Anelastic deformation in Iceland studied using GPS: with special reference to post-tectonic motion following the 1975-1985 krafla rifting episode, and isostatic rebound

The Krafla volcanic system is a spreading segment in north Iceland. A decade-long crustal spreading episode began there in 1975. Up to 8 m of rift-normal surface widening occurred along an 80-90 km-long section of the plate boundary. Isostatic uplift in the vicinity of the melting icecap Vatnajōkull has been proposed. A third GPS survey of a regional network surrounding the Krafla system was conducted in 1992. In 1991 a 10-point GPS network was installed and measured for the first time around Vatnajōkull. The 1991 and 1992 GPS data were processed using the Bernese software. Differencing the 1992 results with those from 1987 and 1990 revealed a regional deformation field with a maximum, rift-normal expansion rate of 4.4 cm/yr near the rift, decreasing to 3 cm/yr at large distances. The time-averaged spreading rate in north Iceland, 1.8 cm/yr, cannot account for this deformation. The vertical deformation field reveals regional uplift throughout the network area, at its maximum closest to the rift and decreasing with distance. Three different models were applied to study the postdyking ground deformation, (1) continued opening at depth on the dyke plane in an elastic halfspace, (2) stress redistribution in an elastic-viscous layered medium, and (3) stress redistribution in an elastic layer over a viscoelastic halfspace. The latter model was developed by extending mathematical techniques previously used to model surface displacements resulting from thrust faulting to the case of dyke emplacement. For the model of continuous dyking at depth, a range of dykes will fit the deformation field. Using the elastic-viscous model, the motion 1987-1990 and 1990-1992 is simulated adequately given the survey errors, but the 1987-1992 deformation is poorly fitted, suggesting that a more realistic geophysical model is required. Using the elastic-viscoelastic approach the effects of historical episodes in the region were subtracted from the observed displacement fields and the remaining motion was modelled as relaxation following the recent Krafla rifting episode. The best-fit model involves a halfspace viscosity of 1.1 x 10(^18) Pa s. The vertical field is noisy, but indicates that the Krafla dyke complex rifted the entire elastic layer. Isostatic uplift centred on Vatnajőkull is inconsistent with the vertical deformation field. The model suggests that the Krafla volcano became inactive after 1988/1989. The model further predicts that the width of the "plate boundary zone" is greater than that of Iceland itself

DESDynI Lidar for Solid Earth Applications

As part of the NASA's 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 I-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 OEM

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.

Abstract Waveform lidar imagery was acquired on September 26, 1999 over the Bartlett Experimental Forest (BEF) in New Hampshire (USA) using NASA\u27s 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 \u3c 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

Fusing simulated GEDI, ICESat-2 and NISAR data for regional aboveground biomass mapping

Accurate mapping of forest aboveground biomass (AGB) is critical for better understanding the role of forests in the global carbon cycle. NASA's current GEDI and ICESat-2 missions as well as the upcoming NISAR mission will collect synergistic data with different coverage and sensitivity to AGB. In this study, we present a multi-sensor data fusion approach leveraging the strength of each mission to produce wall-to-wall AGB maps that are more accurate and spatially comprehensive than what is achievable with any one sensor alone. Specifically, we calibrate a regional L-band radar AGB model using the sparse, simulated spaceborne lidar AGB estimates. We assess our data fusion framework using simulations of GEDI, ICESat-2 and NISAR data from airborne laser scanning (ALS) and UAVSAR data acquired over the temperate high AGB forest and complex terrain in Sonoma County, California, USA. For ICESat-2 and GEDI missions, we simulate two years of data coverage and AGB at footprint level are estimated using realistic AGB models. We compare the performance of our fusion framework when different combinations of the sparse simulated GEDI and ICEsat-2 AGB estimates are used to calibrate our regional L-band AGB models. In addition, we test our framework at Sonoma using (a) 1-ha square grid cells and (b) similarly sized irregularly shaped objects. We demonstrate that the estimated mean AGB across Sonoma is more accurately estimated using our fusion framework than using GEDI or ICESat-2 mission data alone, either with a regular grid or with irregular segments as mapping units. This research highlights methodological opportunities for fusing new and upcoming active remote sensing data streams toward improved AGB mapping through data fusion.</p

Biomass estimation from simulated GEDI, ICESat-2 and NISAR across environmental gradients in Sonoma County, California

