Aboveground Biomass Mapping of Crops Supported by Improved CASA Model and Sentinel-2 Multispectral Imagery
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Datasets and Processing
2.2.1. Meteorological Data
2.2.2. Remote Sensing Data
2.2.3. Measured Field Data
2.3. Methods
2.3.1. Processing Flow of the Original CASA Model
2.3.2. Vegetation Indices
2.3.3. Conversion of NPP into Aboveground Biomass
2.3.4. Accuracy Assessment
2.4. Workflow
3. Results
3.1. Modeling of FPAR Based on Red-Edge Vegetation Indices
3.2. FPAR Inversion Results Based on Red-Edge Vegetation Indices
3.3. Improved Inversion Results Based on Red-Edge Vegetation Indices
3.3.1. Cumulative NPP and Biomass of Crops
3.3.2. Aboveground Biomass Estimation Accuracy of Crops
3.4. Seasonal Variation and Factors Influencing Crops Aboveground Biomass
4. Discussion
4.1. Accuracy Differences of Various Vegetation Indices
4.2. Mapping Differences of Various Models
4.3. Features of Improved CASA Model
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
NPP | Net primary productivity | NPP = APAR × LUE |
APAR | Photosynthetically active radiation absorbed by the vegetation canopy | APAR = PAR × FPAR |
FPAR | Photosynthetically active radiation absorption proportion | FPARwheat = 0.8287 × NDVIred-edge + 0.1889 FPARmaize = 0.1023 × SRred-edge + 0.3011 |
PAR | Photosynthetically active radiation | PAR = SOL × 0.5 |
SOL | Monthly radiation | Defined as the total radiation of crops in main growth stage |
LUE | Actual light use efficiency | LUE = Tε1 × Tε2 × Wε × LUEmax |
LUEmax | Maximum LUE | For winter wheat, LUEmax = 1.95, for summer maize, LUEmax = 2.55 |
Tε1 | Effects of temperature stress | Tε1 = 0.8 + 0.02 × Topt − 0.0005 × Topt2 |
Tε2 | Effects of temperature stress | Tε2 = 1.184/{1 + exp [0.2 × (Topt-10-Tx)]} × 1/{1 + exp[0.3 × (−Topt-10 + Tx)]} |
Topt | Optimal temperature | Defined as the air temperature in the month when the NDVI reaches its maximum |
Tx | Monthly temperature | Defined as monthly temperature of crops in main growth stage |
Wε | Effects of water stress | Wε = (1 − (1 + LSWI)/(1 + LSWImax)) + 0.5 |
LSWI | Land Surface Water Index | LSWI = ()/() |
B | Aboveground biomass | |
Ratio of the aboveground biomass to the whole vegetation | For winter wheat, .90, for summer maize, .91, | |
The C ratio of a crop | For winter wheat, .49, for summer maize, .47, | |
NDVI | Normalized Difference Vegetation Index | |
NDVIred-edge | Red-Edge Normalized Difference Vegetation Index | |
Simple Ratio Vegetation Index | ||
MSR | Modified Simple Ratio Vegetation Index | |
MSRred-edge | Modified Red-Edge Simple Ratio Vegetation Index | |
SRred-edge | Red-Edge Simple Ratio Vegetation Index | |
EVI | Enhanced Vegetation Index |
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Satellite Data | Band | Center Wavelength (nm) | Resolution (m) | Source |
---|---|---|---|---|
Sentinel-2 | B1 | 443 | 60 | European Space Agency (https://sentinel.esa.int/web/sentinel/, accessed on 6 November 2020) |
B2 | 490 | 10 | ||
B3 | 560 | 10 | ||
B4 | 665 | 10 | ||
B5 | 705 | 20 | ||
B6 | 740 | 20 | ||
B7 | 783 | 20 | ||
B8 | 842 | 10 | ||
B8A | 865 | 20 | ||
B9 | 940 | 60 | ||
B10 | 1375 | 60 | ||
B11 | 1610 | 20 | ||
B12 | 2190 | 20 | ||
QA10 | — | 10 | ||
QA20 | — | 20 | ||
QA60 | — | 60 | ||
MCD15A3H | FPAR | — | 500 | NASA LP DAAC at the USGS EROS Center (https://lpdaac.usgs.gov/products/mcd15a3hv006/, accessed on 6 November 2020) |
LAI | — | 500 |
Parameter | Unit | Description | Source |
---|---|---|---|
Meteorological Data | |||
Temperature | °C | Near-surface (2 m) air temperature | China Meteorological Data Service Center (CMDSC) |
Radiation | MJ/m2 | Surface downward shortwave radiation | Angstrom model |
Measured Field Data | |||
Winter Wheat Aboveground Biomass | g/m2 | Aboveground biomass at maturity stage | Field measurements |
Summer Maize Aboveground Biomass | g/m2 | Aboveground biomass at maturity stage | Field measurements |
Crops | Vegetation Indices | Regression Model | R2 |
---|---|---|---|
Winter wheat | y = 0.8287x + 0.1889 | 0.72 | |
y = 0.1656x + 0.7371 | 0.71 | ||
y = 0.1619x + 0.0979 | 0.69 | ||
Maize | y = 0.7081x − 0.0026 | 0.45 | |
y = 0.1023x + 0.3011 | 0.53 | ||
y = 0.5270x + 0.3305 | 0.40 |
Vegetation Indices | Descriptions | Equation | Reference | |
---|---|---|---|---|
It corrects for some atmospheric conditions and canopy background noise. | (5) | [40] | ||
It can distinguish green leaves from other objects and estimate the relative biomass. | (6) | [41] | ||
It is used to assess vegetation biomass and growth, which reduces the impact of atmosphere and topography. | (7) | [42] | ||
It is an improved version of SR, which is sensitive to vegetation biophysical parameters. | (8) | [43] | ||
It uses bands in the red edge and incorporates a correction for leaf specular reflection. | (9) | [44] | ||
It is similar to NDVI but capitalizes on the sensitivity of the vegetation red edge to small changes in canopy chlorophyll. | (10) | [45] | ||
Combined with red band and near infrared band, it has strong robustness in a wide range. However, it saturates in dense vegetation conditions. | (11) | [46] |
Crops | Carbon Content Ratio | Dry Matter Ratio | Root-Shoot Ratio | Moisture Content (%) | |
---|---|---|---|---|---|
Economic Production | Residual Carbon Ratio | ||||
Winter wheat | 0.39 | 0.49 | 0.85 | 0.11 | 12.5 |
Maize | 0.39 | 0.47 | 0.78 | 0.09 | 13.5 |
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Fang, P.; Yan, N.; Wei, P.; Zhao, Y.; Zhang, X. Aboveground Biomass Mapping of Crops Supported by Improved CASA Model and Sentinel-2 Multispectral Imagery. Remote Sens. 2021, 13, 2755. https://doi.org/10.3390/rs13142755
Fang P, Yan N, Wei P, Zhao Y, Zhang X. Aboveground Biomass Mapping of Crops Supported by Improved CASA Model and Sentinel-2 Multispectral Imagery. Remote Sensing. 2021; 13(14):2755. https://doi.org/10.3390/rs13142755
Chicago/Turabian StyleFang, Peng, Nana Yan, Panpan Wei, Yifan Zhao, and Xiwang Zhang. 2021. "Aboveground Biomass Mapping of Crops Supported by Improved CASA Model and Sentinel-2 Multispectral Imagery" Remote Sensing 13, no. 14: 2755. https://doi.org/10.3390/rs13142755