Jason B. Drake

Estimation of tropical forest structural characteristics using large-footprint lidar

Quantification of forest structure is important for developing a better understanding of how forest ecosystems function. Additionally, estimation of forest structural attributes, such as aboveground biomass (AGBM), is an important step in identifying the amount of carbon in terrestrial vegetation pools and is central to global carbon cycle studies. Although current remote sensing techniques recover such tropical forest structure poorly, new large-footprint lidar instruments show great promise. As part of a prelaunch validation plan for the Vegetation Canopy Lidar (VCL) mission, the Laser Vegetation Imaging Sensor (LVIS), a large-footprint airborne scanning lidar, was flown over the La Selva Biological Station, a tropical wet forest site in Costa Rica. The primary objective of this study was to test the ability of large-footprint lidar instruments to recover forest structural characteristics across a spectrum of land cover types from pasture to secondary and primary tropical forests. LVIS metrics were able to predict field-derived quadratic mean stem diameter (QMSD), basal area, and AGBM with R 2 values of up to .93, .72, and .93, respectively. These relationships were significant and nonasymptotic through the entire range of conditions sampled at the La Selva. Our results confirm the ability of large-footprint lidar instruments to estimate important structural attributes, including biomass in dense tropical forests, and when taken along with similar results from studies in temperate forests, strongly validate the VCL mission framework. D 2002 Elsevier Science Inc. All rights reserved.

Sensitivity of large-footprint lidar to canopy structure and biomass in a neotropical rainforest

Accurate estimates of the total biomass in terrestrial vegetation are important for carbon dynamics studies at a variety of scales. Although aboveground biomass is difficult to quantify over large areas using traditional techniques, lidar remote sensing holds great promise for biomass estimation because it directly measures components of canopy structure such as canopy height and the vertical distribution of intercepted canopy surfaces. In this study, our primary goal was to explore the sensitivity of lidar to differences in canopy structure and aboveground biomass in a dense, neotropical rainforest. We first examined the relationship between simple vertical canopy profiles derived from field measurements and the estimated aboveground biomass (EAGB) across a range of field plots located in primary and secondary tropical rainforest and in agroforesty areas. We found that metrics from field-derived vertical canopy profiles are highly correlated (R 2 up to .94) with EAGB across the entire range of conditions sampled. Next, we found that vertical canopy profiles from a large-footprint lidar instrument were closely related with coincident field profiles, and that metrics from both field and lidar profiles are highly correlated. As a result, metrics from lidar profiles are also highly correlated (R 2 up to .94) with EAGB across this neotropical landscape. These results help to explain the nature of the relationship between lidar data and EAGB, and also lay the foundation to explore the generality of the relationship between vertical canopy profiles and biomass in other tropical regions. D 2002 Elsevier Science Inc. All rights reserved.

BEYOND POTENTIAL VEGETATION: COMBINING LIDAR DATA AND A HEIGHT‐STRUCTURED MODEL FOR CARBON STUDIES

Carbon estimates from terrestrial ecosystem models are limited by large uncertainties in the current state of the land surface. Natural and anthropogenic disturbances have important and lasting influences on ecosystem structure and fluxes that can be difficult to detect or assess with conventional methods. In this study, we combined two recent advances in remote sensing and ecosystem modeling to improve model carbon stock and flux estimates at a tropical forest study site at La Selva, Costa Rica (10°25′ N, 84°00′ W). Airborne lidar remote sensing was used to measure spatial heterogeneity in the vertical structure of vegetation. The ecosystem demography model (ED) was used to estimate the consequences of this heterogeneity for regional estimates of carbon stocks and fluxes. Lidar data provided substantial constraints on model estimates of both carbon stocks and net carbon fluxes. Lidar-initialized ED estimates of aboveground biomass were within 1.2% of regression-based approaches, and corresponding model estimates of net carbon fluxes differed substantially from bracketing alternatives. The results of this study provide a promising illustration of the power of combining lidar data on vegetation height with a height-structured ecosystem model. Extending these analyses to larger scales will require the development of regional and global lidar data sets, and the continued development and application of height structured ecosystem models.

