Table 3.
Studies targeting water quality monitoring from RS imagery using AI (where “/” means none. Note that it is ordered chronologically to show trends in data type and model usage) (See the Abbreviations for a full list of the acronyms).
| Reference | Method | Model Comparison | RS Data Type | Evaluation Metrics |
|---|---|---|---|---|
| Chebud et al. (2012) [55] | DNN | / | Landsat TM | RMSE, R2 |
| Wang et al. (2017) [56] | SVR | index methods | spectroradiometer, water samples | RMSE, RPD, R2 |
| Lee and Lee (2018) [57] | LSTM | DNN, RNN | water quality time series | RMSE |
| Wang et al. (2019) [58] | LSTM | / | water quality time series | accuracy, cross-correlation |
| Pu et al. (2019) [59] | CNN | RF, SVM | Landsat-8 | accuracy |
| Liu et al. (2019) [60] | LSTM | ARIMA, SVM | IoT data | MSE |
| Chowdury et al. (2019) [61] | MLP | / | IoT data | threshold value |
| Hafeez et al. (2019) [62] | DNN | CB, RF, SVR | Landsat | accuracy, relative variable importance |
| Li et al. (2019) [63] | RNN–DS hybrid | GRU, LSTM, SRN, SVR | water quality time series | MAE, MAPE, RMSE |
| Randrianiaina et al. (2019) [64] | DNN | / | Landsat-8 | RMSE, R2 |
| Yu et al. (2020) [65] | LSTM | / | water quality time series | MAE, RMSE |
| Zou et al. (2020) [66] | LSTM | DNN, GRU, LSTM | meteorological time series, water quality time series | MAE |
| Peterson et al. (2020) [67] | ELR | MLR, SVR | Landsat-8, Sentinel-2 | MAPE, RMSE, R2 |
| Hanson et al. (2020) [68] | LSTM | / | water quality time series | auto-correlation, MK statistics, RMSE |
| Barzegar et al. (2020) [69] | CNN–LSTM hybrid | CNN, LSTM | water quality data from multiprobe sensor | MAE, NSEC, Percentage of Bias, RMSE, Wilmott’s index |
| Aldhyani et al. (2020) [70] | LSTM | ANN, DNN, KNN, NB, SVM | water quality time series | accuracy, F-score, MSE, precision, R, sensitivity, specificity |
| Li et al. (2021) [71] | RF | SVM | Sentinel-2 MSI | RMSE, RPD, R2, Z-score |
| Sharma et al. (2021) [72] | CNN | CNN | UAV camera | precision, recall |
| Cui et al. (2021) [73] | CNN | KNN, index method, RF, SVM | Landsat-8, Sentinel-2 | RPD, RMSE, R2 |
| Zhao et al. (2021) [74] | DNN | RBFNN | Landsat-8, water quality time series | MAE, MSE, R2 |
| Arias-Rodriguez et al. (2021) [75] | ELM | LR, SVR | Landsat-8, Sentinel-2 MSI, Sentinel-3 OLI | MAE, MSE, RMSE, R2 |
| Kravitz et al. (2021) [76] | DNN | KNN, RF, XGBoost | Landsat 8 OLI, Sentinel-2 MSI | MAPE, RMSE, RMSLE 1 |
| Sun et al. (2021) [77] | DNN | GPR, RF | proximal hyperspectral imager, water samples | accuracy, MRE, RMSE, R2 |
1 The authors use the abbreviation RMSELE for RMSLE in their paper (this might be a typographical error).