Airborne and Spaceborne Lidar Reveal Trends and Patterns of Functional Diversity in a Semi-Arid Ecosystem

Assessing functional diversity and its abiotic controls at continuous spatial scales are crucial to understanding changes in ecosystem processes and services. Semi-arid ecosystems cover large portions of the global terrestrial surface and provide carbon cycling, habitat, and biodiversity, among other important ecosystem processes and services. Yet, the spatial trends and patterns of functional diversity in semi-arid ecosystems and their abiotic controls are unclear. The objectives of this study are two-fold. We evaluated the spatial pattern of functional diversity as estimated from small footprint airborne lidar (ALS) with respect to abiotic controls and fire in a semi-arid ecosystem. Secondly, we used our results to understand the capabilities of large footprint spaceborne lidar (GEDI) for future applications to semi-arid ecosystems. Overall, our findings revealed that functional diversity in this ecosystem is mainly governed by elevation, soil, and water availability. In burned areas, the ALS data show a trend of functional recovery with time since fire. With 16 months of data (April 2019-August 2020), GEDI predicted functional traits showed a moderate correlation (r = 41–61%) with the ALS predicted traits except for the plant area index (PAI) (r = 11%) of low height vegetation (<5 m). We found that the number of GEDI footprints relative to the size of the fire-disturbed areas (=< 2 km2) limited the ability to estimate the full effects of fire disturbance. However, the consistency of diversity trends between ALS and GEDI across our study area demonstrates GEDI’s potential of capturing functional diversity in similar semi-arid ecosystems. The capability of spaceborne lidar to map trends and patterns of functional diversity in this semi-arid ecosystem demonstrates its exciting potential to identify critical biophysical and ecological shifts. Furthermore, opportunities to fuse GEDI with complementary spaceborne data such as ICESat-2 or the upcoming NASA-ISRO Synthetic Aperture Radar (NISAR), and fine scale airborne data will allow us to fill gaps across space and time. For the first time, we have the potential to monitor carbon cycle dynamics, habitats and biodiversity across the globe in semi-arid ecosystems at fine vertical scales

Seasonal pattern of regional carbon balance in the central Rocky Mountains from surface and airborne measurements

[1] High-elevation forests represent a large fraction of potential carbon uptake in North America, but this uptake is not well constrained by observations. Additionally, forests in the Rocky Mountains have recently been severely damaged by drought, fire, and insect outbreaks, which have been quantified at local scales but not assessed in terms of carbon uptake at regional scales. The Airborne Carbon in the Mountains Experiment was carried out in 2007 partly to assess carbon uptake in western U.S. mountain ecosystems. The magnitude and seasonal change of carbon uptake were quantified by (1) paired upwind-downwind airborne CO2 observations applied in a boundary layer budget, (2) a spatially explicit ecosystem model constrained using remote sensing and flux tower observations, and (3) a downscaled global tracer transport inversion. Top-down approaches had mean carbon uptake equivalent to flux tower observations at a subalpine forest, while the ecosystem model showed less. The techniques disagreed on temporal evolution. Regional carbon uptake was greatest in the early summer immediately following snowmelt and tended to lessen as the region experienced dry summer conditions. This reduction was more pronounced in the airborne budget and inversion than in flux tower or upscaling, possibly related to lower snow water availability in forests sampled by the aircraft, which were lower in elevation than the tower site. Changes in vegetative greenness associated with insect outbreaks were detected using satellite reflectance observations, but impacts on regional carbon cycling were unclear, highlighting the need to better quantify this emerging disturbance effect on montane forest carbon cycling

The Changing Landscape for Stroke\ua0Prevention in AF: Findings From the GLORIA-AF Registry Phase 2

