Theme 2

About

Developing sensing technologies and observational data products to monitor terrestrial ecosystems across biomes, timescales, and hydro-climatic regimes.

(Chang et al., 2020, Agricultural and Forest Meteorology)

Two Studies:

Systematic Assessment of Retrieval Methods for Canopy Far-Red Solar-Induced Chlorophyll Fluorescence Using High-Frequency Automated Field Spectroscopy (Chang et al., 2020, JGR Biogeosciences)
An Unmanned Aerial System (UAS) for concurrent measurements of solar-induced chlorophyll fluorescence and hyperspectral reflectance toward improving crop monitoring (Chang et al., 2020, Agricultural and Forest Meteorology)

Design a novel system to simultaneously measure high-quality SIF and hyperspectral reflectance,which has been successfully mounted onto a ground tower and an airborne unmanned aerial vehicle (UAV) platform, respectively

Develop two novel high-resolution (~5km) time series of spatially contiguous SIF for the globe, using machine learning algorithms constrained by known physiological dynamics:

High-Resolution Global Contiguous SIF of OCO-2 (Yu et al., 2019, Geophysical Research Letters)
A framework for harmonizing multiple satellite instruments to generate a long-term global high spatial-resolution solar-induced chlorophyll fluorescence (SIF) (Wen et al., 2020, Remote Sensing of Environment)

The first data product used a hybrid approach that combined artificial neural network (ANN) algorithms and physiological constraints to gap-fill the native SIF measurements from the Orbiting Carbon Observatory (OCO)-2 satellite mission for the period 2014-2018 at bi-weekly resolution.

The second product developed a long-term (2002-2018) harmonized SIF dataset at monthly and ~5km resolution by fusing multiple satellite SIF (from SCIAMACHY and GOME-2) utilizing ANN and Random Forest (RF), respectively, and cumulative probability distribution (CDF) matching.

(Yu et al., 2019, Geophysical Research Letters)

(Wang et al., 2019, Geophysical Research Letters)

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(Kira et al., 2021, Remote Sensing of Environment)

Studies:

Phenology Dynamics of Dryland Ecosystems Along the North Australian Tropical Transect Revealed by Satellite Solar-Induced Chlorophyll Fluorescence (Wang et al., 2019, Geophysical Research Letters)
Partitioning Net Ecosystem Exchange (NEE) of CO2 Using Solar-Induced Chlorophyll Fluorescence (SIF) (Kira et al., 2021, Remote Sensing of Environment)

Apply the instruments and data product to investigate the carbon cycle. In collaboration with ecologists in Australia, we integrated the in-situ GPP fluxes with satellite observations along the North Australian Tropical Transect (NATT) as a testbed and found that SIF outperformed other reflectance-based vegetation indicators mainly because, unlike reflectance, it is not contaminated by background soil and its total signal is contributed by mixed plant species in additive way.

We as well harness SIF remote sensing and eddy covariance (EC) measurements to close the long-standing knowledge gap in ecosystem carbon flux partitioning.

(Wen et al., 2022, Water Resources Research)

Study:

Resolve the Clear-Sky Continuous Diurnal Cycle of High-Resolution ECOSTRESS Evapotranspiration and Land Surface Temperature (Wen et al., 2022, Water Resources Research)

Develop new satellite products of evapotranspiration (ET) and land surface temperature (LST) from thermal remote sensing with high resolution, by resolving the full continuous diurnal cycle of 70m ET and LST from the sporadic ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) measurements.