John Armston

ORCID: 0000-0003-1232-3424
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About
Contact & Profiles
Research Areas
  • Remote Sensing and LiDAR Applications
  • Remote Sensing in Agriculture
  • Forest ecology and management
  • Synthetic Aperture Radar (SAR) Applications and Techniques
  • Forest Ecology and Biodiversity Studies
  • Plant Water Relations and Carbon Dynamics
  • Forest Management and Policy
  • Soil erosion and sediment transport
  • 3D Surveying and Cultural Heritage
  • Soil Geostatistics and Mapping
  • Atmospheric and Environmental Gas Dynamics
  • Fire effects on ecosystems
  • Cryospheric studies and observations
  • Forest Biomass Utilization and Management
  • Meteorological Phenomena and Simulations
  • Adaptive optics and wavefront sensing
  • Land Use and Ecosystem Services
  • Species Distribution and Climate Change
  • Hydrology and Sediment Transport Processes
  • Rangeland and Wildlife Management
  • Soil Moisture and Remote Sensing
  • Landslides and related hazards
  • Aeolian processes and effects
  • Bioenergy crop production and management
  • Remote Sensing and Land Use

University of Maryland, College Park
2017-2025

Norwegian University of Life Sciences
2023

Goddard Space Flight Center
2023

Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR)
2023

ORCID
2022

University of Maryland, Baltimore
2021

The University of Queensland
2010-2019

Queensland Department of Environment and Science
2009-2018

Queensland Government
2010-2016

Naval Postgraduate School
2009

Obtaining accurate and widespread measurements of the vertical structure Earth's forests has been a long-sought goal for ecological community. Such observations are critical accurately assessing existing biomass forests, how changes in this caused by human activities or variations climate may impact atmospheric CO2 concentrations. Additionally, three-dimensional is key component habitat quality biodiversity at local to regional scales. The Global Ecosystem Dynamics Investigation (GEDI) was...

10.1016/j.srs.2020.100002 article EN cc-by-nc-nd Science of Remote Sensing 2020-01-27

We combined two existing datasets of vegetation aboveground biomass (AGB) (Proceedings the National Academy Sciences United States America, 108, 2011, 9899; Nature Climate Change, 2, 2012, 182) into a pan-tropical AGB map at 1-km resolution using an independent reference dataset field observations and locally calibrated high-resolution maps, harmonized upscaled to 14 477 estimates. Our data fusion approach uses bias removal weighted linear averaging that incorporates spatializes patterns...

10.1111/gcb.13139 article EN Global Change Biology 2015-10-26

Summary Allometric equations are currently used to estimate above‐ground biomass (AGB) based on the indirect relationship with tree parameters. Terrestrial laser scanning (TLS) can measure canopy structure in 3D high detail. In this study, we develop an approach AGB from TLS data, which does not need any prior information about allometry. We compare these estimates against destructively harvested and derived allometric equations. also evaluate parameters, diameter at breast height (DBH)...

10.1111/2041-210x.12301 article EN Methods in Ecology and Evolution 2014-11-21

Terrestrial laser scanning (TLS) was introduced for basic forest measurements, such as tree height and diameter, in the early 2000s. Recent advances sensor algorithm development have allowed us to assess situ 3D structure explicitly revolutionised way we monitor quantify ecosystem function. Here, provide an interdisciplinary focus explore current developments TLS measure structure. We argue that data will play a critical role understanding fundamental ecological questions about size shape,...

