ArticleSensors (Basel, Switzerland)2017
Modeling Aboveground Biomass in Hulunber Grassland Ecosystem by Using Unmanned Aerial Vehicle Discrete Lidar.
Article in Sensors (Basel, Switzerland), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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14 citing papers in PubMed.
- UAV and Satellite Synergies for Mapping Grassland Aboveground Biomass in Hulunbuir Meadow Steppe.Plants (Basel, Switzerland) · 2024Article
- The Estimation of Grassland Aboveground Biomass and Analysis of Its Response to Climatic Factors Using a Random Forest Algorithm in Xinjiang, China.Plants (Basel, Switzerland) · 2024Article
- UAV Multisensory Data Fusion and Multi-Task Deep Learning for High-Throughput Maize Phenotyping.Sensors (Basel, Switzerland) · 2023Article
- Correction of UAV LiDAR-derived grassland canopy height based on scan angle.Frontiers in plant science · 2023Article
- Individual Tree Structural Parameter Extraction and Volume Table Creation Based on Near-Field LiDAR Data: A Case Study in a Subtropical Planted Forest.Sensors (Basel, Switzerland) · 2021Article
- Article
- Growth Indicators of Main Species Predict Aboveground Biomass of Population and Community on a Typical Steppe.Plants (Basel, Switzerland) · 2020Article
- Vegetation traits of pre-Alpine grasslands in southern Germany.Scientific data · 2020Article
- Detecting shrub encroachment in seminatural grasslands using UAS LiDAR.Ecology and evolution · 2020Article
- Non-destructive estimation of field maize biomass using terrestrial lidar: an evaluation from plot level to individual leaf level.Plant methods · 2020Article
- Estimating Grassland Carbon Stocks in Hulunber China, Using Landsat8 Oli Imagery and Regression Kriging.Sensors (Basel, Switzerland) · 2019Article
- Evaluating Soil-Borne Causes of Biomass Variability in Grassland by Remote and Proximal Sensing.Sensors (Basel, Switzerland) · 2019Article
- Combining Multi-Source Remotely Sensed Data and a Process-Based Model for Forest Aboveground Biomass Updating.Sensors (Basel, Switzerland) · 2017Article
- Article
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6 authors.
Funding
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Abstract
Accurate canopy structure datasets, including canopy height and fractional cover, are required to monitor aboveground biomass as well as to provide validation data for satellite remote sensing products. In this study, the ability of an unmanned aerial vehicle (UAV) discrete light detection and ranging (lidar) was investigated for modeling both the canopy height and fractional cover in Hulunber grassland ecosystem. The extracted mean canopy height, maximum canopy height, and fractional cover were used to estimate the aboveground biomass. The influences of flight height on lidar estimates were also analyzed. The main findings are: (1) the lidar-derived mean canopy height is the most reasonable predictor of aboveground biomass (
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