Articles | Volume 17, issue 11
https://doi.org/10.5194/hess-17-4701-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-17-4701-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| Highlight paper
| 
28 Nov 2013
Research article | Highlight paper |
| 28 Nov 2013
Rainfall estimation using moving cars as rain gauges – laboratory experiments
E. Rabiei
Institute of Water Resources Management, Hydrology and Agricultural Hydraulic Engineering, Leibniz Universität Hannover, Hanover, Germany
U. Haberlandt
Institute of Water Resources Management, Hydrology and Agricultural Hydraulic Engineering, Leibniz Universität Hannover, Hanover, Germany
M. Sester
Institute of Cartography and Geoinformatics, Leibniz Universität Hannover, Hanover, Germany
D. Fitzner
Institute of Cartography and Geoinformatics, Leibniz Universität Hannover, Hanover, Germany
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44 citations as recorded by crossref.
- CondMerg: an open source implementation in R language of conditional merging for weather radars and rain gauges observations D. Guenzi et al. https://doi.org/10.1007/s12145-016-0278-y
- A Lagrangian meshfree model for solidification of liquid thin-films A. Bharadwaj et al. https://doi.org/10.1016/j.compfluid.2024.106267
- WeatherEye-Proposal of an Algorithm Able to Classify Weather Conditions from Traffic Camera Images K. Dahmane et al. https://doi.org/10.3390/atmos12060717
- Modelling Weather Precipitation Intensity on Surfaces in Motion with Application to Autonomous Vehicles M. Carvalho & H. Hangan https://doi.org/10.3390/s23198034
- A review of video‐based rainfall measurement methods K. Yan et al. https://doi.org/10.1002/wat2.1678
- SIRE-ST: A Swin Transformer-Based Cascaded Model for Urban Rainfall Estimation in Complex Environments G. Hou et al. https://doi.org/10.1109/ACCESS.2026.3681681
- A Soiling Mitigation Method to Enhance the Performance of ADAS in Precipitation W. Pao et al. https://doi.org/10.4271/2022-01-0076
- The Car as an Ambient Sensing Platform [Point of View] E. Massaro et al. https://doi.org/10.1109/JPROC.2016.2634938
- A novel quality control model of rainfall estimation with videos – A survey based on multi-surveillance cameras X. Wang et al. https://doi.org/10.1016/j.jhydrol.2021.127312
- Deep Learning for Opportunistic Rain Estimation via Satellite Microwave Links G. Scognamiglio et al. https://doi.org/10.3390/s24216944
- Fast Bayesian Regression Kriging Method for Real‐Time Merging of Radar, Rain Gauge, and Crowdsourced Rainfall Data P. Yang & T. Ng https://doi.org/10.1029/2018WR023857
- Flood hazard assessment and the role of citizen science B. Sy et al. https://doi.org/10.1111/jfr3.12519
- Opportunistic remote sensing of rainfall using microwave links from cellular communication networks R. Uijlenhoet et al. https://doi.org/10.1002/wat2.1289
- Tropical rainfall monitoring with commercial microwave links in Sri Lanka A. Overeem et al. https://doi.org/10.1088/1748-9326/ac0fa6
- Cars as a Diffuse Network of Road-Environment Monitoring Nodes M. Allegretti & S. Bertoldo https://doi.org/10.4236/wsn.2014.69018
- Evaluating weather impact on vehicles: a systematic review of perceived precipitation dynamics and testing methodologies W. Pao et al. https://doi.org/10.1088/2631-8695/ad2033
- From proof‐of‐concept to proof‐of‐value: Approaching third‐party data to operational workflows of national meteorological services I. Garcia‐Marti et al. https://doi.org/10.1002/joc.7757
- Estimation of raindrop size distribution and rain rate with infrared surveillance camera in dark conditions J. Lee et al. https://doi.org/10.5194/amt-16-707-2023
- Evaluating rain gauge precipitation measurements using a giant rain gauge as a benchmark A. Petroselli & S. Grimaldi https://doi.org/10.1007/s00704-025-05540-w
