Search NASA⌕ Search

Engineering topics

Dubayah, Ralph

Publications and source records attributed to Dubayah, Ralph.

18 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Ecosystem Science with NISAR: Final Preparations in The Pre-Launch Period

The NISAR mission which in its most recent round of launch preparations was set to launch in the spring of 2024, and now delayed until later in the fall or early spring of 2025, will serve as an unprecedented resource for the Remote Sensing of Ecosystems Science community. The two frequency, L- and S-band will full-polarimetric capability over a 250 km wide swath using the SweepSAR technique [1] will collect reliable set of observations (60 per year; 30 each for ascending and descending passes) on a continuing basis that will allow for the modeling and observation of time-varying processes that are prevalent in the living environment broadly described as Ecosystems. Among the prime science goals of the NISAR Ecosystems disciplines are in the characterization of agriculture, disturbance, biomass, forest structure and water dynamics seen in the world’s rivers, coasts, and permafrost regions. In this paper we provide an overview of the Ecosystem science that will be enabled by the NISAR mission and give a status of the basic algorithms that are being used to provide a basic set of tools to the community to make use of the data that NISAR will provide.

Siqueira, Paul↗
NASA NTRS2020

The Global Ecosystem Dynamics Investigation: High-Resolution Laser Ranging of the Earth’s Forests and Topography

Obtaining accurate and widespread measurements of the vertical structure of the Earth’s forests has been a longsought goal for the ecological community. Such observations are critical for accurately assessing the existing biomass of forests, and how changes in this biomass caused by human activities or variations in climate may impact atmospheric CO2 concentrations. Additionally, the three-dimensional structure of forests is a key component of habitat quality and biodiversity at local to regional scales. The Global Ecosystem Dynamics Investigation (GEDI) was launched to the International Space Station in late 2018 to provide high-quality measurements of forest vertical structure in temperate and tropical forests between 51.6 N & S latitude. The GEDI instrument is a geodetic-class laser altimeter/waveform lidar comprised of 3 lasers that produce 8 transects of structural information. Over its two-year nominal lifetime GEDI is anticipated to provide over 10 billion waveforms at a footprint resolution of 25 m. These data will be used to derive a variety of footprint and gridded products, including canopy height, canopy foliar profiles, Leaf Area Index (LAI), sub-canopy topography and biomass. Additionally, data from GEDI are used to demonstrate the efficacy of its measurements for prognostic ecosystem modeling, habit and biodiversity studies, and for fusion using radar and other remote sensing instruments. GEDI science and technology are unique: no other space-based mission has been created that is specifically optimized for retrieving vegetation vertical structure. As such, GEDI promises to advance our understanding of the importance of canopy vertical variations within an ecological paradigm based on structure, composition and function.

Dubayah, Ralph↗
NASA NTRS2018

Quantifying Long-Term Changes in Carbon Stocks and Forest Structure from Amazon Forest Degradation

Despite sustained declines in Amazon deforestation, forest degradation from logging and firecontinues to threaten carbon stocks, habitat, and biodiversity in frontier forests along the Amazon arcof deforestation. Limited data on the magnitude of carbon losses and rates of carbon recoveryfollowing forest degradation have hindered carbon accounting efforts and contributed to incompletenational reporting to reduce emissions from deforestation and forest degradation (REDD+). Wecombined annual time series of Landsat imagery and high-density airborne lidar data to characterizethe variability, magnitude, and persistence of Amazon forest degradation impacts on abovegroundcarbon density (ACD) and canopy structure. On average, degraded forests contained 45.1% of thecarbon stocks in intact forests, and differences persisted even after 15 years of regrowth. Incomparison to logging, understory fires resulted in the largest and longest-lasting differences in ACD.Heterogeneity in burned forest structure varied by fire severity and frequency. Forests with a historyof one, two, and three or more fires retained only 54.4%, 25.2%, and 7.6% of intact ACD,respectively, when measured after a year of regrowth. Unlike the additive impact of successive fires,selective logging before burning did not explain additional variability in modeled ACD loss andrecovery of burned forests. Airborne lidar also provides quantitative measures of habitat structure thatcan aid the estimation of co-benefits of avoided degradation. Notably, forest carbon stocks recoveredfaster than attributes of canopy structure that are critical for biodiversity in tropical forests, includingthe abundance of tall trees. We provide the first comprehensive look-up table of emissions factors forspecific degradation pathways at standard reporting intervals in the Amazon. Estimated carbon lossand recovery trajectories provide an important foundation for assessing the long-term contributionsfrom forest degradation to regional carbon cycling and advance our understanding of the currentstate of frontier forests.

