Abstract
The use of satellite-borne large-footprint LiDAR (light detection and ranging) systems allows for the acquisition of forest monitoring data. This paper mainly describes the design, use, operating principles, installation and data properties of the new Laser Vegetation Detecting Sensor (LVDS), a LiDAR system designed and developed at the Academy of Forest Inventory and Planning (AFIP) and the Beijing Institute of Telemetry (BIT). Data from LVDS were used to calculate the mean height of forest trees on sample plots using data collected in the Hunan province of China. The results show that the full waveform data obtained by LVDS has the ability to accurately characterize forest height. The mean absolute percentage error of mean forest height per plot in flat areas was 6.8%, with a mean absolute deviation of 0.78 m. The airborne LVDS system provides prototype data sets and a platform for instrument proof-of-concept studies for China’s Terrestrial Ecosystem Carbon Monitoring (TECM) mission, which is an Earth remote sensing satellite due for launch in 2020. The information produced by LVDS allows for forest structure studies with high accuracy and coverage of large areas.
Highlights
Forests play an important role in the ecosystem
In forested areas, we examined the relationship between light detection and ranging (LiDAR) height estimates and mean forest height based on ground plot data
The relationship does follow the 1:1 line, and there does not appear to be any systematic bias or heteroscedasticity. These results strongly suggest that the Laser Vegetation Detecting Sensor (LVDS) system performs as expected when measuring forest canopy height, and can be a valuable tool for monitoring both the status of and trends in forest cover in China and elsewhere
Summary
With the development of China’s economy, forest resource monitoring has become more and more important as pressures on forest resources have increased. Mean canopy height is an important parameter that reflects the vertical structure of forests [1,2], and is of great importance for the quantitative estimation of forest habitat extent [3], biomass quantity, and the area affected by landscape changes [4,5,6]. In traditional field-based forest surveys, ground measurements on inventory plots have been used to estimate mean forest height. Is this method time- and effort-consuming, and tree height collection is often unreliable, especially in areas where forests are dense or otherwise difficult to traverse. Traditional forest survey instruments cannot meet the need for low-cost, reliable forest canopy height information
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