- Harnessing Crowdsourced Data and Prevalent Technologies for Atmospheric Research N. David https://doi.org/10.1007/s00376-019-9022-0
- Hydrometeorological Monitoring Using Opportunistic Sensing Networks in the Amsterdam Metropolitan Area L. de Vos et al. https://doi.org/10.1175/BAMS-D-19-0091.1
- Rainfall estimates from opportunistic sensors in Germany across spatio-temporal scales M. Graf et al. https://doi.org/10.1016/j.ejrh.2021.100883
- A discrete droplet method for modelling thin film flows A. S． Bharadwaj et al. https://doi.org/10.1016/j.apm.2022.08.001
- Reconstructing and Nowcasting the Rainfall Field by a CML Network P. Zhang et al. https://doi.org/10.1029/2023EA002909
- Estimation of precipitation fields from 1-minute rain gauge time series – comparison of spatial and spatio-temporal interpolation methods D. Fitzner & M. Sester https://doi.org/10.1080/13658816.2015.1040022
- Areal rainfall estimation using moving cars – computer experiments including hydrological modeling E. Rabiei et al. https://doi.org/10.5194/hess-20-3907-2016
- Advancing Opportunistic Sensing in Hydrology: A Novel Approach to Measuring Rainfall With Ordinary Surveillance Cameras S. Jiang et al. https://doi.org/10.1029/2018WR024480
- Recording Rainfall Intensity: Has an Optimum Method Been Found? D. Dunkerley https://doi.org/10.3390/w15193383
- A Bayesian deep learning approach for video-based estimation and uncertainty quantification of urban rainfall intensity F. Zheng et al. https://doi.org/10.1016/j.jhydrol.2024.131706
- Rainfall nowcasting models: state of the art and possible future perspectives D. De Luca et al. https://doi.org/10.1080/02626667.2025.2490780
- Toward the camera rain gauge P. Allamano et al. https://doi.org/10.1002/2014WR016298
- Quality Control for Crowdsourced Personal Weather Stations to Enable Operational Rainfall Monitoring L. de Vos et al. https://doi.org/10.1029/2019GL083731
- Precipitation Monitoring Using Commercial Microwave Links: Current Status, Challenges and Prospectives P. Zhang et al. https://doi.org/10.3390/rs15194821
- Crowdsourcing Methods for Data Collection in Geophysics: State of the Art, Issues, and Future Directions F. Zheng et al. https://doi.org/10.1029/2018RG000616
- Optimal Distributed MQTT Broker and Services Placement for SDN-Edge Based Smart City Architecture D. Fawwaz et al. https://doi.org/10.3390/s22093431
- Development and Assessment of Methods for Predicting Rainfall in Unmeasured Watersheds Using the Relation Between Observed and Sensor-Measured Rainfall C. Lee & H. Kim https://doi.org/10.9798/KOSHAM.2021.21.6.293
- Application of machine learning-based post-processing to improve crowd-sourced urban rainfall categorizations M. Hussain et al. https://doi.org/10.1016/j.acags.2025.100255
- Crowdsourcing for climate and atmospheric sciences: current status and future potential C. Muller et al. https://doi.org/10.1002/joc.4210
- Use of autonomous transmission line-type electromagnetic sensors for classification of dry and wet periods at sub-hourly time intervals V. Mikešová et al. https://doi.org/10.1007/s10661-018-7059-7
- ExTraCT: Expediting Offloading Transfers Through Intervehicle Communication Transmissions P. Kolios et al. https://doi.org/10.1109/TITS.2014.2357221
- Measurements and Observations in the XXI century (MOXXI): innovation and multi-disciplinarity to sense the hydrological cycle F. Tauro et al. https://doi.org/10.1080/02626667.2017.1420191
- APPLICABILITY OF A COMPACT DOPPLER SENSOR FOR VEHICLE PRECIPITATION MEASUREMENTS S. ONOMURA et al. https://doi.org/10.2208/jscejhe.76.2_I_211
- Toward Improved Real‐Time Rainfall Intensity Estimation Using Video Surveillance Cameras F. Zheng et al. https://doi.org/10.1029/2023WR034831
- Crowdsensing Framework for Monitoring Bridge Vibrations Using Moving Smartphones T. Matarazzo et al. https://doi.org/10.1109/JPROC.2018.2808759
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