Prediction of Open Woodland Transpiration Incorporating Sun-Induced Chlorophyll Fluorescence and Vegetation Structure
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data
2.2.1. Transpiration Field Measurements
2.2.2. LiDAR Data and Vegetation Structure
2.2.3. Satellite Remote Sensing Data
2.3. Method
2.3.1. Model Framework Overview
2.3.2. Radiative Transfer Models
2.3.3. Determination of 3D Vegetation Structure
2.3.4. LAI Partitioning
2.3.5. Two-Step Parameter Inversion
2.3.6. Model Simulation
3. Results
3.1. Relationships between SIF and T
3.1.1. Correlations between SIF and T at Multiple Temporal Scales
3.1.2. Correlation between SIF and T from the Canopy and Understory
3.1.3. Timeseries of SIF and T Comparison across All Sites
3.2. Influence of Environmental Factors on SIF–T Correlation
3.2.1. Influence of Soil Reflectance and LAI on SIF–T Correlations
3.2.2. Influence of Canopy Leaf Area Index, Temperature, and Rainfall on SIF–T Correlations
4. Discussion
4.1. SIF Emission Performance in Explaining T Variation
4.2. Further Research
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Site | Symbol | Collection Period | Environmental Situation | Coordinates | Annual Mean T (mm/h) | FVC | Woodland Category |
---|---|---|---|---|---|---|---|
Mallee Cliffs E. largiflorens (Black Box) sparse site | MCBB_S | June 2019–May 2021 | Highly saline groundwater | 34°19′37″S, 142°23′21″E | 0.003 | 0.12 | Sparse |
Mallee Cliffs E. largiflorens (Black Box) moderate sparse site | MCBB_MS | June 2019–May 2021 | Fresh groundwater lens | 34°19′44″S, 142°22′46″E | 0.006 | 0.25 | Moderate-sparse |
Lindsay Forest E. camaldulensis (River Red Gum) open woodland site | LFRRG_OW | Oct 2019–May 2021 | ~80 m from River Murray Channel | 34°3′44″S, 141°2′40″E | 0.020 | 0.5 | Open woodland |
Parameter | Symbol | Value Range | Step | Unit |
---|---|---|---|---|
leaf mesophyll structure parameter | N | 1–3 | 1 | unitless |
leaf chlorophyll a + b content | Cab | 10–100 | 8 | μg cm−2 |
total carotenoid content | Ccar | 0.25 Cab | - | μg cm−2 |
senescence material | Cs | 0–0.3 | 0.1 | unitless |
leaf dry matter content | Cw | 0.001–0.05 | 0.008 | mg cm−2 |
leaf water content | Cw | 0.001–0.15 | 0.045 | cm |
leaf area density | LAD | 0.1–2 | 0.4 | m2 m−3 |
understory LAI | LAIu | 0.1, 1, 2 | - | m2 m−2 |
soil reflectance | Rsoil | 0.1, 0.2, 0.4 | - | unitless |
Variable | Value | Source |
---|---|---|
Scene area | 50 × 50 m | - |
Vegetation structure | - | LiDAR |
SZA, SAA | Calculate based on simulation time | - |
VZA, VAA | 0°, 0° | - |
PAR | 0–2000 umol m−2 s−1 | Himawari-8 |
LAD | 0.1–2 m−2 m−3 | Retrieved based on two-step inversion and MODIS LAI |
BAD | 0.5 m−2 m−3 | - |
Leaf Ref and Tran | - | Retrieved based on two-step inversion, simulate by PROSPECT-5 with VIS2 |
EF-matrix | - | Retrieved based on two-step inversion, simulate by Fluspect-B with VIS2 |
LAIu | 0.1–2 m−2 m−2 | Retrieved based on two-step inversion |
Mean understory Ref and Tran at PAR and NIR region | 0.2, 0.4 0.2, 0.4 | - |
Mean soil Ref at PAR and NIR region | 0.1–0.5 | Retrieved based on two-step inversion |
All Sites | MCBB_S | MCBB_MS | LFRRG_OW | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Hourly | Daily | Monthly | Hourly | Daily | Monthly | Hourly | Daily | Monthly | Hourly | Daily | Monthly | |
SIFred | 0.35 | 0.38 | 0.39 | 0.18 | 0.12 | 0.08 * | 0.49 | 0.53 | 0.62 | 0.36 | 0.27 | 0.25 |
SIFvalley | 0.44 | 0.47 | 0.49 | 0.15 | 0.10 | 0.06 * | 0.53 | 0.60 | 0.72 | 0.37 | 0.27 | 0.27 |
SIFwater vapour | 0.82 | 0.87 | 0.90 | 0.27 | 0.28 | 0.29 | 0.58 | 0.68 | 0.81 | 0.48 | 0.43 | 0.51 |
SIFNIR | 0.86 | 0.90 | 0.93 | 0.33 | 0.39 | 0.44 | 0.57 | 0.66 | 0.80 | 0.54 | 0.52 | 0.68 |
SIFO2-A | 0.85 | 0.90 | 0.93 | 0.34 | 0.41 | 0.47 | 0.53 | 0.64 | 0.78 | 0.54 | 0.55 | 0.73 |
All Sites | MCBB_S | MCBB_MS | LFRRG_OW | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Total | Canopy | Understory | Total | Canopy | Understory | Total | Canopy | Understory | Total | Canopy | Understory | |
SIFred | 0.81 | 0.58 | 0.26 | 0.20 | 0.30 | 0.13 | 0.55 | 0.41 | 0.50 | 0.46 | 0.52 | 0.26 |
SIFvalley | 0.79 | 0.65 | 0.30 | 0.18 | 0.22 | 0.12 | 0.58 | 0.49 | 0.54 | 0.45 | 0.49 | 0.27 |
SIFwater vapour | 0.80 | 0.85 | 0.65 | 0.25 | 0.34 | 0.22 | 0.58 | 0.59 | 0.57 | 0.46 | 0.53 | 0.35 |
SIFNIR | 0.81 | 0.86 | 0.74 | 0.29 | 0.40 | 0.26 | 0.57 | 0.59 | 0.56 | 0.48 | 0.57 | 0.37 |
SIFO2-A | 0.81 | 0.85 | 0.75 | 0.30 | 0.40 | 0.27 | 0.56 | 0.54 | 0.51 | 0.48 | 0.55 | 0.38 |
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Gao, S.; Woodgate, W.; Ma, X.; Doody, T.M. Prediction of Open Woodland Transpiration Incorporating Sun-Induced Chlorophyll Fluorescence and Vegetation Structure. Remote Sens. 2024, 16, 143. https://doi.org/10.3390/rs16010143
Gao S, Woodgate W, Ma X, Doody TM. Prediction of Open Woodland Transpiration Incorporating Sun-Induced Chlorophyll Fluorescence and Vegetation Structure. Remote Sensing. 2024; 16(1):143. https://doi.org/10.3390/rs16010143
Chicago/Turabian StyleGao, Sicong, William Woodgate, Xuanlong Ma, and Tanya M. Doody. 2024. "Prediction of Open Woodland Transpiration Incorporating Sun-Induced Chlorophyll Fluorescence and Vegetation Structure" Remote Sensing 16, no. 1: 143. https://doi.org/10.3390/rs16010143
APA StyleGao, S., Woodgate, W., Ma, X., & Doody, T. M. (2024). Prediction of Open Woodland Transpiration Incorporating Sun-Induced Chlorophyll Fluorescence and Vegetation Structure. Remote Sensing, 16(1), 143. https://doi.org/10.3390/rs16010143