Academic Journal
Estimation of Forest Structural Attributes Using Spectral Indices and Point Clouds from UAS-Based Multispectral and RGB Imageries.
Title: | Estimation of Forest Structural Attributes Using Spectral Indices and Point Clouds from UAS-Based Multispectral and RGB Imageries. |
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Authors: | Shen, Xin, Cao, Lin, Yang, Bisheng, Xu, Zhong, Wang, Guibin |
Source: | Remote Sensing; Apr2019, Vol. 11 Issue 7, p800-800, 1p |
Abstract: | Forest structural attributes are key indicators for parameterization of forest growth models, which play key roles in understanding the biophysical processes and function of the forest ecosystem. In this study, UAS-based multispectral and RGB imageries were used to estimate forest structural attributes in planted subtropical forests. The point clouds were generated from multispectral and RGB imageries using the digital aerial photogrammetry (DAP) approach. Different suits of spectral and structural metrics (i.e., wide-band spectral indices and point cloud metrics) derived from multispectral and RGB imageries were compared and assessed. The selected spectral and structural metrics were used to fit partial least squares (PLS) regression models individually and in combination to estimate forest structural attributes (i.e., Lorey's mean height (H |
Subject Terms: | PARTIAL least squares regression, AERIAL photogrammetry, REMOTE sensing, PARAMETERIZATION, CLOUDS |
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ISSN: | 20724292 |
DOI: | 10.3390/rs11070800 |
Database: | Complementary Index |
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