# Urban Greenway Planning and Designing Based on MGWR and the Entropy Weight Method
## 2 Methods  
### Data and Variables  
The study area is Xiamen City. Xiamen City is a famous tourist city in China, located in the middle of the west coast of the Taiwan Strait and the center of the Golden Triangle in southern Fujian. Xiamen municipality is composed of the mainland area along Xiamen Bay in southeastern Fujian Province and the islands of Xiamen Island and Gulangyu Island as well as Xiamen Bay. The land area of Xiamen is 1699.39 km\({}^{2}\), of which Xiamen Main Island has a land area of about 158 km\({}^{2}\) (including Gulangyu Island) and a sea area of about 390 km\({}^{2}\). Xiamen has six municipal districts, including Huli, Siming, Tongan, Jimei, Haicang, and Xiang'an districts.  
By the end of 2021, about 647 km of greenway construction had been completed. Regarding future construction of slow traffic systems, Xiamen also has a clear plan. From 2022 to 2025, Xiamen plans to renovate and upgrade 73 existing roads and slow running system projects along with 195 new slow running system projects. The project is expected to add 407 km of slow traffic systems. At the same time, Xiamen City issued a public tender for the near-term implementation plan of Xiamen Greenway (2023-2028) to further improve the greenway planning of Xiamen City. It can be seen that although Xiamen has made some progress in greenway planning, there are still some gaps. Therefore, this study can provide a theoretical reference for greenway planning in Xiamen City.  
To provide more accurate input parameters for the determination of green corridors, it is necessary to grid the study area, with a grid unit of 500 m \(\times\) 500 m. A total of 6476 grids were created, as shown in Figure 1. Each grid is used as a source of data from which the weights of the suitability indicators are calculated using the model.  
The bike sharing data are obtained from Xiamen City Big Data Security Open Platform ([[https://data.xm.gov.cn/opendata/datas/#/catalog_list?archivingStatus=0&provide&depth=_JTJ&sf=dataTotal](https://data.xm.gov.cn/opendata/datas/#/catalog_list?archivingStatus=0&provide&depth=_JTJ&sf=dataTotal)]([https://data.xm.gov.cn/opendata/datas/#/catalog_list?archivingStatus=0&provide&depth=_JTJ&sf=dataTotal](https://data.xm.gov.cn/opendata/datas/#/catalog_list?archivingStatus=0&provide&depth=_JTJ&sf=dataTotal)), accessed on 1 October 2024). The data include ID, trajectory point data of traveling, time, and latitude and longitude coordinates. The transit data are obtained from Xiamen City Big Data Security Open Platform. The public transport data are obtained from Cubic Data Society. The built environment data are obtained from traditional statistical data and network open source big data. The road network data are obtained from OpenStreetMap. The POI data are obtained from Gaode Map as well as the 30-m fine surface coverage data set and the DEM data set. This study uses 2021 data.  
Considering the functional classification of greenways and based on the theory of the 5 Ds (density, diversity, design, distance from transportation sites, and accessibility to destinations), 13 indicators, including road density, intersection density, POI entropy index, land use mix, density of tourist attractions, greening ratio, distance to bus stop, distance to metro station, intermediate, and accessibility, were selected to be analyzed to determine the suitability. The calculations for the independent variables will be shown in Section 2.2.1. The dependent variable is the density of shared bicycle origin-destination (OD) points.