Rappaport, Danielle I.↗
NASA NTRS2017

Disturbance Distance: Quantifying Forests' Vulnerability to Disturbance Under Current and Future Conditions

Disturbances, both natural and anthropogenic, are critical determinants of forest structure, function, and distribution. The vulnerability of forests to potential changes in disturbance rates remains largely unknown. Here, we developed a framework for quantifying and mapping the vulnerability of forests to changes in disturbance rates. By comparing recent estimates of observed forest disturbance rates over a sample of contiguous US forests to modeled rates of disturbance resulting in forest loss, a novel index of vulnerability, Disturbance Distance, was produced. Sample results indicate that 20% of current US forestland could be lost if disturbance rates were to double, with southwestern forests showing highest vulnerability. Under a future climate scenario, the majority of US forests showed capabilities of withstanding higher rates of disturbance then under the current climate scenario, which may buffer some impacts of intensified forest disturbance.

Dolan, Katelyn A.↗
NASA NTRS2013

Characterization of Canopy Layering in Forested Ecosystems Using Full Waveform Lidar

Canopy structure, the vertical distribution of canopy material, is an important element of forest ecosystem dynamics and habitat preference. Although vertical stratification, or "canopy layering," is a basic characterization of canopy structure for research and forest management, it is difficult to quantify at landscape scales. In this paper we describe canopy structure and develop methodologies to map forest vertical stratification in a mixed temperate forest using full-waveform lidar. Two definitions-one categorical and one continuous-are used to map canopy layering over Hubbard Brook Experimental Forest, New Hampshire with lidar data collected in 2009 by NASA's Laser Vegetation Imaging Sensor (LVIS). The two resulting canopy layering datasets describe variation of canopy layering throughout the forest and show that layering varies with terrain elevation and canopy height. This information should provide increased understanding of vertical structure variability and aid habitat characterization and other forest management activities.

lidar↗
NASA NTRS2012

Retrieval of Vertical LAI Profiles Over Tropical Rain Forests using Waveform Lidar at La Selva, Costa Rica

This study explores the potential of waveform lidar in mapping the vertical and spatial distributions of leaf area index (LAI) over the tropical rain forest of La Selva Biological Station in Costa Rica. Vertical profiles of LAI were derived at 0.3 m height intervals from the Laser Vegetation Imaging Sensor (LVIS) data using the Geometric Optical and Radiative Transfer (GORT) model. Cumulative LAI profiles obtained from LVIS were validated with data from 55 ground to canopy vertical transects using a modular field tower to destructively sample all vegetation. Our results showed moderate agreement between lidar and field derived LAI (r2=0.42, RMSE=1.91, bias=−0.32), which further improved when differences between lidar and tower footprint scales (r2=0.50, RMSE=1.79, bias=0.27) and distance of field tower from lidar footprint center (r2=0.63, RMSE=1.36, bias=0.0) were accounted for. Next, we mapped the spatial distribution of total LAI across the landscape and analyzed LAI variations over different land cover types. Mean values of total LAI were 1.74, 5.20, 5.41 and 5.62 over open pasture, secondary forests, regeneration forests after selective-logging and old-growth forests respectively. Lastly, we evaluated the sensitivities of our LAI retrieval model to variations in canopy/ground reflectance ratio and to waveform noise such as induced by topographic slopes. We found for both, that the effects were not significant for moderate LAI values (about 4). However model derivations of LAI might be inaccurate in areas of high-slope and high LAI (about 8) if ground return energies are low. This research suggests that large footprint waveform lidar can provide accurate vertical LAI profile estimates that do not saturate even at the high LAI levels in tropical rain forests and may be a useful tool for understanding the light transmittance within these canopies.

