ECOSTRESS estimates gross primary production with fine spatial resolution for different times of day from the International Space Station

Abstract

Accurate estimation of gross primary production (GPP), the amount of carbon absorbed by plants via photosynthesis, is of great importance for understanding ecosystem functions, carbon cycling, and climate-carbon feedbacks. Remote sensing has been widely used to quantify GPP at regional to global scales. However, polarorbiting satellites (e.g., Landsat, Sentinel, Terra, Aqua, Suomi NPP, JPSS, OCO-2) lack the capability to examine the diurnal cycles of GPP because they observe the Earth's surface at the same time of day. The Ecosystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS), launched in June 2018, observes the land surface temperature (LST) at different times of day with high spatial resolution (70 m × 70 m) from the International Space Station (ISS). Here, we made use of ECOSTRESS data to predict instantaneous GPP with high spatial resolution for different times of day using a data-driven approach based on machine learning. The predictive GPP model used instantaneous ECOSTRESS LST observations along with the daily enhanced vegetation index (EVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS), land cover type from the National Land Cover Database (NCLD), and instantaneous meteorological data from the ERA5 reanalysis dataset. Our model estimated instantaneous GPP across 56 flux tower sites fairly well (R 2 = 0.88, Root Mean Squared Error (RMSE) = 2.42 μmol CO 2 m − 2 s − 1 ). The instantaneous GPP estimates driven by ECOSTRESS LST captured the diurnal variations of tower GPP for different biomes. We then produced multiple high resolution ECOSTRESS GPP maps for the central and northern California. We found distinct changes in GPP at different times of day (e.g., higher in late morning, peak around noon, approaching zero at dusk), and clear differences in productivity across landscapes (e.g., savannas, croplands, grasslands, and forests) for different times of day. ECOSTRESS GPP also captured the seasonal variations in the diurnal cycling of photosynthesis. This study demonstrates the feasibility of using ECOSTRESS data for producing instantaneous GPP (i.e., GPP for the acquisition time of the ECOSTRESS data) for different times of day. The ECOSTRESS GPP can shed light on how plant photosynthesis and water use vary over the course of the diurnal cycle and inform agricultural management and future improvement of terrestrial biosphere/land surface models.

Reviews and syntheses: Ongoing and emerging opportunities to improve environmental science using observations from the Advanced Baseline Imager on the Geostationary Operational Environmental Satellites

“…Atmospheric attenuation due to water vapor requires atmospheric correction of thermal data collected from satellites and also limits surface temperature retrieval to thermal bands that have the lowest atmospheric absorption (Sun and Pinker, 2003). A single-channel approach requires the use of one thermal channel within an atmospheric window at around 10 µm and radiative transfer modeling to simulate atmospheric transmittance and emission of longwave radiation (Li et al, 2013;Pinker et al, 2019). With known land surface emissivity and atmospheric profiles and simulated atmospheric transmittance/emission, surface temperature can be retrieved through the inversion of a radiative transfer equation that explains the different components of at-sensor radiance (Li et al, 2013).…”

“…A single-channel approach requires the use of one thermal channel within an atmospheric window at around 10 µm and radiative transfer modeling to simulate atmospheric transmittance and emission of longwave radiation (Li et al, 2013;Pinker et al, 2019). With known land surface emissivity and atmospheric profiles and simulated atmospheric transmittance/emission, surface temperature can be retrieved through the inversion of a radiative transfer equation that explains the different components of at-sensor radiance (Li et al, 2013). Since accurate atmospheric profiles over a study area can be difficult to obtain, a split-window technique can be used to correct atmospheric absorption to estimate surface temperature from at-sensor radiance in two thermal bands with differential water vapor absorption (Li et al, 2013;Ulivieri and Cannizzaro, 1985).…”

“…With known land surface emissivity and atmospheric profiles and simulated atmospheric transmittance/emission, surface temperature can be retrieved through the inversion of a radiative transfer equation that explains the different components of at-sensor radiance (Li et al, 2013). Since accurate atmospheric profiles over a study area can be difficult to obtain, a split-window technique can be used to correct atmospheric absorption to estimate surface temperature from at-sensor radiance in two thermal bands with differential water vapor absorption (Li et al, 2013;Ulivieri and Cannizzaro, 1985). Split-window techniques were used in earlier estimates of surface temperature from GOES thermal data, and they are based on the relationship between surface temperature and the difference in temperature between two adjacent thermal bands with high emissivity and low atmospheric absorption typically centered at 11 and 12 µm (Li et al, 2013;Sun and Pinker, 2003).…”

“…The ABI features three longwave infrared bands with spatial resolutions of about 2 km for measuring land surface temperature (LST) -the skin temperature of the uppermost layer of the land surface -including correction for atmospheric moisture (Yu et al, 2012). Since the emission from the land surface diverges from a blackbody, the knowledge of land surface emissivity is a crucial component for the retrieval of LST from at-sensor radiance (Li et al, 2013;Sun and Pinker, 2003). Global emissivity data may be gathered by consulting compiled tables of emissivities for various land covers along with land cover classifications of the landscape (Li et al, 2013).…”

Linking Remotely Sensed Carbon and Water Use Efficiencies with In Situ Soil Properties

“…Estimates of global GPP are also available from the Max Planck Institute for Biogeochemistry (MPI-BGC) based on upscaling of eddy covariance-based measurements [41]. Currently, NASA ECOSTRESS onboard the space station is producing ET and WUE starting from July 2018 [42] and can also lead to instantaneous GPP estimates [43]. In addition, satellite-based solar-induced fluorescence (SIF) has been related to GPP [44][45][46].…”