A5027601247- Remote Sensing in Agriculture
- Species Distribution and Climate Change
- Plant Water Relations and Carbon Dynamics
- Atmospheric and Environmental Gas Dynamics
- Climate variability and models
- Ecology and Vegetation Dynamics Studies
- Land Use and Ecosystem Services
- Forest ecology and management
- Remote Sensing and LiDAR Applications
- Forest Management and Policy
- Data Analysis with R
- Fire effects on ecosystems
- Hydrology and Watershed Management Studies
- Scientific Computing and Data Management
- Cryospheric studies and observations
- Plant and animal studies
- Climate change and permafrost
- Leaf Properties and Growth Measurement
- Research Data Management Practices
- Science and Climate Studies
- Meteorological Phenomena and Simulations
- Semantic Web and Ontologies
- Plant responses to elevated CO2
- Urban Heat Island Mitigation
- Wildlife Ecology and Conservation
Goddard Space Flight Center
2020-2025
Earth System Science Interdisciplinary Center
2022
Pacific Northwest National Laboratory
2018-2021
Boise State University
2021
Joint Global Change Research Institute
2018-2020
Boston University
2016-2019
University of Delaware
2014-2016
The 2017–2027 National Academies' Decadal Survey, Thriving on Our Changing Planet, recommended Surface Biology and Geology (SBG) as a "Designated Targeted Observable" (DO). SBG DO is based the need for capabilities to acquire global, high spatial resolution, visible shortwave infrared (VSWIR; 380–2500 nm; ~30 m pixel resolution) hyperspectral (imaging spectroscopy) multispectral midwave thermal (MWIR: 3–5 μm; TIR: 8–12 ~60 measurements with sub-monthly temporal revisits over terrestrial,...
Abstract. Reduced-complexity climate models (RCMs) are critical in the policy and decision making space, directly used within multiple Intergovernmental Panel on Climate Change (IPCC) reports to complement results of more comprehensive Earth system models. To date, evaluation RCMs has been limited a few independent studies. Here we introduce systematic form Reduced Complexity Model Intercomparison Project (RCMIP). We expect RCMIP will extend over phases, with Phase 1 being first. In 1, focus...
Over the last decades, climate science has evolved rapidly across multiple expert domains. Our best tools to capture state-of-the-art knowledge in an internally self-consistent modeling framework are increasingly complex fully coupled Earth System Models (ESMs). However, computational limitations and structural rigidity of ESMs mean that full range uncertainties domains difficult with alone. The choice instead more computationally efficient reduced complexity models (RCMs), which...
In an era of rapid global change, our ability to understand and predict Earth's natural systems is lagging behind monitor measure changes in the biosphere. Bottlenecks informing models with observations have reduced capacity fully exploit growing volume variety available data. Here, we take a critical look at information infrastructure that connects ecosystem modeling measurement efforts, propose roadmap community cyberinfrastructure development can reduce divisions between empirical...
Abstract The terrestrial carbon cycle is a major source of uncertainty in climate projections. Its dominant fluxes, gross primary productivity (GPP), and respiration (in particular soil respiration, R S ), are typically estimated from independent satellite-driven models upscaled situ measurements, respectively. We combine carbon-cycle flux estimates partitioning coefficients to show that historical global GPP irreconcilable. When we estimate based on measurements some assumptions about :GPP...
Summary Leaf traits are essential for understanding many physiological and ecological processes. Partial least squares regression (PLSR) models with leaf spectroscopy widely applied trait estimation, but their transferability across space, time, plant functional types (PFTs) remains unclear. We compiled a novel dataset of paired spectra, 47 393 records > 700 species eight PFTs at 101 globally distributed locations multiple seasons. Using this dataset, we conducted an unprecedented...
Abstract Like leaves, floral coloration is driven by inherent optical properties, which are determined pigments, scattering structure, and thickness. However, establishing the relative contribution of these factors to canopy spectral signals usually limited in situ observations. Modeling flowering dynamics (e.g., blooming duration, spatial distribution) at landscape scale may reveal insights into ecological processes phenological adaptations environmental changes. Multi‐temporal visible...
Abstract We stand at the threshold of a transformative era in Earth observation, marked by space‐borne visible‐to‐shortwave infrared (VSWIR) imaging spectrometers that promise consistent global observations ecosystem function, phenology, and inter‐ intra‐annual change. However, full value repeat spectroscopy, information embedded within different temporal scales, reliability existing algorithms across diverse types vegetation phenophases have remained elusive due to absence suitable...
