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Article

Estimation of Grassland Canopy Height and Aboveground Biomass at the Quadrat Scale Using Unmanned Aerial Vehicle

1
School of Geographic Sciences, Nantong University, 999 Tongjing Road, Nantong 226007, China
2
State Key Laboratory of Cryospheric Sciences, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, 320 Donggang West Road, Lanzhou 730000, China
3
State Key Laboratory Breeding Base of Desertification and Aeolian Sand Disaster Combating, Gansu Desert Control Research Institute, 390 North Bank Road West, Lanzhou 730070, China
4
College of Geomatics and Geoinformation, Guilin University of Technology, 12 Jiangan Road, Guilin 541004, China
5
University of Chinese Academy Sciences, Beijing 100049, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(6), 851; https://doi.org/10.3390/rs10060851
Received: 13 April 2018 / Revised: 20 May 2018 / Accepted: 28 May 2018 / Published: 31 May 2018
Aboveground biomass is a key indicator of a grassland ecosystem. Accurate estimation from remote sensing is important for understanding the response of grasslands to climate change and disturbance at a large scale. However, the precision of remote sensing inversion is limited by a lack in the ground truth and scale mismatch with satellite data. In this study, we first tried to establish a grassland aboveground biomass estimation model at 1 m2 quadrat scale by conducting synchronous experiments of unmanned aerial vehicle (UAV) and field measurement in three different grassland ecosystems. Two flight modes (the new QUADRAT mode and the commonly used MOSAIC mode) were used to generate point clouds for further processing. Canopy height metrics of each quadrat were then calculated using the canopy height model (CHM). Correlation analysis showed that the mean of the canopy height model (CHM_mean) had a significant linear relationship with field height (R2 = 0.90, root mean square error (RMSE) = 19.79 cm, rRMSE = 16.5%, p < 0.001) and a logarithmic relationship with field aboveground biomass (R2 = 0.89, RMSE = 91.48 g/m2, rRMSE = 16.11%, p < 0.001). We concluded our study by conducting a preliminary application of estimation of the aboveground biomass at a plot scale by jointly using UAV and the constructed 1 m2 quadrat scale estimation model. Our results confirmed that UAV could be used to collect large quantities of ground truths and bridge the scales between ground truth and remote sensing pixels, which were helpful in improving the accuracy of remote sensing inversion of grassland aboveground biomass. View Full-Text
Keywords: vegetation height; grassland; aboveground biomass; UAV; canopy height model; structure from motion (SfM); FragMAP vegetation height; grassland; aboveground biomass; UAV; canopy height model; structure from motion (SfM); FragMAP
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MDPI and ACS Style

Zhang, H.; Sun, Y.; Chang, L.; Qin, Y.; Chen, J.; Qin, Y.; Du, J.; Yi, S.; Wang, Y. Estimation of Grassland Canopy Height and Aboveground Biomass at the Quadrat Scale Using Unmanned Aerial Vehicle. Remote Sens. 2018, 10, 851. https://doi.org/10.3390/rs10060851

AMA Style

Zhang H, Sun Y, Chang L, Qin Y, Chen J, Qin Y, Du J, Yi S, Wang Y. Estimation of Grassland Canopy Height and Aboveground Biomass at the Quadrat Scale Using Unmanned Aerial Vehicle. Remote Sensing. 2018; 10(6):851. https://doi.org/10.3390/rs10060851

Chicago/Turabian Style

Zhang, Huifang, Yi Sun, Li Chang, Yu Qin, Jianjun Chen, Yan Qin, Jiaxing Du, Shuhua Yi, and Yingli Wang. 2018. "Estimation of Grassland Canopy Height and Aboveground Biomass at the Quadrat Scale Using Unmanned Aerial Vehicle" Remote Sensing 10, no. 6: 851. https://doi.org/10.3390/rs10060851

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