Rainfall estimation using moving cars as rain gauges (RainCars)

使用移动汽车作为雨量计估算降雨量 (RainCars)

• 批准号: 170444902
• 负责人: Professor Dr.-Ing. Uwe Haberlandt
• 金额: --
• 依托单位: Institut für Kartographie und Geoinformatik
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2010
• 资助国家: 德国
• 起止时间: 2009-12-31 至 2016-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/170444902?language=en
• 关键词: Rainfall; estimation; using; moving; cars

Objective of the proposed research is the investigation of a completely new approach for rainfall estimation using motorcars as moving rain gauges with windscreen wipers as sensors to detect precipitation. This idea would easily be technically feasible if the cars are provided with GPS and a small memory chip for recording the coordinates, car speed and wiper frequency. This initial research will explore theoretically the benefits of such an approach. For that valid relationships between wiper speed and rainfall rate (W-R-relationship) are assumed and derived from laboratory and field experiments. Different traffic models are developed to generate motorcars on roads in a river basin. Radar data are used as reference truth rainfall fields. Rainfall from these fields is sampled from the conventional rain gauge and dynamic car networks. Areal rainfall is calculated from these networks for different scales using geostatistical interpolation methods and compared against truth radar data. The car sensors can be considered as a geosensor network. It allows to measure and process information locally in a decentralized way and thus has benefits with respect to scalability, which is crucial when large areas have to be covered with large amounts of measurement units.

本研究的目的是研究一种全新的降雨量估算方法，使用汽车作为移动雨量计，并使用挡风玻璃雨刷器作为传感器来检测降水量。如果汽车配备了 GPS 和用于记录坐标、汽车速度和雨刷频率的小型存储芯片，那么这个想法在技术上很容易实现。这项初步研究将从理论上探讨这种方法的好处。为此，假设雨刷速度和降雨率之间的有效关系（W-R 关系），并从实验室和现场实验中得出。人们开发了不同的交通模型来在流域的道路上生产汽车。雷达数据用作参考真实降雨场。这些田地的降雨量是通过传统雨量计和动态汽车网络进行采样的。使用地统计插值方法根据这些网络计算出不同尺度的面积降雨量，并与真实的雷达数据进行比较。汽车传感器可以被视为地理传感器网络。它允许以分散的方式在本地测量和处理信息，因此具有可扩展性的优点，这在必须用大量测量单元覆盖大面积时至关重要。

项目成果

Rainfall Estimation with a Geosensor Network of Cars – Theoretical Considerations and First Results

• DOI: 10.1127/1432-8364/2013/0161
• 发表时间: 2013-05
• 期刊: Photogrammetrie Fernerkundung Geoinformation
• 作者: D. Fitzner;Monika Sester;U. Haberlandt;E. Rabiei

Geostatistical merging of rain gauge and radar data for high temporal resolutions and various station density scenarios

针对高时间分辨率和各种站点密度场景的雨量计和雷达数据的地统计合并

• DOI: 10.1016/j.jhydrol.2013.10.028
• 发表时间: 2014
• 期刊: Journal of Hydrology
• 影响因子: 6.4
• 作者: Berndt;Rabiei;Haberlandt
• 通讯作者: Haberlandt

Applying bias correction for merging rain gauge and radar data

• DOI: 10.1016/j.jhydrol.2015.01.020
• 发表时间: 2015-03
• 期刊: Journal of Hydrology
• 影响因子: 6.4
• 作者: E. Rabiei;U. Haberlandt

Decentralized Gradient-based Field Motion Estimation with a Wireless Sensor Network

• DOI: 10.5220/0005639100130024
• 发表时间: 2016-02
• 作者: D. Fitzner;Monika Sester

Areal rainfall estimation using moving cars – computer experimentsincluding hydrological modeling

• DOI: 10.5194/hess-20-3907-2016
• 发表时间: 2015-12
• 期刊: Hydrology and Earth System Sciences
• 影响因子: 6.3
• 作者: E. Rabiei;U. Haberlandt;Monika Sester;D. Fitzner;M. Wallner