Estimates of the magnitude and distribution of aboveground carbon in Earth's forests remain uncertain, yet knowledge of forest carbon content at a global scale is critical for forest management in support of climate mitigation. In light of this knowledge gap, several upcoming spaceborne missions aim to map forest aboveground biomass, and many new biomass products are expected from these datasets. As these new missions host different technologies, each with relative strengths and weaknesses for biomass retrieval, as well as different spatial resolutions, consistently comparing or combining biomass estimates from these new datasets will be challenging. This paper presents a demonstration of an inter-comparison of biomass estimates from simulations of three NASA missions (GEDI, ICESat-2 and NISAR) over Sonoma county in California, USA. We use a high resolution, locally calibrated airborne lidar map as our reference dataset, and emphasize the importance of considering uncertainties in both reference maps and spaceborne estimates when conducting biomass product validation. GEDI and ICESat-2 were simulated from airborne lidar point clouds, while UAVSAR's L-band backscatter was used as a proxy for NISAR. To estimate biomass for the lidar missions we used GEDI's footprint-level biomass algorithms, and also adapted these for application to ICESat-2. For UAVSAR, we developed a locally trained biomass model, calibrated against the ALS reference map. Each mission simulation was evaluated in comparison to the local reference map at its native product resolution (25 m, 100 m transect, and 1 ha) yielding RMSEs of 57%, 75%, and 89% for GEDI, NISAR, and ICESat-2 respectively. RMSE values increased for GEDI's power beam during simulated daytime conditions (64%), coverage beam during nighttime conditions (72%), and coverage beam daytime conditions (87%). We also test the application of GEDI's biomass modeling framework for estimation of biomass from ICESat-2, and find that ICESat-2 yields reasonable biomass estimates, particularly in relatively short, open canopies. Results suggest that while all three missions will produce datasets useful for biomass mapping, tall, dense canopies such as those found in Sonoma County present the greatest challenges for all three missions, while steep slopes also prove challenging for single-date SAR-based biomass retrievals. Our methods provide guidance for the inter-comparison and validation of spaceborne biomass estimates through the use of airborne lidar reference maps, and could be repeated with on-orbit estimates in any area with high quality field plot and ALS data. These methods allow for regional interpretations and filtering of multi-mission biomass estimates toward improved wall-to-wall biomass maps through data fusion.</p

The Algorithm Theoretical Basis Document for the Derivation of Range and Range Distributions from Laser Pulse Waveform Analysis for Surface Elevations, Roughness, Slope, and Vegetation Heights

The primary purpose of the GLAS instrument is to detect ice elevation changes over time which are used to derive changes in ice volume. Other objectives include measuring sea ice freeboard, ocean and land surface elevation, surface roughness, and canopy heights over land. This Algorithm Theoretical Basis Document (ATBD) describes the theory and implementation behind the algorithms used to produce the level 1B products for waveform parameters and global elevation and the level 2 products that are specific to ice sheet, sea ice, land, and ocean elevations respectively. These output products, are defined in detail along with the associated quality, and the constraints, and assumptions used to derive them

Mapping Migratory Bird Prevalence Using Remote Sensing Data Fusion

Background: Improved maps of species distributions are important for effective management of wildlife under increasing anthropogenic pressures. Recent advances in lidar and radar remote sensing have shown considerable potential for mapping forest structure and habitat characteristics across landscapes. However, their relative efficacies and integrated use in habitat mapping remain largely unexplored. We evaluated the use of lidar, radar and multispectral remote sensing data in predicting multi-year bird detections or prevalence for 8 migratory songbird species in the unfragmented temperate deciduous forests of New Hampshire, USA. Methodology and Principal Findings: A set of 104 predictor variables describing vegetation vertical structure and variability from lidar, phenology from multispectral data and backscatter properties from radar data were derived. We tested the accuracies of these variables in predicting prevalence using Random Forests regression models. All data sets showed more than 30% predictive power with radar models having the lowest and multi-sensor synergy ("fusion") models having highest accuracies. Fusion explained between 54% and 75% variance in prevalence for all the birds considered. Stem density from discrete return lidar and phenology from multispectral data were among the best predictors. Further analysis revealed different relationships between the remote sensing metrics and bird prevalence. Spatial maps of prevalence were consistent with known habitat preferences for the bird species. Conclusion and Significance: Our results highlight the potential of integrating multiple remote sensing data sets using machine-learning methods to improve habitat mapping. Multi-dimensional habitat structure maps such as those generated from this study can significantly advance forest management and ecological research by facilitating fine-scale studies at both stand and landscape level

Lidar remote sensing variables predict breeding habitat of a Neotropical migrant bird

A topic of recurring interest in ecological research is the degree to which vegetation structure influences the distribution and abundance of species. Here we test the applicability of remote sensing, particularly novel use of waveform lidar measurements, for quantifying the habitat heterogeneity of a contiguous northern hardwoods forest in the northeastern United States. We apply these results to predict the breeding habitat quality, an indicator of reproductive output of a well-studied Neotropical migrant songbird, the Blackthroated Blue Warbler (Dendroica caerulescens). We found that using canopy vertical structure metrics provided unique information for models of habitat quality and spatial patterns of prevalence. An ensemble decision tree modeling approach (random forests) consistently identified lidar metrics describing the vertical distribution and complexity of canopy elements as important predictors of habitat use over multiple years. Although other aspects of habitat were important, including the seasonality of vegetation cover, the canopy structure variables provided unique and complementary information that systematically improved model predictions. We conclude that canopy structure metrics derived from waveform lidar, which will be available on future satellite missions, can advance multiple aspects of biodiversity research, and additional studies should be extended to other organisms and regions.Key words: bird diversity; Black-throated Blue Warbler; canopy structure; Dendroica caerulescens; habitat quality; Hubbard Brook Experimental Forest, New Hampshire, USA; Neotropical migratory birds; northern hardwoods forests; remote sensing; waveform lidar data

Toward Global Snow from Space: Coverage of Snow Observation Constellation Configurations

No abstract availabl