiji Jindo, Takahiro Endo, Kazuo Oki, Haruo Sawada, Egidio Arai, Yosio Edemir Shimabukuro, Carlos Henrique Souza Celes, Moacir Alberto Assis Campos, Francisco Gasparetto Higuchi, Adriano José Nogueira Lima, Niro Higuchi,
