Assessing the impact of bridge construction on the land use/cover and socio-economic indicator time series: A case study of Hangzhou Bay Bridge

Abstract

Construction of transportation infrastructure is a vital step in boosting economic and societal opportunities and often results in land use changes. In this study, we focus on the land use dynamics of the urban agglomeration around Hangzhou Bay, where the Qiantang River flows into the East China Sea. The Hangzhou Bay Bridge crosses the bay since 2008. We used Interrupted Time Series Analysis (ITSA) to analyze the influence of the bridge on the land use and land cover (LULC) time series of the surrounding areas and on socio-economic indicators. We applied the Random Forest method to classify Landsat imagery from 2000 to 2017, thus enabling us to quantify LULC changes before and after the construction of the Hangzhou Bay Bridge. Google Earth Engine (GEE) was used for data acquisition, pre-processing, and classification. The results showed that during the period from 2000 to 2017, impervious surface areas expanded rapidly at the expense of agricultural land, and this transformation continued even more rapidly after 2008. ITSA showed that the driver behind the impervious surface area expansion switched from residential and industrial area growth in 2000–2008, to exclusively infrastructure area growth in 2008–2017. The construction of the bridge accelerated the expansion of impervious surface in the joint area of the bridge-connected cities of Ningbo and Jiaxing. With the Hangzhou Bay Bridge connection, various socio-economic factors, including tourism, GDP, tertiary industry, real estate investment, and highway freight, increased rapidly. The outcomes of this research could contribute to policymaking and impact assessments for sustainable urban development and land management. The methods used in this study are universal and therefore can also be used to assess the effect of any notable event that may impact LULC change.

Keywords

• land use/cover time series
• socio-economic indicators
• bridge construction
• interrupted time series analysis
• random forest
• google earth engine