Publications

Luo, P; Song, YZ; Wu, P (2021). Spatial disparities in trade-offs: economic and environmental impacts of road infrastructure on continental level. GISCIENCE & REMOTE SENSING, 58(5), 756-775.

Abstract
Remote sensing and geospatial techniques are being used to provide large-scale and regional solutions for achieving the sustainable development goals (SDGs) of the United Nations, including sustainable infrastructure development. Road transportation infrastructure has a significant contribution to the economy, but it also increases environmental pressure. However, little knowledge is available about spatial characteristics in the relationship between road impacts on the economy and impacts on the roadside environment. This research explores the spatial disparities in the relationship of road impacts on a continental level in Australia from 2011 to 2016. The performance of road transportation infrastructure is characterized from the perspectives of road density, connectivity, traffic volumes, and service to communities, other transportations (e.g. ports and airports), and industries, using remote sensing data and spatial heterogeneity models. Local economy and roadside environment are respectively presented using resident income and the change of roadside Enhanced Vegetation Index (EVI) and Aerosol Optical Depth (AOD) derived from the moderate resolution imaging spectroradiometer (MODIS) onboard the Terra satellite generated from Google Earth Engine. The road impacts of variables and their interaction on the economy and environment were calculated using an optimal parameters-based geographical detectors model (OPGD). Results reveal that the interaction of road density and traffic volumes can explain 47.4% of the resident income. In addition, results demonstrate the significant spatial disparities in the relationship between road impacts on the economy and impacts on the local environment. In major cities, such as Sydney and Melbourne, the pressure of roadside environment is increased with the economic growth, but the roadside environment has been improved in suburban and rural areas. Areas with the service to industries range from 64.4 km to 128 km have the most significant roadside EVI increase (2.5%). To the best of our knowledge, this is the first research to explore spatially differentiated trade-offs between the economic and roadside environmental impacts of roads using remotely sensed data, geospatial data, and spatial heterogeneity model at the continental level. Findings from this study provide an in-depth understanding of the interactions and trade-offs of road impacts on the local economy and the environment. Geospatial trade-offs and impact analysis methods in the study can be applied in wider fields to achieve global and regional SDGs.

DOI:
10.1080/15481603.2021.1947624

ISSN:
1548-1603