Tang, Hao↗
NASA NTRS2012

Characterizing 3D Vegetation Structure from Space: Mission Requirements

Human and natural forces are rapidly modifying the global distribution and structure of terrestrial ecosystems on which all of life depends, altering the global carbon cycle, affecting our climate now and for the foreseeable future, causing steep reductions in species diversity, and endangering Earth s sustainability. To understand changes and trends in terrestrial ecosystems and their functioning as carbon sources and sinks, and to characterize the impact of their changes on climate, habitat and biodiversity, new space assets are urgently needed to produce high spatial resolution global maps of the three-dimensional (3D) structure of vegetation, its biomass above ground, the carbon stored within and the implications for atmospheric green house gas concentrations and climate. These needs were articulated in a 2007 National Research Council (NRC) report (NRC, 2007) recommending a new satellite mission, DESDynI, carrying an L-band Polarized Synthetic Aperture Radar (Pol-SAR) and a multi-beam lidar (Light RAnging And Detection) operating at 1064 nm. The objectives of this paper are to articulate the importance of these new, multi-year, 3D vegetation structure and biomass measurements, to briefly review the feasibility of radar and lidar remote sensing technology to meet these requirements, to define the data products and measurement requirements, and to consider implications of mission durations. The paper addresses these objectives by synthesizing research results and other input from a broad community of terrestrial ecology, carbon cycle, and remote sensing scientists and working groups. We conclude that: (1) current global biomass and 3-D vegetation structure information is unsuitable for both science and management and policy. The only existing global datasets of biomass are approximations based on combining land cover type and representative carbon values, instead of measurements of actual biomass. Current measurement attempts based on radar and multispectral data have low explanatory power outside low biomass areas. There is no current capability for repeatable disturbance and regrowth estimates. (2) The science and policy needs for information on vegetation 3D structure can be successfully addressed by a mission capable of producing (i) a first global inventory of forest biomass with a spatial resolution 1km or finer and unprecedented accuracy (ii) annual global disturbance maps at a spatial resolution of 1 ha with subsequent biomass accumulation rates at resolutions of 1km or finer, and (iii) transects of vertical and horizontal forest structure with 30 m along-transect measurements globally at 25 m spatial resolution, essential for habitat characterization. We also show from the literature that lidar profile samples together with wall-to53 wall L-band quad-pol-SAR imagery and ecosystem dynamics models can work together to satisfy these vegetation 3D structure and biomass measurement requirements. Finally we argue that the technology readiness levels of combined pol-SAR and lidar instruments are adequate for space flight. Remaining to be worked out, are the particulars of a lidar/pol-SAR mission design that is feasible and at a minimum satisfies the information and measurement requirement articulated herein.

Hall, Forrest G.↗
NASA NTRS2011

Mapping Canopy Damage from Understory Fires in Amazon Forests Using Annual Time Series of Landsat and MODIS Data

Understory fires in Amazon forests alter forest structure, species composition, and the likelihood of future disturbance. The annual extent of fire-damaged forest in Amazonia remains uncertain due to difficulties in separating burning from other types of forest damage in satellite data. We developed a new approach, the Burn Damage and Recovery (BDR) algorithm, to identify fire-related canopy damages using spatial and spectral information from multi-year time series of satellite data. The BDR approach identifies understory fires in intact and logged Amazon forests based on the reduction and recovery of live canopy cover in the years following fire damages and the size and shape of individual understory burn scars. The BDR algorithm was applied to time series of Landsat (1997-2004) and MODIS (2000-2005) data covering one Landsat scene (path/row 226/068) in southern Amazonia and the results were compared to field observations, image-derived burn scars, and independent data on selective logging and deforestation. Landsat resolution was essential for detection of burn scars less than 50 ha, yet these small burns contributed only 12% of all burned forest detected during 1997-2002. MODIS data were suitable for mapping medium (50-500 ha) and large (greater than 500 ha) burn scars that accounted for the majority of all fire-damaged forest in this study. Therefore, moderate resolution satellite data may be suitable to provide estimates of the extent of fire-damaged Amazon forest at a regional scale. In the study region, Landsat-based understory fire damages in 1999 (1508 square kilometers) were an order of magnitude higher than during the 1997-1998 El Nino event (124 square kilometers and 39 square kilometers, respectively), suggesting a different link between climate and understory fires than previously reported for other Amazon regions. The results in this study illustrate the potential to address critical questions concerning climate and fire risk in Amazon forests by applying the BDR algorithm over larger areas and longer image time series.

