| Predicting stream water quality under different urban development pattern scenarios with an interpretable machine learning approach R Wang, JH Kim, MH Li Science of the Total Environment 761, 144057, 2021 | 80 | 2021 |
| Investigating sense of place of the Las Vegas Strip using online reviews and machine learning approaches Y Song, R Wang, J Fernandez, D Li Landscape and Urban Planning 205, 103956, 2021 | 40 | 2021 |
| Predicting bioretention pollutant removal efficiency with design features: A data-driven approach R Wang, X Zhang, MH Li Journal of Environmental Management 242, 403-414, 2019 | 34 | 2019 |
| Comparing stormwater quality and watershed typologies across the United States: A machine learning approach CB Guzman, R Wang, O Muellerklein, M Smith, CG Eger Water Research 216, 118283, 2022 | 11 | 2022 |
| How spatial patterns affect urban green space equity at different equity levels: A bayesian quantile regression approach J Guan, R Wang, D Van Berkel, Z Liang Landscape and Urban Planning 233, 104709, 2023 | 4 | 2023 |
| Investigating water quality sensitivity to climate variability and its influencing factors in four Lake Erie watersheds R Wang, Y Ma, G Zhao, Y Zhou, I Shehab, A Burton Journal of Environmental Management 325, 116449, 2023 | 3 | 2023 |
| Incorporating water quality into land use scenario analysis with random forest models R Goodspeed, R Wang, C Lizundia, L Du, S Jaipuria Environment and Planning B: Urban Analytics and City Science, 23998083221138842, 2022 | | 2022 |
Ming-Han LiDean, College of Architecture, Planning and Public Affairs, The University of Texas atVerified email at uta.edu
