J. Bryan Blair

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.

The Laser Vegetation Imaging Sensor : a medium-altitude, digitisation-only, airborne laser altimeter for mapping vegetation and topography

Abstract The Laser Vegetation Imaging Sensor (LVIS) is an airborne, scanning laser altimeter, designed and developed at NASAs Goddard Space Flight Center (GSFC). LVIS operates at altitudes up to 10 km above ground, and is capable of producing a data swath up to 1000 m wide nominally with 25-m wide footprints. The entire time history of the outgoing and return pulses is digitised, allowing unambiguous determination of range and return pulse structure. Combined with aircraft position and attitude knowledge, this instrument produces topographic maps with dm accuracy and vertical height and structure measurements of vegetation. The laser transmitter is a diode-pumped Nd:YAG oscillator producing 1064 nm, 10 ns, 5 mJ pulses at repetition rates up to 500 Hz. LVIS has recently demonstrated its ability to determine topography (including sub-canopy) and vegetation height and structure on flight missions to various forested regions in the US and Central America. The LVIS system is the airborne simulator for the Vegetation Canopy Lidar (VCL) mission (a NASA Earth remote sensing satellite due for launch in year 2000), providing simulated data sets and a platform for instrument proof-of-concept studies. The topography maps and return waveforms produced by LVIS provide Earth scientists with a unique data set allowing studies of topography, hydrology, and vegetation with unmatched accuracy and coverage.

Modeling laser altimeter return waveforms over complex vegetation using high‐resolution elevation data

The upcoming generation of laser altimeters record the interaction of emitted laser radiation with terrestrial surfaces in the form of a digitized waveform. We model these laser altimeter return waveforms as the sum of the reflections from individual surfaces within laser footprints, accounting for instrument-specific properties. We compare over 1000 modeled and recorded waveform pairs using the Pearson correlation. We show that we reliably synthesize the vertical structure information for vegetation canopies contained in a medium-large diameter laser footprint from a high-resolution elevation data set.

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.

Validation of SRTM Elevations Over Vegetated and Non-vegetated Terrain Using Medium-Footprint Lidar

The Shuttle Radar Topography Mission (SRTM) generated one of the most-complete high-resolution digital topographic data sets of the world to date. The elevations generated by the on-board C-band sensor represent surface elevations in “bare earth” regions, and the elevations of various scatterers such as leaves and branches in other regions. Elevations generated by a medium-footprint (� 10 m diameter) laser altimeter (lidar) system known as NASA’s Laser Vegetation Imaging Sensor (LVIS) were used to assess the accuracy of SRTM elevations at study sites of variable relief, and landcover. Five study sites in Maine, Massachusetts, Maryland, New Hampshire, and Costa Rica were chosen where coincident LVIS and SRTM data occur. Both ground and canopy top lidar elevations were compared to the SRTM elevations. In “bare earth” regions, the mean vertical offset between the SRTM elevations and LVIS ground elevations varied with study site and was approximately 0.0 m, 0.5 m, 3.0 m, 4.0 m, and 4.5 m at the Maine, Maryland, Massachusetts, New Hampshire, and Costa Rica study sites, respectively. In vegetated regions, the mean vertical offset increased, implying the phase center fell above the ground, and the offset varied by region. The SRTM elevations fell on average approximately 14 m below the LVIS canopy top elevations, except in Costa Rica where they were approximately 8 m below the canopy top. At all five study sites, SRTM elevations increased with increasing vertical extent (i.e., the difference between the LVIS canopy top and ground elevations and analogous to canopy height in vegetated regions). A linear relationship was found sufficient to describe the relationship between the SRTM-LVIS elevation difference and canopy vertical extent.

The proposed DESDynI mission - From science to implementation

The proposed DESDynI mission is being planned by NASA to study earth change in three distinct disciplines - ecosystems, solid earth, and cryospheric sciences. DESDynI would provide unique and unprecedented capabilities to the science community, with an imaging L-band radar proposed to include new modes and observational techniques, and a first-of-a-kind multi-beam lidar for measuring canopy height metrics at fine spatial resolution. Under current planning scenarios, DESDynI could be ready to launch in 2017. In this paper, we describe the science objectives, how these lead to the measurements that achieve these objectives, and how these requirements lead to a mission design. The properties of the radar are then described, including a number of new radar modes and capabilities such as “SweepSAR” scan-on-receive techniques and split-spectrum acquisitions in single and multipol configurations.

