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Abstract
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.
Highlights
Grassland ecosystems are an important component of natural ecosystems, accounting for 15% of Earth’s surface area [1]
Synchronous experiments of unmanned aerial vehicle (UAV) and field sampling were conducted at three study sitesIntotehxisplsotruedtyh,esfyenascihbriolintyouofs ienxvpeertriinmgetnhtes coafnUopAyVheaingdhtfaienldd asbaomvpeglirnogunwdebreiocmoansdsuocftegdraasstlathnrdeeat sqtuudaydrsaittesscatloe efrxopmloUreAtVheimfeaagseibs.ility of inverting the canopy height and aboveground biomass of grassland at quadrat scale from UAV images
Based on the acquired UAV images, point clouds and canopy height model (CHM) metrics of each quadrat were calculated by using structure from motion (SfM) and CHM algorithms to explore the relationships between CHM metrics and field measurements
Summary
Grassland ecosystems are an important component of natural ecosystems, accounting for 15% of Earth’s surface area [1]. They provide food and habitat for herbivores [2], and play an important role in environmental protection, such as water conservation, sand fixation, and soil conservation [3,4]. Grassland ecosystems play a critical role in the global carbon cycle and in climate regulation [5,6]. Biomass is one of the important indicators for evaluating grassland ecosystems. Variable biomass-climatic relationships exist within different grassland ecosystems [8,9,10]. An accurate estimation of grassland biomass would significantly increase our understanding of the response of grasslands to climate change and disturbance, and the coupling mechanism of grassland ecosystems and climate change
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