0000000000358940
AUTHOR
Yongguang Zhang
showing 5 related works from this author
Beyond APAR and NPQ: Factors Coupling and Decoupling SIF and GPP Across Scales
2021
The connection between solar-induced fluorescence (SIF) and vegetation gross primary productivity is being widely investigated across spatial, temporal, and biological scales, including: a) studies at the leaf [1], [2], plant canopy [2]–[4] or satellite pixel scale [5], [6], b) temporally with studies spanning from diurnal [7] to seasonal scales [1], [3], [5], and b) biologically with studies covering various plant functional types (PFTs), e.g., crops [4], [7], deciduous [8] or evergreen forests [1], [3], in response to different sources of stress.
Global and time-resolved monitoring of crop photosynthesis with chlorophyll fluorescence
2014
Guanter, Luis et al.
Chlorophyll a fluorescence illuminates a path connecting plant molecular biology to Earth-system science
2021
Remote sensing methods enable detection of solar-induced chlorophyll a fluorescence. However, to unleash the full potential of this signal, intensive cross-disciplinary work is required to harmonize biophysical and ecophysiological studies. For decades, the dynamic nature of chlorophyll a fluorescence (ChlaF) has provided insight into the biophysics and ecophysiology of the light reactions of photosynthesis from the subcellular to leaf scales. Recent advances in remote sensing methods enable detection of ChlaF induced by sunlight across a range of larger scales, from using instruments mounted on towers above plant canopies to Earth-orbiting satellites. This signal is referred to as solar-in…
Estimating crop primary productivity with Sentinel-2 and Landsat 8 using machine learning methods trained with radiative transfer simulations
2019
Abstract Satellite remote sensing has been widely used in the last decades for agricultural applications, both for assessing vegetation condition and for subsequent yield prediction. Existing remote sensing-based methods to estimate gross primary productivity (GPP), which is an important variable to indicate crop photosynthetic function and stress, typically rely on empirical or semi-empirical approaches, which tend to over-simplify photosynthetic mechanisms. In this work, we take advantage of all parallel developments in mechanistic photosynthesis modeling and satellite data availability for an advanced monitoring of crop productivity. In particular, we combine process-based modeling with …
Reply to Magnani et al.: Linking large-scale chlorophyll fluorescence observations with cropland gross primary production
2014
Guanter, Luis et al.