10.1016/j.rse.2020.112102 article EN cc-by Remote Sensing of Environment 2020-09-25
Laura Duncanson James R. Kellner John Armston R. Dubayah David Minor and 95 more Steven Hancock Sean P. Healey Paul L. Patterson Svetlana Saarela Suzanne Marselis Carlos E. Silva Jamis M. Bruening S. J. Goetz Hao Tang M. A. Hofton Bryan Blair S. B. Luthcke Temilola Fatoyinbo Katharine Abernethy Alfonso Alonso Hans‐Erik Andersen Paul Aplin Timothy R. Baker Nicolas Barbier Jean François Bastin Peter Biber Pascal Boeckx Jan Bogaert Luigi Boschetti Peter Boucher Doreen S. Boyd David F. R. P. Burslem Sofía Calvo-Rodríguez Jérôme Chave Robin L. Chazdon David B. Clark Deborah A. Clark Warren B. Cohen David A. Coomes Piermaria Corona K. C. Cushman Mark Cutler James W. Dalling Michele Dalponte Jonathan P. Dash Sergio de‐Miguel Songqiu Deng Peter W. Ellis Barend Erasmus Patrick A. Fekety Alfredo Fernández-Landa António Ferraz Rico Fischer Adrian Fisher Antonio García‐Abril Terje Gobakken Jörg Hacker Marco Heurich Ross A. Hill Chris Hopkinson Huabing Huang Stephen P. Hubbell Andrew T. Hudak Andreas Huth Benedikt Imbach Kathryn J. Jeffery Masato Katoh Elizabeth Kearsley David Kenfack Natascha Kljun Nikolai Knapp Kamil Král Martin Krůček Nicolas Labrière Simon L. Lewis Marcos Longo Richard Lucas Russell Main J. A. Manzanera Rodolfo Vásquez Renaud Mathieu Herve R. Memiaghe Victoria Meyer Abel Monteagudo Mendoza A. Monerris Paul Montesano Felix Morsdorf Erik Næsset Laven Naidoo Reuben Nilus Michael J. O’Brien David A. Orwig Konstantinos Papathanassiou Geoffrey G. Parker Christopher D. Philipson Oliver L. Phillips Jan Písek John R. Poulsen Hans Pretzsch Christoph Rüdiger

NASA's Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates forest aboveground biomass density (AGBD). This paper presents the development models used to create GEDI's footprint-level (~25 m) AGBD (GEDI04_A) product, including description datasets and procedure for final model selection. The fit our are from compilation globally distributed spatially temporally coincident field airborne...

10.1016/j.rse.2021.112845 article EN cc-by Remote Sensing of Environment 2022-01-07

Abstract Plot-scale measurements have been the foundation for forest surveys and reporting over 200 years. Through recent integration with airborne satellite remote sensing, manual of vegetation structure at plot scale are now basis landscape, continental international mapping our resources. The use terrestrial laser scanning (TLS) plot-scale measurement was first demonstrated a decade ago, intimation that these instruments could replace methods. This has not yet case, despite unparalleled...

10.1007/s40725-015-0025-5 article EN cc-by Current Forestry Reports 2015-10-27

NASA's Global Ecosystem Dynamics Investigation (GEDI) is a spaceborne lidar mission which will produce near global (51.6°S to 51.6°N) maps of forest structure and above-ground biomass density during its 2-year mission. GEDI uses waveform simulator for calibration algorithms assessing accuracy. This paper implements simulator, using the method proposed in Blair Hofton (1999; https://doi.org/10.1029/1999GL010484), builds upon that work by adding instrument noise validating simulated waveforms...

10.1029/2018ea000506 article EN cc-by-nc-nd Earth and Space Science 2019-02-01

Estimates of the magnitude and distribution aboveground carbon in Earth's forests remain uncertain, yet knowledge forest content at a global scale is critical for management support climate mitigation. In light this gap, several upcoming spaceborne missions aim to map biomass, many new biomass products are expected from these datasets. As host different technologies, each with relative strengths weaknesses retrieval, as well spatial resolutions, consistently comparing or combining estimates...

10.1016/j.rse.2020.111779 article EN cc-by-nc-nd Remote Sensing of Environment 2020-04-01

NASA's Global Ecosystem Dynamics Investigation (GEDI) is a key climate mission whose goal to advance our understanding of the role forests in global carbon cycle. While GEDI first space-based LIDAR explicitly optimized measure vertical forest structure predictive aboveground biomass, accurate interpretation this vast amount waveform data across broad range observational and environmental conditions challenging. Here, we present novel supervised machine learning approach interpret waveforms...