Use of waveform lidar and hyperspectral sensors to assess selected spatial and structural patterns associated with recent and repeat disturbance and the abundance of sugar maple (Acer saccharum Marsh.) in a temperate mixed hardwood and conifer forest

Waveform lidar imagery was acquired on September 26, 1999 over the Bartlett Experimental Forest (BEF) in New Hampshire (USA) using NASAs Laser Vegetation Imaging Sensor (LVIS). This flight occurred 20 months after an ice storm damaged millions of hectares of forestland in northeastern North America. Lidar measurements of the amplitude and intensity of ground energy returns appeared to readily detect areas of moderate to severe ice storm damage associated with the worst damage. Southern through eastern aspects on side slopes were particularly susceptible to higher levels of damage, in large part overlapping tracts of forest that had suffered the highest levels of wind damage from the 1938 hurricane and containing the highest levels of sugar maple basal area and biomass. The levels of sugar maple abundance were determined through analysis of the 1997 Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) high resolution spectral imagery and inventory of USFS Northern Research Station field plots. We found a relationship between field measurements of stem volume losses and the LVIS metric of mean canopy height (r2 = 0.66; root mean square errors = 5.7 m3/ha, p < 0.0001) in areas that had been subjected to moderate-to-severe ice storm damage, accurately documenting the short-term outcome of a single disturbance event.

DESDynI lidar for solid earth applications

As part of the NASAs DESDynI mission, global elevation profiles from contiguous 25 m footprint Lidar measurements will be made. Here we present results of a performance simulation of a single pass of the multi-beam Lidar instrument over uplifted marine terraces in southern Alaska. The significance of the Lidar simulations is that surface topography would be captured at sufficient resolution for mapping uplifted terraces features but it will be hard to discern 1-2m topographic change over features less than tens of meters in width. Since Lidar would penetrate most vegetation, the accurate bald Earth elevation profiles will give new elevation information beyond the standard 30-m DEM.

The 2016 NASA AfriSAR campaign: Airborne SAR and Lidar measurements of tropical forest structure and biomass in support of future satellite missions

Background The AfriSAR campaign was a joint NASA and European Space Agency airborne campaign conducted in Gabon in support of the upcoming ESA BIOMASS, NASA-ISRO Synthetic Aperture Radar (NISAR) and NASA Global Ecosystem Dynamics Initiative (GEDI) missions. The aim of the campaign was to collect ground, airborne SAR and airborne Lidar data for the development and evaluation of forest structure and biomass retrieval algorithms. The campaign consisted of two deployments, the first in 2015 with the ONERA SETHI SAR system and the second in 2016 with the NASA LVIS (Land Vegetation and Ice Sensor) Lidar, the NASA L-band UAVSAR and the DLR F-SAR. In addition, field teams from the Gabon ANPN (Agence Nationale des Parcs Nationaux), University College London and NASA were collecting ground data. Here we focus on the 2016 NASA contributions to campaign.

Arctic Radiation-IceBridge Sea and Ice Experiment: The Arctic Radiant Energy System during the Critical Seasonal Ice Transition

AbstractThe National Aeronautics and Space Administration (NASA)’s Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE) acquired unique aircraft data on atmospheric radiation and sea ice properties during the critical late summer to autumn sea ice minimum and commencement of refreezing. The C-130 aircraft flew 15 missions over the Beaufort Sea between 4 and 24 September 2014. ARISE deployed a shortwave and longwave broadband radiometer (BBR) system from the Naval Research Laboratory; a Solar Spectral Flux Radiometer (SSFR) from the University of Colorado Boulder; the Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) from the NASA Ames Research Center; cloud microprobes from the NASA Langley Research Center; and the Land, Vegetation and Ice Sensor (LVIS) laser altimeter system from the NASA Goddard Space Flight Center. These instruments sampled the radiant energy exchange between clouds and a variety of sea ice scenarios, including prior to and after refreezing began. The most c...