Mapping Canopy Heights of Poplar Plantations in Plain Areas Using ZY3-02 Stereo and Multispectral Data

Mingbo Liu,Wei Chen,Xuejun Wang,Chunxiang Cao

doi:10.3390/ijgi8030106

Abstract

Forest canopy height plays an important role in forest management and ecosystem modeling. There are a variety of techniques employed to map forest height using remote sensing data but it is still necessary to explore the use of new data and methods. In this study, we demonstrate an approach for mapping canopy heights of poplar plantations in plain areas through a combination of stereo and multispectral data from China’s latest civilian stereo mapping satellite ZY3-02. First, a digital surface model (DSM) was extracted using photogrammetry methods. Then, canopy samples and ground samples were selected through manual interpretation. Canopy height samples were obtained by calculating the DSM elevation differences between the canopy samples and ground samples. A regression model was used to correlate the reflectance of a ZY3-02 multispectral image with the canopy height samples, in which the red band and green band reflectance were selected as predictors. Finally, the model was extrapolated to the entire study area and a wall-to-wall forest canopy height map was obtained. The validation of the predicted canopy height map reported a coefficient of determination (R2) of 0.72 and a root mean square error (RMSE) of 1.58 m. This study demonstrates the capacity of ZY3-02 data for mapping the canopy height of pure plantations in plain areas.

Highlights

Forest canopy height is a critical parameter for forest management and ecosystem modeling
A variety of methods for mapping forest height using remote sensing data have been developed in recent years: the light detection and ranging (LiDAR) technique uses point cloud or waveform data from laser pulses to detect the vertical structure of a forest
It is expected that the application of spaceborne LiDAR in large-scale forest height mapping will be further developed when data from the ICESat-2 [10] and GEDI (Global Ecosystem Dynamics Investigation, a LiDAR system mounted on the International Space Station) [11] become available

Summary

Introduction

Forest canopy height is a critical parameter for forest management and ecosystem modeling. A variety of methods for mapping forest height using remote sensing data have been developed in recent years: the light detection and ranging (LiDAR) technique uses point cloud or waveform data from laser pulses to detect the vertical structure of a forest. The Geoscience Laser Altimeter System (GLAS) onboard NASA’s Ice, Cloud, and land Elevation Satellite (ICESat) collected data from 2003 to 2009. It offered an unprecedented opportunity for estimating forest height at a global scale [5]. It is expected that the application of spaceborne LiDAR in large-scale forest height mapping will be further developed when data from the ICESat-2 [10] and GEDI (Global Ecosystem Dynamics Investigation, a LiDAR system mounted on the International Space Station) [11] become available

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Conclusion