Estimation of tropical forest height and biomass dynamics using lidar remote sensing at La Selva, Costa Rica

Abstract

[1] In this paper we present the results of an experiment to measure forest structure and biomass dynamics over the tropical forests of La Selva Biological Station in Costa Rica using a medium resolution lidar. Our main objective was to observe changes in forest canopy height, related height metrics, and biomass, and from these map sources and sinks of carbon across the landscape. The Laser Vegetation Imaging Sensor (LVIS) measured canopy structure over La Selva in 1998 and again in 2005. Changes in waveform metrics were related to field-derived changes in estimated aboveground biomass from a series of old growth and secondary forest plots. Pairwise comparisons of nearly coincident lidar footprints between years showed canopy top height changes that coincided with expected changes based on land cover types. Old growth forests had a net loss in height of −0.33 m, while secondary forests had net gain of 2.08 m. Multiple linear regression was used to relate lidar metrics with biomass changes for combined old growth and secondary forest plots, giving an r 2 of 0.65 and an RSE of 10.5 Mg/ha, but both parametric and bootstrapped confidence intervals were wide, suggesting weaker model performance. The plot level relationships were then used to map biomass changes across La Selva using LVIS at a 1 ha scale. The spatial patterns of biomass changes matched expected patterns given the distribution of land cover types at La Selva, with secondary forests showing a gain of 25 Mg/ha and old growth forests showing little change (2 Mg/ha). Prediction intervals were calculated to assess uncertainty for each 1 ha cell to ascertain whether the data and methods used could confidently estimate the sign (source or sink) of the biomass changes. The resulting map showed most of the old growth areas as neutral (no net biomass change), with widely scattered and isolated sources and sinks. Secondary forests in contrast were mostly sinks or neutral, but were never sources. By quantifying both the magnitude of biomass changes and the sensitivity of lidar to detect them, this work will help inform the formulation of future space missions focused on biomass dynamics, such as NASA's Deformation Ecosystem Structure and Dynamics of Ice mission.

Quantifying Dynamics in Tropical Peat Swamp Forest Biomass with Multi-Temporal LiDAR Datasets

“…It is possible to detect small scale changes in the canopy height or AGB because height and intensity metrics have been proven to be reproducible [32,33]. For example, Dubayah et al [34] conducted a multi-temporal LiDAR study in Costa Rica and proved that old growth forests have a slower height growth rate (−0.33 m ± 4.09 m) compared to secondary forests (2.08 m ± 3.71 m) and accumulate therefore less biomass per hectare per year (0.3 t·ha −1 ·y −1 compared to 3.6 t·ha…”

Impacts of Airborne Lidar Pulse Density on Estimating Biomass Stocks and Changes in a Selectively Logged Tropical Forest

“…Airborne lidar is a technology well-suited to measure forest structure and estimate AGB stocks and changes in tropical forests (e.g., [8][9][10][11][12][13]). Lidar can provide high resolution, three-dimensional information on forest structure and the underlying topography [14,15].…”

National Forest Aboveground Biomass Mapping from ICESat/GLAS Data and MODIS Imagery in China

“…When the surface is covered by vegetation, echoes are a function of the vertical distribution of vegetation and the ground surface within a footprint. LiDAR data capture the horizontal and vertical structure of vegetation in great detail, resulting in accurate estimates of forest biomass across a broad range of forest types and biomes [30][31][32][33]. LiDAR systems acquire data either over small footprints (<1 m, point-cloud data, or waveform data, airborne) or large footprints (>10 m, waveform, either airborne or spaceborne) [34,35].…”