Urban Greenway Planning and Designing Based on MGWR and the Entropy Weight Method

Travelers’ attention to high-quality human habitats is increasing, and the role of urban greenways in improving the quality of travelling spaces has also been appreciated. This research aims at making the weight calculation of suitability more scientific and reasonable, clustering the shared bicycle...

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Veröffentlicht in:Applied sciences Jg. 14; H. 24; S. 11670
Hauptverfasser: Li, Weijia, Ji, Xinge, Bai, Hua
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Basel MDPI AG 01.12.2024
Schlagworte:
Algorithms
Bicycles
Bicycling
Big Data
Built environment
Cities
Clustering
DBSCAN clustering algorithm
Delphi method
entropy weight method
Land area
Methods
multiscale geographic weighted regression
Open data
origin-destination of shared bicycle
Planning
Roads & highways
suitability
Travel
urban greenway
China
Gulangyu Island
ISSN:2076-3417, 2076-3417
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Zusammenfassung:Travelers’ attention to high-quality human habitats is increasing, and the role of urban greenways in improving the quality of travelling spaces has also been appreciated. This research aims at making the weight calculation of suitability more scientific and reasonable, clustering the shared bicycle travelling OD points according to suitability, and analyzing the distribution of OD points. Taking Xiamen as an example, multiscale geographically weighted regression and entropy weight methods were used to calculate the weights of variables using multi-source big data. The clustering of origin-destination (OD) points for shared bicycle travel are identified using the DBSCAN clustering algorithm, which can provide accurate support for greenway planning and shared bicycle placement. The results show that the density of tourist attractions, POI entropy index, road density, and intermediate are four important factors affecting the suitability of greenways. The clustering results of the shared bicycle OD points show that the high-aggregation areas of origin and destination points are located in the northeast and southwest directions as well as west and east directions. This study provides a theoretical and modelling analysis reference for greenway planning and design.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2076-3417
2076-3417
DOI:10.3390/app142411670