Research on Urban Greenway Alignment Selection Based on Multisource Data

Abstract

At present, people’s growing need for a beautiful ecological environment needs to be met. As a high-quality ecological product, greenways help improve the living environment and promote green and coordinated development. How to scientifically and rationally plan greenway routes and expand the green ecological network has become an important issue for the sustainable development of high-density built-up areas. Therefore, this study determines the suitability evaluation system of urban greenway alignment selection based on spatial constructiveness, greenway accessibility, resource attractiveness and public demand through factor analysis. Taking Xixi Wetland to South Lake in Yuhang District as an example, combining urban multi-source data and GIS spatial analysis methods, all routes suitable for greenway construction in the study area were determined, and four excellent greenway routes were initially identified through manual correction. Subsequently, the PSO-BP neural network model was trained using 172 greenway samples to obtain a greenway alignment suitability evaluation model with an accuracy of more than 96%, which was used for subsequent greenway alignment optimization. The above four preliminary greenway routes are substituted into the PSO-BP model to obtain the optimal greenway routes in the study area. The results show that there are 17 indicators in 4 levels and 8 dimensions in the urban greenway route selection potential model, among which two indicators, public cycling and running demand, have a greater weight and should be highly considered in the route selection assessment. The optimal planned route for the greenway start from Guangfu Temple entrance of Xixi Wetland, follow the roadside green belt and Yuhangtang River greenway to South Lake. The study obtained the best planning route for the greenway from Xixi Wetland to South Lake in Yuhang District, which is a new practice of landscape garden planning and design supported by multisource data and new technologies, with a view to providing a reference for the preferential selection of urban greenway routes in similar high-density built-up areas.