Abstract Secondary forest regrowth shapes community succession and biogeochemistry for decades, including in the Upper Great Lakes region. Vegetation models encapsulate our understanding of function, whether can reproduce multi‐decadal patterns is an indication ability to predict responses future change. We test a vegetation model simulate C cycling composition during 100 years following stand‐replacing disturbance, asking (a) Which processes parameters are most important accurately Midwest...
Abstract. Canopy radiative transfer is the primary mechanism by which models relate vegetation composition and state to surface energy balance, important light- temperature-sensitive plant processes as well understanding land–atmosphere feedbacks. In addition, certain parameters (e.g., specific leaf area, SLA) that have an outsized influence on model behavior can be constrained observations of shortwave reflectance, thus reducing predictive uncertainty. Importantly, calibrating against...
Abstract This paper summarizes the open community conventions developed by Ecological Forecasting Initiative (EFI) for common formatting and archiving of ecological forecasts metadata associated with these forecasts. Such standards are intended to promote interoperability facilitate forecast communication, distribution, validation, synthesis. For output files, we first describe convention conceptually in terms global attributes, dimensions, forecasted variables, ancillary indicator...
Abstract Current biodiversity metrics derived from remote sensing data are typically applied to small local areas, require significant training data, and not easily extensible globally. Here we propose the mathematical concept of intrinsic dimensionality (ID) as a method quantify terrestrial vegetation variability without need for in situ data. We apply this technique airborne imaging spectroscopy Surface Biology Geology High Frequency Time series (SHIFT) campaign, with weekly overflights...
Abstract. Here we present results from the first phase of Reduced Complexity Model Intercomparison Project (RCMIP). RCMIP is a systematic examination reduced complexity climate models (RCMs), which are used to complement and extend insights more complex Earth System Models (ESMs), in particular those participating Sixth Coupled (CMIP6). In Phase 1 RCMIP, with 14 namely ACC2, AR5IR (2 3 box versions), CICERO-SCM, ESCIMO, FaIR, GIR, GREB, Hector, Held et al. two layer model, MAGICC, MCE, OSCAR...
Abstract Spectroscopic reflectance data provide novel information on the properties of Earth's terrestrial and aquatic surfaces. Until recently, imaging spectroscopy missions were dependent mainly airborne instruments, such as Next Generation Airborne Visible InfraRed Imaging Spectrometer (AVIRIS‐NG), providing limited spatial temporal observations. Currently, there is an emergence spaceborne missions, which require advances in end‐to‐end model support for traceability studies. To this...
Abstract The retrieval algorithms used for optical remote sensing satellite data to estimate Earth's geophysical properties have specific requirements spatial resolution, temporal revisit, spectral range and instrument signal‐to‐noise ratio (SNR) performance meet biogeoscience objectives. Studies surface from hyperspectral use a of sensitive various sources spectroscopic uncertainty, which are in turn influenced by mission architecture choices. Retrieval vary across scientific fields may be...
Abstract Process-based ecosystem models help us understand and predict processes, but using them has long involved a difficult choice between performing data- labor-intensive site-level calibrations or relying on general parameters that may not reflect local conditions. Hierarchical Bayesian (HB) calibration provides third option frees modelers from assuming model to be completely generic site-specific allows formal distinction prediction at known sites “out-of-sample” new sites. Here, we...
Over the last decades, climate science has evolved rapidly across multiple expert domains. Our best tools to capture state-of-the-art knowledge in an internally self-consistent modelling framework are increasingly complex fully coupled Earth System Models (ESMs). However, computational limitations and structural rigidity of ESMs mean that full range uncertainties domains difficult with alone. The choice instead more computationally efficient reduced complexity models (RCMs), which...
Abstract In this analysis of the spatial resolving power thermal imagery products we focus on four satellite instruments that are used in research and applications, for example, to monitor land surface temperature derive evapotranspiration. These imagers Landsat 7, 8, 9, as well ECOsystem Spaceborne Thermal Radiometer Experiment Space Station (ECOSTRESS). We compiled sets close‐in‐time, day‐time images bridges surrounded by open water bodies, captured each during cloud‐free moments. Where...