Future spaceborne imaging spectroscopy missions will revolutionize remote sensing: Here we simulate the first dynamic globally-gridded imaging spectroscopy dataset for pre-launch characterization of expected science and applications and mission design.
By the end of this decade, the scientific community at large with be flush with imaging spectroscopy data, often colloquially referred to as hyperspectral data. Even now, continuing and novel missions are providing spectroscopy data at various temporal, spatial, and spectral resolutions at various places across the globe. For instance, the SHIFT campaign (or Surface Biology and Geology High-Frequency Time Series), has provides repeat spectroscopy datasets across a single growing season in the Santa Barbara, California area with a short revisit time. Where SHIFT prioritizes temporal frequency, the ABoVE experiment (Arctic-Boreal Vulnerability Experiment) focuses on a specific environment and use-case of spectroscopy data. Linking these two themes together, the new EMIT mission (Earth Surface Mineral Dust Source Investigation), focuses on exploring the impacts of dust on Earth’s climate regulation across global drylands.
Yet, one main challenge with all of these and other spectroscopy datasets is their lack of continuity with each other. Indeed, most of the globe has been imaged using imaging spectroscopy at some point. However, the temporal, spectral, and spatial discrepancies between all of these datasets, not to mention data privacy and acquisition constraints, make it quite challenging to use spectroscopy data in large spatial scale studies. And while there are hundreds-to-thousands of satellites imaging the Earth each day to collect important data, there has yet to be a globally-consistent imaging spectrometer that can answer the same questions that the aforementioned missions seek to investigate.
Imaging spectroscopy data provides invaluable insight that was limited from previous multispectral imagers due to restricted spectral resolutions (or quantity of light being measured). The reflectance of light from Earth’s surfaces – particularly light that the human eye cannot perceive – offers information into the vegetation composition, physics, health, and productivity of these landscapes.
Soon an emergence in Earth observations using imaging spectroscopy will take place; in early 2022, DLR (the German Aerospace Center) launched the Environmental Mapping and Analysis Program (ENMAP) and NASA launched EMIT. Building off of these early global missions, by the end of this decade NASA will have launched the Surface Biology and Geology (SBG) mission and the European Space Agency, or ESA, will have launched the Copernicus Hyperspectral Imaging Mission for the Environment (CHIME). Together, SBG and CHIME will provide global datasets with state-of-the-art temporal, spatial, and spectral resolution. Importantly, there is a large push for NASA and ESA to work collaboratively to accomplish more than either agency could alone, promoting the next generation of international collaboration for Earth Observation.
Before the launch of these next-generation missions, mission requirements and dataset workflows will need to be well outlined and understood to provide pre-launch characterization of expected science and applications products. In this regard, end-to-end (E2E) simulators will play an important role in supporting this cause. E2E simulators quantify instrument, retrieval, and algorithmic uncertainties and the propagation of these uncertainties under potential future workflows. Radiative transfer models, which model surface-leaving reflectances, combined with process-based models, such as land-surface models, can also inform E2E as the basis of Observing System Simulation Experiments, or OSSE’s.
That is where LPJ-PROSAIL comes in. LPJ-PROSAIL is a dynamic global vegetation model (LPJ) which simulates the vegetation of Earth, that has been linked with the radiative transfer model PROSAIL. LPJ simulates the vegetation of Earth based on the position, climate, soil, and CO2 concentration of each grid cell. The vegetation is then fed into PROSAIL, which simulates reflectance spectroscopy data at the same globally-gridded spatial resolutions. In this way, LPJ-PROSAIL represents the first possibility of obtaining globally-gridded imaging spectroscopy data. Although the data is simulated, LPJ provides sufficient fidelity with in-situ spectroscopy datasets and allows for the development of mission design and future workflows to help facilitate pre-launch characterization for both SBG and CHIME missions.
In the not-too-distant future, imaging spectroscopy from space has the promise to measure and monitor the health and productivity of Earth’s ecosystems with accuracy that has not yet been observed. This form of remote sensing represents the future of Earth Observation and will allow us the tools to best understand our planet and how we can potentially inhabit it in the most sustainable and harmonious ways possible.
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Authors: Benjamin Poulter, Bryce Currey, Leonardo Calle, Alexey N. Shiklomanov, Cibele H. Amaral, E. N. Jack Brookshire, Petya Campbell, Adam Chlus, Kerry Cawse-Nicholson, Fred Huemmrich, Charles E. Miller , Kimberley Miner, Zoe Pierrat, Ann M. Raiho, David Schimel, Shawn Serbin, William K. Smith, Natasha Stavros, Jochen Stutz, Phil Townsend, David R. Thompson, and Zhen Zhang
Online link: https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2022JG006935. Open access.