Background GLORIA-AF (Global Registry on Long-Term Oral Antithrombotic Treatment in Patients with Atrial Fibrillation) is a prospective, global registry program describing antithrombotic treatment patterns in patients with newly diagnosed nonvalvular atrial fibrillation at risk of stroke. Phase 2 began when dabigatran, the first non\u2013vitamin K antagonist oral anticoagulant (NOAC), became available. Objectives This study sought to describe phase 2 baseline data and compare these with the pre-NOAC era collected during phase 1. Methods During phase 2, 15,641 consenting patients were enrolled (November 2011 to December 2014); 15,092 were eligible. This pre-specified cross-sectional analysis describes eligible patients\u2019 baseline characteristics. Atrial fibrillation disease characteristics, medical outcomes, and concomitant diseases and medications were collected. Data were analyzed using descriptive statistics. Results Of the total patients, 45.5% were female; median age was 71 (interquartile range: 64, 78) years. Patients were from Europe (47.1%), North America (22.5%), Asia (20.3%), Latin America (6.0%), and the Middle East/Africa (4.0%). Most had high stroke risk (CHA2DS2-VASc [Congestive heart failure, Hypertension, Age  6575 years, Diabetes mellitus, previous Stroke, Vascular disease, Age 65 to 74 years, Sex category] score  652; 86.1%); 13.9% had moderate risk (CHA2DS2-VASc = 1). Overall, 79.9% received oral anticoagulants, of whom 47.6% received NOAC and 32.3% vitamin K antagonists (VKA); 12.1% received antiplatelet agents; 7.8% received no antithrombotic treatment. For comparison, the proportion of phase 1 patients (of N = 1,063 all eligible) prescribed VKA was 32.8%, acetylsalicylic acid 41.7%, and no therapy 20.2%. In Europe in phase 2, treatment with NOAC was more common than VKA (52.3% and 37.8%, respectively); 6.0% of patients received antiplatelet treatment; and 3.8% received no antithrombotic treatment. In North America, 52.1%, 26.2%, and 14.0% of patients received NOAC, VKA, and antiplatelet drugs, respectively; 7.5% received no antithrombotic treatment. NOAC use was less common in Asia (27.7%), where 27.5% of patients received VKA, 25.0% antiplatelet drugs, and 19.8% no antithrombotic treatment. Conclusions The baseline data from GLORIA-AF phase 2 demonstrate that in newly diagnosed nonvalvular atrial fibrillation patients, NOAC have been highly adopted into practice, becoming more frequently prescribed than VKA in Europe and North America. Worldwide, however, a large proportion of patients remain undertreated, particularly in Asia and North America. (Global Registry on Long-Term Oral Antithrombotic Treatment in Patients With Atrial Fibrillation [GLORIA-AF]; NCT01468701

Calibration of the National Ecological Observatory Network\u27s Airborne Observation Platforms

The National Ecological Observatory Network (NEON) is a continental-scale ecological observation facility funded by the National Science Foundation (NSF). NEON\u27s mission is to enable understanding and forecasting of the impacts of land-use change and invasive species by providing the infrastructure and consistent methodologies for the collection of continental-scale ecological data. The Airborne Observation Platform (AOP) will play a unique role by collecting regional scale remote sensing data surrounding the NEON sites. This is expected to enable scaling of individual in-situ measurements collected by NEON or others to those collected by external satellite-based remote sensing systems. The airborne payload consists of the NEON Imaging Spectrometer (NIS), a full waveform and discrete LIDAR, and a high-resolution digital camera integrated into a Twin Otter aircraft. Three payloads on separate aircraft will provide coverage of 80 plus sites located in the 20 NEON Domains as well as targets of opportunity and PI-driven science. A key component of the NEON design is the consistent calibration of the airborne instruments to provide reliable and accurate scientific data over the full lifetime of the NEON observatory. The NEON Sensor Test Facility provides the facilities for the laboratory calibration of the AOP instrumentation. This work examines the spectral and radiometric calibration of the NIS in the NEON Sensor Test Facility. Recent work has focused on the traceability and uncertainty of the radiometric and spectral calibration and stability of the calibration from lab to operations. To verify the operational stability during acquisitions, a quality check algorithm has been developed to assess the raw NIS data prior to ingestion into the NEON processing framework. In addition, routine vicarious calibration flights are scheduled to independently verify the lab-based calibration. The work presented here also examines implemented improvements in characterizing the level of stray light in the NIS data. These corrections have significantly improved the fidelity of the spectroscopic data as well as improving the overall radiometric and spectral accuracy across the typical heterogeneous scenes included in the NEON collections