Morton, Douglas C.↗
NASA NTRS2000

Primary and Secondary Controls on Measurements of Forest Height Using Large-Footprint Lidar at the Hubbard Brook LTER

On September 26, 1999, we mapped canopy structure over 90% of the Hubbard Brook Experimental Forest in White Mountain National Forest, New Hampshire, using the Laser Vegetation Imaging Sensor (LVIS). This airborne instrument was configured to emulate data expected from the Vegetation Canopy Lidar (VCL) space mission. We compared above ground heights of the tallest surfaces detected by lidar with average forest canopy heights estimated from tree-based measurements in or near 346 0.05 ha plots (made in autumn of 1997 and 1998). Vegetation heights had by far the predominant influence on lidar top heights, but with this large data set we were able to measure two significant secondary effects: those of steepness or slope of the underlying terrain and of tree crown form. The size of the slope effect was intermediate between that expected from models of homogeneous canopy layers and for solitary tree crowns. The first detected surfaces were also proportionately taller for plots with more basal area in broad leaved northern hardwoods than for mostly coniferous plots. We expected this because of the contrast between the shapes of cumulative distributions of surface area for elliptical or hemi-elliptical tree crowns and those for conical crowns. Correcting for these secondary effects, when appropriate data are available for calibration, may improve vegetation structure estimates in regional studies using VCL or similar lidar data sources.

Knox, Robert G.↗
NASA NTRS1990

Topographic distribution of clear-sky radiation over the Konza Prairie, Kansas

A method for exploring the topographic modulation of clear-sky incoming radiation using a two-stream atmospheric model together with digital elevation data is presented to obtain the temporal and spatial distribution of this energy. Utilizing this methodology for the Konza Prairie, it is observed that the variance and spatial autocorrelation of the simulated radiation data changed with sun angle and elevation grid spacing. An analytical formula that describes the behavior of the variance as a function of optical depth, sun angle, and mean terrain slope can be developed by considering direct solar radiation variability on a constant-slope terrain which has a uniform albedo and a uniform distribution of slopes. The decrease in mean slope and the increase in slope and autocorrelation is attributed to a loss of some of the shorter-wavelength terrain features at coarser grid spacings.

Dubayah, Ralph↗
NASA NTRS1989

Covariance of greenness and terrain variables over the Konza Prairie

An analysis is made of time-dependent covariance of the greenness vegetation index with mapped terrain variables over the Konza Prarie (Kansas) during the 1987 growing season. The analysis was part of an ongoing project to establish appopriate ground-sampling and data-integration strategies for satellite-based monitoring of land surface climate conditions. Greenness images for six dates between May and October were derived from atmospherically corrected thematic mapper (TM) data and coregistered with maps of woody vegetation, fire, and soils. Local variance in greenness peaked in mid-June, falling rapidly until mid-August, and declining gradually thereafter. Greenness images exhibited positive autocorrelation up to distances of 180-210 m, but the dominant scale of pattern occurred at a block size of 60 m by 60 m throughout the growing season. 40-44 percent of total scene variance in July and August was accounted for by the effects of woody vegetation (8.9 percent of the area), prairie burning, and soil type. The effect of these terrain variables was fairly consistent between June and late August and was manifested as additional high-frequency spatial variation in imagery from that period.

Davis, Frank W.↗