10.1016/j.rse.2021.112760 article EN cc-by Remote Sensing of Environment 2021-11-03

Accurate mapping of forest aboveground biomass (AGB) is critical for better understanding the role forests in global carbon cycle. NASA's current GEDI and ICESat-2 missions as well upcoming NISAR mission will collect synergistic data with different coverage sensitivity to AGB. In this study, we present a multi-sensor fusion approach leveraging strength each produce wall-to-wall AGB maps that are more accurate spatially comprehensive than what achievable any one sensor alone. Specifically,...

10.1016/j.rse.2020.112234 article EN cc-by Remote Sensing of Environment 2020-12-11

Abstract Accurate estimation of aboveground forest biomass stocks is required to assess the impacts land use changes such as deforestation and subsequent regrowth on concentrations atmospheric CO 2 . The Global Ecosystem Dynamics Investigation (GEDI) a lidar mission launched by NASA International Space Station in 2018. GEDI was specifically designed retrieve vegetation structure within novel, theoretical sampling design that explicitly quantifies its uncertainty across variety spatial...

10.1088/1748-9326/ac8694 article EN cc-by Environmental Research Letters 2022-08-03

The Global Ecosystem Dynamics Investigation (GEDI) LiDAR provides new spaceborne vegetation canopy structural information including relative height products defined with respect to 25 m diameter footprints. GEDI geolocation requirement is that each footprint center horizontally georeferenced within 10 (1σ), assuming normally distributed errors a 0 mean and standard deviation. impact of this uncertainty on the reliability forest estimation examined considering Airborne Laser scanner (ALS)...

10.1016/j.srs.2021.100024 article EN cc-by-nc-nd Science of Remote Sensing 2021-06-18

Forests play a critical role in stabilizing Earth's climate. Establishing protected areas (PAs) represents one approach to forest conservation, but PAs were rarely created mitigate climate change. The global impact of on the carbon cycle has not previously been quantified due lack accurate global-scale stock maps. Here we used ~412 million lidar samples from NASA's GEDI mission estimate total PA aboveground (C) 61.43 Gt (+/- 0.31), 26% all mapped terrestrial woody C. Of this total, 9.65 + /-...

10.1038/s41467-023-38073-9 article EN cc-by Nature Communications 2023-06-01

Abstract Improving the global monitoring of above‐ground biomass (AGB) is crucial for forest management to be effective in climate mitigation. In last decade, methods have been developed estimating AGB from terrestrial laser scanning (TLS) data. TLS‐derived estimates can address current uncertainties allometric and Earth observation (EO) that quantify AGB. We assembled a dataset TLS scanned consecutively destructively measured trees variety conditions reconstruction pipelines. The comprised...

10.1111/2041-210x.13906 article EN Methods in Ecology and Evolution 2022-05-26

NASA's Global Ecosystem Dynamics Investigation (GEDI) is designed to provide high-resolution measurements of forest structure and topography between 52° N S. However, current geolocation accuracy may limit further science applications footprint-level products as early adopters have found it difficult align with in-situ forestry inventory data imagery for calibration validation purpose. Here we developed a new means rapidly evaluate mitigate the impact systematic error on performance GEDI's...

10.1016/j.rse.2023.113571 article EN cc-by Remote Sensing of Environment 2023-04-09

Focusing on woody vegetation in Queensland, Australia, the study aimed to establish whether relationship between Advanced Land Observing Satellite (ALOS) Phased Array L-band SAR (PALSAR) HH and HV backscattering coefficients above ground biomass (AGB) was consistent within structural formations (forests, woodlands open woodlands, including scrub). Across these formations, 2781 plot-based measurements (from 1139 sites) of tree diameters by species were collated, from which AGB estimated using...

10.1109/jstars.2010.2086436 article EN IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2010-12-01
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