NEON Imaging Spectrometer (NIS) Calibration Updates

The NIS (NEON Imaging Spectrometer) is an airborne pushbroom hyperspectral instrument developed by NASA Jet Propulsion Laboratory (JPL) for the National Ecological Observation Network (NEON) and is included in all three of NEON’s Airborne Observation Platform (AOP) payloads. NEON, funded by the National Science Foundation (NSF), is a continental-scale observatory designed to collect long-term data to better understand and forecast impacts of climate change, land use change and invasive species (Kampe et al. 2010). NEON has recently completed the construction phase and is in the initial operational phase, which represents annual activities that will be repeated for the remaining 30-year lifetime of the project (Goulden et al. 2019). The AOP begun data collection in 2013, although only a small subset of NEON sites was collected. By 2018 and 2019, AOP was collecting data in 16 domains annually, representing the typical data collection scenario during the operational phase of the NEON project. NEON provides 28 data products from AOP, which are publicly available and can be freely accessed from NEON data portal: https://data.neonscience.org/home. In addition to the NIS, AOP payloads include a discrete and full-waveform lidar and a high resolution RGB camera. The NIS design is based on AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) NextGen Imaging Spectrometer and measures radiant energy both in VNIR (Visible-Near Infrared) and SWIR (Shortwave Infrared) spectral region (380-2510 nm) with ~5 nm sampling and 1 mRad instantaneous field of view (IFOV) (Kuester et al. 2010). This 1 mRad IFOV leads to a ground resolution of 1m at a typical flight altitude of ~1000m. In order to ensure the accuracy of the measurements, the NIS requires stable and consistent annual calibrations (Leisso et al. 2014). Assessment of NIS calibration datasets revealed anomalies that should be characterized and corrected to improve the accuracy of NIS datasets. This presentation will briefly discuss the current status of NEON project and provides detailed description of NIS calibration improvements including: 1) characterizing NIS stray light anomalies, 2) techniques implemented to correct such anomalies, and 3) NIS stability analysis. Goulden T., B. Hass, J. Musinsky, and A. K. Shrestha, 2019, Status of NEON\u27s Airborne Observation Platform , AGU Fall Meeting, 9-13 December, 2019, San Francisco, CA, USA, Kampe T. U., B. R. Johnson, M. Kuester, and M. Keller, 2010, NEON: the first continental-scale ecological observatory with airborne remote sensing of vegetation canopy biochemistry and structure , Journal of Applied Remote Sensing 4(1), 043510 (1 March 2010). https://doi.org/10.1117/1.3361375 Kuester M. A., J.T. McCorkel, Johnson, B.R., and Kampe T.U., 2010, Radiometric Calibration Concept of Imaging Spectrometers for a long-term Ecological Remote Sensing Project Leisso N., Kampe T., Karpowicz B., 2014, Calibration of the National Ecological Observatory Network\u27s airborne imaging spectrometers , 2014 IEEE Geoscience and Remote Sensing Symposium, Quebec City, QC, 2014, pp. 2625-2628. doi: 10.1109/IGARSS.2014.694701

A Comparison of Multitemporal Airborne Laser Scanning Data and the Fuel Characteristics Classification System for Estimating Fuel Load and Consumption

Characterizing pre-fire fuel load and fuel consumption are critical for assessing fire behavior, fire effects, and smoke emissions. Two approaches for quantifying fuel load are airborne laser scanning (ALS) and the Fuel Characteristic Classification System (FCCS). The implementation of multitemporal ALS (i.e., the use of two or more ALS datasets across time at a given location) in conjunction with empirical models trained with field data can be used to measure fuel and estimate fuel consumption from a fire. FCCS, adapted for use in LANDFIRE (LF), provides 30 m resolution estimates of fuel load across the contiguous United States and can be used to estimate fuel consumption through software programs such as Fuel and Fire Tools (FFT). This study compares the two approaches for two wildfires in the northwestern United States having predominantly sagebrush steppe and ponderosa pine savanna ecosystems. The results showed that the LF FCCS approach yielded higher pre-fire fuel loads and fuel consumption than the ALS approach and that the coarser scale LF FCCS data did not capture as much heterogeneity as the ALS data. At Tepee, 50.0% of the difference in fuel load and 87.3% of the difference in fuel consumption were associated with distinguishing sparse trees from rangeland. At Keithly, this only accounted for 8.2% and 8.6% of the differences, demonstrating the significance of capturing heterogeneity in rangeland vegetation structure and fire effects. Our results suggest future opportunities to use ALS data to better parametrize fine-scale fuel load variability that LF FCCS does not capture

