| PERSIANN-CNN: Precipitation estimation from remotely sensed information using artificial neural networks–convolutional neural networks M Sadeghi, AA Asanjan, M Faridzad, PHU Nguyen, K Hsu, S Sorooshian, ... Journal of Hydrometeorology 20 (12), 2273-2289, 2019 | 129 | 2019 |
| PERSIANN-CCS-CDR, a 3-hourly 0.04 global precipitation climate data record for heavy precipitation studies M Sadeghi, P Nguyen, MR Naeini, K Hsu, D Braithwaite, S Sorooshian Scientific Data 8 (1), 157, 2021 | 94 | 2021 |
| Persiann dynamic infrared–rain rate (PDIR-now): A near-real-time, quasi-global satellite precipitation dataset P Nguyen, M Ombadi, VA Gorooh, EJ Shearer, M Sadeghi, S Sorooshian, ... Journal of hydrometeorology 21 (12), 2893-2906, 2020 | 71 | 2020 |
| Improving near real-time precipitation estimation using a U-Net convolutional neural network and geographical information M Sadeghi, P Nguyen, K Hsu, S Sorooshian Environmental Modelling & Software 134, 104856, 2020 | 61 | 2020 |
| Application of machine learning algorithms in hydrology H Mosaffa, M Sadeghi, I Mallakpour, MN Jahromi, HR Pourghasemi Computers in earth and environmental sciences, 585-591, 2022 | 38 | 2022 |
| Spatiotemporal variations of precipitation over Iran using the high-resolution and nearly four decades satellite-based PERSIANN-CDR dataset H Mosaffa, M Sadeghi, N Hayatbini, V Afzali Gorooh, A Akbari Asanjan, ... Remote Sensing 12 (10), 1584, 2020 | 32 | 2020 |
| Evaluation of PERSIANN-CDR constructed using GPCP V2. 2 and V2. 3 and a comparison with TRMM 3B42 V7 and CPC unified gauge-based analysis in global scale M Sadeghi, A Akbari Asanjan, M Faridzad, V Afzali Gorooh, P Nguyen, ... Remote Sensing 11 (23), 2755, 2019 | 29 | 2019 |
| Application of remote sensing precipitation data and the CONNECT algorithm to investigate spatiotemporal variations of heavy precipitation: Case study of major floods across … M Sadeghi, EJ Shearer, H Mosaffa, VA Gorooh, MR Naeini, N Hayatbini, ... Journal of Hydrology 600, 126569, 2021 | 24 | 2021 |
| Estimation of spatial distribution of PM10, lead, and radon concentrations in Sepahanshahr, Iran using Geographic Information System (GIS) H Farrokhzadeh, N Jafari, M Sadeghi, M Talesh Alipour, MM Amin, ... Journal of Mazandaran University of Medical Sciences 28 (159), 84-96, 2018 | 15 | 2018 |
| The application of PERSIANN family datasets for hydrological modeling H Salehi, M Sadeghi, S Golian, P Nguyen, C Murphy, S Sorooshian Remote Sensing 14 (15), 3675, 2022 | 12 | 2022 |
| Precipitation estimation from remotely sensed information using artificial neural networks-cloud classification system-climate data record (PERSIANN-CCS-CDR) M Sadeghi, J Lee, P Nguyen, KL Hsu, S Sorooshian, D Braithwaite AGU Fall Meeting Abstracts 2019, H13P-1964, 2019 | 12 | 2019 |
| What is the geographical space? A thinking on the nature of the geographical space from the perspective of hermeneutic phenomenology M Sadeghi, J Javan, MR Rahnama Journal of Arid Regions Geographic Studies 5 (19), 12-28, 2015 | 9 | 2015 |
| Discrepancies in changes in precipitation characteristics over the contiguous United States based on six daily gridded precipitation datasets I Mallakpour, M Sadeghi, H Mosaffa, AA Asanjan, M Sadegh, P Nguyen, ... Weather and climate extremes 36, 100433, 2022 | 8 | 2022 |
| PERSIANN-CCS-CDR, a 3-hourly 0.04 global precipitation climate data record for heavy precipitation studies. Sci Data 8: 1–11 M Sadeghi, P Nguyen, MR Naeini, K Hsu, D Braithwaite, S Sorooshian | 5 | 2021 |
| An assessment of the unprecedented extreme precipitation events over Iran: from satellite perspective AA Asanjan, M Faridzad, N Hayatbini, VA Gorooh, M Sadeghi, EJ Shearer, ... Irvine (CA): University of California, 2019 | 4 | 2019 |
| Structural-Functional Explanation of Urban Participative Management (Case Study: Mashhad) M Sadeghi, MR Rahnama HUMAN GEOGRAPHY RESEARCH QUARTERLY 45 (1), 20-21, 2013 | 4 | 2013 |
| Assessment of the PERSIANN-CDR Products Bias-corrected with the GPCP Datasets Versions 2.2 & 2.3 M Sadeghi University of California, Irvine, 2018 | 3 | 2018 |
| A Simplified Machine Learning Based Wildfire Ignition Model from Insurance Perspective Y Liu, S Le, Y Zou, M Sadeghi, Y Chen, N Andela, P Gentine ICLR 2023 Workshop on Tackling Climate Change with Machine Learning, 2023 | 2 | 2023 |
| Attention-based wildland fire spread modeling using fire-tracking satellite observations Y Zou, M Sadeghi, Y Liu, A Puchko, S Le, Y Chen, N Andela, P Gentine Fire 6 (8), 289, 2023 | 2 | 2023 |
| â What is the methodology of cognition of geographical space?(A thinking on the nature of the methodology of cognition of geographical space by the perspective of hermeneutic … M Sadeghi, J Javan, M Rahnama Journal of Arid Regions Geographic Studies 7 (25), 17-36, 2022 | 2 | 2022 |
soroosh sorooshianProfessor of Civil Engineering, UC Irvine在 uci.edu 的电子邮件经过验证
