• 研究报告 •

### 基于几何光学模型的毛竹林郁闭度无人机遥感定量反演

1. (1浙江农林大学浙江省森林生态系统碳循环与固碳减排重点实验室, 浙江临安 311300; 2浙江农林大学环境与资源学院, 浙江临安 311300)
• 出版日期:2015-05-18 发布日期:2015-05-18

### Retrieval of crown closure of moso bamboo forest using unmanned aerial vehicle (UAV) remotely sensed imagery based on geometricoptical model.

WANG Cong1,2, DU Hua-qiang1,2, ZHOU Guo-mo1,2, XU Xiao-jun1,2, SUN Shao-bo1,2, GAO Guo-long1,2

1. (1Zhejiang Provincial Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration, Zhejiang A&F University, Lin’an 311300, Zhejiang, China; 2School of Environmental and Resources Science, Zhejiang A&F University, Lin’an 311300, Zhejiang, China)
• Online:2015-05-18 Published:2015-05-18

Abstract:

This research focused on the application of remotely sensed imagery from unmanned aerial vehicle (UAV) with high spatial resolution for the estimation of crown closure of moso bamboo forest based on the geometricoptical model, and analyzed the influence of unconstrained and fully constrained linear spectral mixture analysis (SMA) on the accuracy of the estimated results. The results demonstrated that the combination of UAV remotely sensed imagery and geometricoptical model could, to some degrees, achieve the estimation of crown closure. However, the different SMA methods led to significant differentiation in the estimation accuracy. Compared with unconstrained SMA, the fully constrained linear SMA method resulted in higher accuracy of the estimated values, with the coefficient of determination (R2) of 0.63 at    0.01 level, against the measured values acquired during the field survey. Root mean square error (RMSE) of approximate 0.04 was low, indicating that the usage of fully constrained linear SMA could bring about better results in crown closure estimation, which was closer to the actual condition in moso bamboo forest.