Integrating airborne remote sensing and field campaigns for ecology and Earth system science

In recent years, the availability of airborne imaging spectroscopy (hyperspectral) data has expanded dramatically. The high spatial and spectral resolution of these data uniquely enable spatially explicit ecological studies including species mapping, assessment of drought mortality and foliar trait distributions. However, we have barely begun to unlock the potential of these data to use direct mapping of vegetation characteristics to infer subsurface properties of the critical zone. To assess their utility for Earth systems research, imaging spectroscopy data acquisitions require integration with large, coincident ground-based datasets collected by experts in ecology and environmental and Earth science. Without coordinated, well-planned field campaigns, potential knowledge leveraged from advanced airborne data collections could be lost. Despite the growing importance of this field, documented methods to couple such a wide variety of disciplines remain sparse. We coordinated the first National Ecological Observatory Network Airborne Observation Platform (AOP) survey performed outside of their core sites, which took place in the Upper East River watershed, Colorado. Extensive planning for sample tracking and organization allowed field and flight teams to update the ground-based sampling strategy daily. This enabled collection of an extensive set of physical samples to support a wide range of ecological, microbiological, biogeochemical and hydrological studies. We present a framework for integrating airborne and field campaigns to obtain high-quality data for foliar trait prediction and document an archive of coincident physical samples collected to support a systems approach to ecological research in the critical zone. This detailed methodological account provides an example of how a multi-disciplinary and multi-institutional team can coordinate to maximize knowledge gained from an airborne survey, an approach that could be extended to other studies. The coordination of imaging spectroscopy surveys with appropriately timed and extensive field surveys, along with high-quality processing of these data, presents a unique opportunity to reveal new insights into the structure and dynamics of the critical zone. To our knowledge, this level of co-aligned sampling has never been undertaken in tandem with AOP surveys and subsequent studies utilizing this archive will shed considerable light on the breadth of applications for which imaging spectroscopy data can be leveraged

Leveraging the NEON Airborne Observation Platform for socio‐environmental systems research

Abstract During the 21st century, human–environment interactions will increasingly expose both systems to risks, but also yield opportunities for improvement as we gain insight into these complex, coupled systems. Human–environment interactions operate over multiple spatial and temporal scales, requiring large data volumes of multi‐resolution information for analysis. Climate change, land‐use change, urbanization, and wildfires, for example, can affect regions differently depending on ecological and socioeconomic structures. The relative scarcity of data on both humans and natural systems at the relevant extent can be prohibitive when pursuing inquiries into these complex relationships. We explore the value of multitemporal, high‐density, and high‐resolution LiDAR, imaging spectroscopy, and digital camera data from the National Ecological Observatory Network’s Airborne Observation Platform (NEON AOP) for Socio‐Environmental Systems (SES) research. In addition to providing an overview of NEON AOP datasets and outlining specific applications for addressing SES questions, we highlight current challenges and provide recommendations for the SES research community to improve and expand its use of this platform for SES research. The coordinated, nationwide AOP remote sensing data, collected annually over the next 30 yr, offer exciting opportunities for cross‐site analyses and comparison, upscaling metrics derived from LiDAR and hyperspectral datasets across larger spatial extents, and addressing questions across diverse scales. Integrating AOP data with other SES datasets will allow researchers to investigate complex systems and provide urgently needed policy recommendations for socio‐environmental challenges. We urge the SES research community to further explore questions and theories in social and economic disciplines that might leverage NEON AOP data