Extracting Flooded Roads by Fusing GPS Trajectories and Road Network

She She,Fang Fang,Zhong Zhong,Zheng Zheng,Zhou Zhou

doi:10.3390/ijgi8090407

Abstract

Urban roads are the lifeline of urban transportation and satisfy the commuting and travel needs of citizens. Following the acceleration of urbanization and the frequent extreme weather in recent years, urban waterlogging is occurring more than usual in summer and has negative effects on the urban traffic networks. Extracting flooded roads is a critical procedure for improving the resistance ability of roads after urban waterlogging occurs. This paper proposes a flooded road extraction method to extract the flooding degree and the time at which roads become flooded in large urban areas by using global positioning system (GPS) trajectory points with driving status information and the high position accuracy of vector road data with semantic information. This method uses partition statistics to create density grids (grid layer) and uses map matching to construct a time-series of GPS trajectory point density for each road (vector layer). Finally, the fusion of grids and vector layers obtains a more accurate result. The experiment uses a dataset of GPS trajectory points and vector road data in the Wuchang district, which proves that the extraction result has a high similarity with respect to the flooded roads reported in the news. Additionally, extracted flooded roads that were not reported in the news were also found. Compared with the traditional methods for extracting flooded roads and areas, such as rainfall simulation and SAR image-based classification in urban areas, the proposed method discovers hidden flooding information from geospatial big data, uploaded at no cost by urban taxis and remaining stable for a long period of time.

Highlights

Roads are the backbone of urban transportation
The time resolution of the time series is affected by the number of global positioning system (GPS) points; a higher time strict degree of extraction; a higher sensitivity leads to a smaller number of flooded roads, but the extraction result is more reliable
Some additional flooded roads were extracted by the proposed method but were not reported in the to be substantially flooded by analyzing the traffic flow on the rainy day

Summary

Introduction

Smooth traffic is crucial for daily commute and emergency travel of the urban residents [1]. Traditional city design and construction often ignore the importance of urban surface permeability, so vegetation areas with good water storage and drainage are covered by a large amount of urban construction materials, which cause the urban water drainage ability to decline sharply [2]. With the continuous increase of extreme climates, some cities have serious waterlogging problems during periods of abnormal precipitation in the spring and summer [3,4]. Roads in low-lying areas or with poor drainage systems are flooded, which cause an increase in urban traffic pressure and incur negative effects on the travel of urban residents. It is of great importance to study the extraction of flooded roads

Results

Discussion

Conclusion