Soybean Cultivars Identification Using Remotely Sensed Image and Machine Learning Models
Abstract
:1. Introduction
2. Materials and Methods
2.1. Experimental Area and Treatments Evaluated
2.2. Image Acquisition and Multispectral Models
2.3. Using Machine Learning Models
2.4. Statistical Analysis
3. Results
3.1. Spectral Signature of Cultivars
3.2. Correlation between Variables
3.3. Scattering between Variables
3.4. Choosing the Best Model and Best Input
3.5. Confusion Matrix Using ANN’s
4. Discussion
4.1. Tested Models
4.2. Tested Inputs
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Vegetation Indices | Equations |
---|---|
AFRI1600 (Aerosol Free Vegetation Index 1600) | |
ARVI2 (Atmospherically Resistant Vegetation Index 2) | |
ATSAVI (Ajusted Transformed Soil-Ajusted VI) | |
EVI (Enhanced Vegetation Index) | |
EVI2 (Enhanced Vegetation Index 2) | |
GNDVI (Green Normalized Difference Vegetation Index) | |
GRNDVI (Green-Red NDVI) | |
GVI (Tasselled Capvegetation) | |
GVMI (Global Vegetation Moisture Index) | |
MNDVI (Modified Normalized Difference Vegetation Index) | |
NDVI (Normalized Difference Vegetation Index) | |
SBI (Tasselled Cap—brightness) | |
SIWSI (Normalized Difference 860/1640) |
Model | SBs * | VIs | SBs + VIs |
---|---|---|---|
ANN | 92.18 Aa | 88.30 Ba | 91.12 Aa |
DT | 85.88 Ac | 72.24 Bc | 85.72 Ac |
RBF | 80.94 Ab | 49.50 Be | 74.88 Af |
REPTree | 82.92 Ad | 68.32 Bd | 82.46 Ad |
RF | 89.62 Ae | 80.22 Bb | 87.94 Ab |
SVM | 73.82 Bf | 78.86 Ab | 78.24 Ae |
Model | SBs * | VIs | SBs + VIs |
---|---|---|---|
ANN | 0.91 Aa | 0.86 Ba | 0.89 Aa |
DT | 0.82 Ac | 0.66 Bc | 0.82 Ac |
RBF | 0.76 Ae | 0.37 Ce | 0.68 Bf |
REPTree | 0.79 Ad | 0.60 Bd | 0.78 Ad |
RF | 0.87 Ab | 0.75 Bb | 0.85 Ab |
SVM | 0.67 Bf | 0.73 Ab | 0.74 Ae |
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Gava, R.; Santana, D.C.; Cotrim, M.F.; Rossi, F.S.; Teodoro, L.P.R.; da Silva Junior, C.A.; Teodoro, P.E. Soybean Cultivars Identification Using Remotely Sensed Image and Machine Learning Models. Sustainability 2022, 14, 7125. https://doi.org/10.3390/su14127125
Gava R, Santana DC, Cotrim MF, Rossi FS, Teodoro LPR, da Silva Junior CA, Teodoro PE. Soybean Cultivars Identification Using Remotely Sensed Image and Machine Learning Models. Sustainability. 2022; 14(12):7125. https://doi.org/10.3390/su14127125
Chicago/Turabian StyleGava, Ricardo, Dthenifer Cordeiro Santana, Mayara Favero Cotrim, Fernando Saragosa Rossi, Larissa Pereira Ribeiro Teodoro, Carlos Antonio da Silva Junior, and Paulo Eduardo Teodoro. 2022. "Soybean Cultivars Identification Using Remotely Sensed Image and Machine Learning Models" Sustainability 14, no. 12: 7125. https://doi.org/10.3390/su14127125