Using Social Media Camping Data for Evaluating, Quantifying, and Understanding Recreational Ecosystem Services in Post-COVID-19 Megacities: A Case Study from Beijing

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How to cite this study

Xu, H., Zhao, G., Liu, Y. and Miao, M. 2023. Using Social Media Camping Data for Evaluating, Quantifying, and Understanding Recreational Ecosystem Services in Post-COVID-19 Megacities: A Case Study from Beijing. Forests 14(6): 1151.

Overview

The authors apply a GIS spatial analysis using social media data to quantify public perspectives of recreational ecosystem services (RESs) or green spaces in Beijing, China. This megacity-scale study was conducted using data from the Little Red Book (LRB) which has been referred to as “China’s Instagram.” Though the authors acknowledge there are some limitations in their methodology, they found that existing urban green spaces do not provide enough outdoor recreation facilities for the current demand, which leads to more clusters of outdoor recreational activity in the suburbs.

Relevance

This study is relevant to planners or policymakers working at a mega-city scale who want to assess public perception of green spaces or spatial distribution of daytime or overnight stays, including hiking, canoeing, climbing, fishing, swimming, kayaking, shooting, stone skipping, and bird watching. Their results can help city planners and policymakers who use social media or GIS methods to identify popular recreational areas and formulate policies to effectively manage the supply and demand of these green spaces.

Location

This study is located in Beijing, China. Beijing has a total administrative area of 16,410 km². The study focused on two main parts: the central urban area and the suburbs.

Trail Type

This study analyzes outdoor recreational green spaces in urban and suburban areas in Beijing, China.

Purpose

The purpose of this study is to assess the public’s perception of the recreational value of green spaces in Beijing, especially after the COVID-19 pandemic. Though the Beijing Municipal Forestry and Park Bureau has promoted urban park projects since 2021, outdoor recreation was not emphasized in new urban parks and green space projects even though demand for outdoor recreation surged post-COVID. The research was funded by the Research Enhancement Project for Young Scholars of BUCEA and the National Natural Science Foundation.

Findings

  • In general, there was more outdoor recreation in the suburbs than in the urban core. 
  • Areas with the most outdoor recreation were highly associated with grasslands and woods. 
  • Areas with the least outdoor recreation were highly associated with wetlands and waterbodies. The lower public perception value is likely due to the strict environmental protection laws in place on public water bodies. Swimming, fishing, gatherings, and picnicking are commonly prohibited, potentially reducing public enjoyment.

Methods

The authors used the Little Red Book (LRB) geotagged social media data from 2020 – 2022. The LRB has been referred to as “China’s Instagram” that allows users to upload notes and photographs with geolocation data. To collect their sample size, they extracted note data using key terms like “forest, park, water, wetland, river, lake, grass” in conjunction with the word “camping” and then used a Python code to mine the geographic coordinates included on the posts. They first identified 3,680 geotagged sites with relevant geotagged notes. Additionally, they removed images focusing on people and kept images only of the scenery or outdoor recreation-related activities. This was intended to reduce the interference caused by the people’s favorite pictures that might not be reflective of their opinions of the space. 

Their final sample size was 2,971 geotagged sites with relevant geotagged notes. To conduct spatial analysis, the authors used GIS point data from LRB. To assess the public’s perception of outdoor recreation sites, they used the number of “likes” on each note to quantify the RES values of each geo-location. Their reasoning is that a like symbolizes public reception of the message and interest in the uploaded information. However, since many other factors can influence the number of likes on a note, results regarding RES values should be interpreted with caution. 

 

Added to library on November 7, 2023