Multifractal analysis of canopy height measures in a longleaf pine savanna

Spatial patterns of forest canopies are fractal as they exhibit variation over a continuum of scales. A measure of fractal dimension of a forested landscape represents the spatial summation of physiologic (leaf-level), demographic (populationlevel), and abiotic (e.g., edaphic) processes, as well as exogenous disturbances (e.g., fire and hurricane) and thus provides a basis to classify or monitor such systems. However, forests typically exhibit a spectrum of fractal parameters which yields further insight to the geometric structure of the system and potentially the underlying processes. We calculated multifractal properties of longleaf pine flatwoods, the predominant ecosystem of central Florida, from canopy profile data derived from an airborne laser altimeter and ground-based measurements in The Nature Conservancy’s Disney Wilderness Preserve located near Kissimmee, Florida. These metrics were compared for six 500 m transects to determine the level of consistency between remotely sensed and field measures and within a forest community. Multifractal techniques uncovered subtle differences between transects that could correspond to unique, underlying abiotic and biotic processes. These techniques should be considered a valuable tool for ecological analysis. # 2000 Elsevier Science B.V. All rights reserved.

Simulating vertical and horizontal multifractal patterns of a longleaf pine savanna

Many ecological processes (e.g., individual growth, competition, and mortality) are dictated by existing spatial patterns and lead to the generation of new spatial conditions. Spatial patterns are the result of a spectrum of ecological processes operating at widely different time scales. In this study, a cellular automata model that incorporated autecological information for longleaf pine (LLP) and fire effects was used to simulate one- and two-dimensional spatial canopy/gap properties (i.e., the distribution of crown heights and widths) over a savanna landscape. These were quantified using multifractal analysis and were compared to remotely-sensed data from LLP stands from the Disney Wilderness Preserve located near Kissimmee, Florida. Lidar-derived transect information provided canopy height patterns and aerial photography provided crown width and horizontal distribution patterns. Multifractal spectra and size class distributions were found to be sensitive to spatially interactive parameters (i.e., competition, fire ignition and spread probabilities). Simulations with moderate levels of competition coupled with a relatively high fire frequency (once every 4 years) and a relatively high likelihood of fire spread across five-meter grid cells (dependent on litter fuel loads) were shown to create patterns that closely mimic the quasi three-dimensional remotely-sensed measures of this open canopy system.

Analysis of laser altimeter waveforms for forested ecosystems of Central Florida

An experimental profiling airborne laser altimeter system developed at NASAs Goddard Space Flight Center was used to acquire vertical canopy data from several ecosystem types from The Nature Conservancys Disney Wilderness Preserve, near Kissimmee, Florida. This laser altimeter, besides providing submeter accuracy of tree height, captures a profile of data which relates to the magnitude of reflectivity of the laser pulse as it penetrates different elevations of the forest canopy. This complete time varying amplitude of the return signal of the laser pulse, between the first (i.e., the canopy top) and last (i.e., the ground) returns, yields a waveform which is related to canopy architecture, specifically the nadir-projected vertical distribution of the surface of canopy components (i.e., foliage, twigs, and branches). Selected profile returns from representative covertypes (e.g., pine flatwoods, bayhead, and cypress wetland) were compared with ground truthed forest composition (i.e., species and size class distribution) and structural (i.e., canopy height, canopy closure, crown depth) measures to help understand how these properties contribute to variation in the altimeter waveform.

Portable and Airborne Small Footprint LiDAR: Forest Canopy Structure Estimation of Fire Managed Plots

This study used an affordable ground-based portable LiDAR system to provide an understanding of the structural differences between old-growth and secondary-growth Southeastern pine. It provided insight into the strengths and weaknesses in the structural determination of portable systems in contrast to airborne LiDAR systems. Portable LiDAR height profiles and derived metrics and indices (e.g., canopy cover, canopy height) were compared among plots with different fire frequency and fire season treatments within secondary forest and old growth plots. The treatments consisted of transitional season fire with four different return intervals: 1-yr, 2-yr, 3-yr fire return intervals, and fire suppressed plots. The remaining secondary plots were treated using a 2-yr late dormant season fire cycle. The old growth plots were treated using a 2-yr growing season fire cycle. Airborne and portable LiDAR derived canopy cover were consistent throughout the plots, with significantly higher canopy cover values found in 3-yr and fire suppressed plots. Portable LiDAR height profile and metrics presented a higher sensitivity in capturing subcanopy elements than the airborne system, particularly in dense canopy plots. The 3-dimensional structures of the secondary plots with varying fire return intervals were dramatically different to old-growth plots, where a symmetrical distribution with clear recruitment was visible. Portable LiDAR, even though limited to finer spatial scales and specific biases, is a low-cost investment with clear value for the management of forest canopy structure.