A carbon sink-driven approach to estimate gross primary production from microwave satellite observations

Teubner, Irene; Forkel, Matthias; Camps‐Valls, Gustau; Jung, Martin; Miralles, Diego G.; Tramontana, Gianluca; Schalie, Robin van der; Vreugdenhil, Mariëtte; Moesinger, Leander; Dorigo, Wouter

doi:10.1016/j.rse.2019.04.022

Cited by 55 publications

(51 citation statements)

References 98 publications

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“…These results depend on the frequency, sensor type (active or passive) and land cover [170]. In another study, it was found that GPP can be expressed as a function of VOD through a differential equation [171].…”

Section: Vod and Carbon Balancementioning

confidence: 96%

Global Monitoring of the Vegetation Dynamics from the Vegetation Optical Depth (VOD): A Review

et al. 2020

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Vegetation is a key element in the energy, water and carbon balances over the land surfaces and is strongly impacted by climate change and anthropogenic effects. Remotely sensed observations are commonly used for the monitoring of vegetation dynamics and its temporal changes from regional to global scales. Among the different indices derived from Earth observation satellites to study the vegetation, the vegetation optical depth (VOD), which is related to the intensity of extinction effects within the vegetation canopy layer in the microwave domain and which can be derived from both passive and active microwave observations, is increasingly used for monitoring a wide range of ecological vegetation variables. Based on different frequency bands used to derive VOD, from L- to Ka-bands, these variables include, among others, the vegetation water content/status and the above ground biomass. In this review, the theoretical bases of VOD estimates for both the passive and active microwave domains are presented and the global long-term VOD products computed from various groups in the world are described. Then, major findings obtained using VOD are reviewed and the perspectives offered by methodological improvements and by new sensors onboard satellite missions recently launched or to be launched in a close future are presented.

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Section: Vod and Carbon Balancementioning

confidence: 96%

Global Monitoring of the Vegetation Dynamics from the Vegetation Optical Depth (VOD): A Review

et al. 2020

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“…Although VOD has often been used as a proxy of aboveground biomass (e.g. Liu et al, 2015;Tian et al, 2017;Brandt et al, 2018;Teubner et al, 2019), it is in fact determined by both biomass and plant water status (Konings et al, 2019). VOD variations within a day Li et al, 2017;Anderegg et al, 2018) and during soil dry-downs (Feldman et al, 2018;Zhang et al, 2019;Feldman et al, 2020) highlight the sensitivity of VOD to relative water content.…”

Section: Contribution Of Vod To Informing Plant Hydraulic Behaviormentioning

confidence: 99%

Global ecosystem-scale plant hydraulic traits retrieved using model-data fusion

Liu¹,

Holtzman²,

Konings³

2020

Preprint

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Abstract. Droughts are expected to become more frequent and severe under climate change, increasing the need for accurate predictions of plant drought response. This response varies substantially depending on plant properties that regulate water transport and storage within plants, i.e., plant hydraulic traits. It is therefore crucial to map plant hydraulic traits at a large scale to better assess drought impacts. Improved understanding of global variations in plant hydraulic traits is also needed for paramaterizing the latest generation of land surface models, many of which explicitly simulate plant hydraulic processes for the first time. Here, we use a model-data fusion approach to evaluate the spatial pattern of plant hydraulic traits across the globe. This approach integrates a plant hydraulic model with datasets derived from microwave remote sensing that inform ecosystem-scale plant water regulation. In particular, we use both surface soil moisture and vegetation optical depth (VOD) derived from the X-band JAXA Advanced Microwave Scanning Radiometer for EOS (AMSR-E). VOD is proportional to vegetation water content and therefore closely related to leaf water potential. In addition, evapotranspiration (ET) from the Atmosphere Land-Exchange Inverse model (ALEXI) is also used as a constraint to derive plant hydraulic traits. The derived traits are compared to independent data sources based on ground measurements. Using the K-means clustering method, we build six hydraulic functional types (HFTs) with distinct trait combinations – mathematically tractable alternatives to the common approach of assigning plant hydraulic values based on plant functional types. Using traits averaged by HFTs rather than by PFTs improves VOD and ET estimation accuracies in the majority of areas across the globe. The use of HFTs and/or plant hydraulic traits derived from model-data fusion in this study will contribute to improved parameterization of plant hydraulics in large-scale models and the prediction of ecosystem drought response.

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“…Droughts can have wide environmental and socio-economic impacts, ranging from their effects on climate, the carbon cycle, and food security to water availability. Droughts are typically induced by a lack of precipitation and/or an aboveaverage atmospheric demand for evapotranspiration (ET), which leads to an associated reduced availability of soil moisture in the root zone (Seneviratne et al, 2010;Teuling, 2018). The former is typically referred to as meteorological drought, whereas the latter is referred to as agricultural drought.…”

Section: Introductionmentioning

confidence: 99%

Anatomy of the 2018 agricultural drought in the Netherlands using in situ soil moisture and satellite vegetation indices

Buitink

Swank

Ploeg

et al. 2020

Hydrol. Earth Syst. Sci.

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Abstract. The soil moisture status near the land surface is a key determinant of vegetation productivity. The critical soil moisture content determines the transition from an energy-limited to a water-limited evapotranspiration regime. This study quantifies the critical soil moisture content by comparison of in situ soil moisture profile measurements of the Raam and Twente networks in the Netherlands, with two satellite-derived vegetation indices (near-infrared reflectance of terrestrial vegetation, NIRv, and vegetation optical depth, VOD) during the 2018 summer drought. The critical soil moisture content is obtained through a piece-wise linear correlation of the NIRv and VOD anomalies with soil moisture on different depths of the profile. This non-linear relation reflects the observation that negative soil moisture anomalies develop weeks before the first reduction in vegetation indices: 2–3 weeks in this case. Furthermore, the inferred critical soil moisture content was found to increase with observation depth, and this relationship is shown to be linear and distinctive per area, reflecting the tendency of roots to take up water from deeper layers when drought progresses. The relations of non-stressed towards water-stressed vegetation conditions on distinct depths are derived using remote sensing, enabling the parameterization of reduced evapotranspiration and its effect on gross primary productivity in models to study the impact of a drought on the carbon cycle.

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A carbon sink-driven approach to estimate gross primary production from microwave satellite observations

Abstract: Global estimation of Gross Primary Production (GPP) -the uptake of atmospheric carbon dioxide by plants through photosynthesis -is commonly based on optical satellite remote sensing data. This presents a source-driven

Cited by 55 publications

References 98 publications

Global Monitoring of the Vegetation Dynamics from the Vegetation Optical Depth (VOD): A Review

Global Monitoring of the Vegetation Dynamics from the Vegetation Optical Depth (VOD): A Review

Global ecosystem-scale plant hydraulic traits retrieved using model-data fusion

Anatomy of the 2018 agricultural drought in the Netherlands using in situ soil moisture and satellite vegetation indices

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