Predict the Suitable Places to Run in the Urban Area of Beijing by Using the Maximum Entropy Model
Many people in the world do not have enough physical activities to maintain good health, which has recently become a threat to public health. In addition to individual genetic and social factors, we considered the geographical environment of the city as a factor that affects these healthy physical a...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-08-01
|
| Series: | ISPRS International Journal of Geo-Information |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2220-9964/10/8/534 |
| _version_ | 1827685087490080768 |
|---|---|
| author | Liuyi Song An Zhang |
| author_facet | Liuyi Song An Zhang |
| author_sort | Liuyi Song |
| collection | DOAJ |
| description | Many people in the world do not have enough physical activities to maintain good health, which has recently become a threat to public health. In addition to individual genetic and social factors, we considered the geographical environment of the city as a factor that affects these healthy physical activities. We used the location-based data in social media combined with the open geographic data to explore the impact mechanism of urban environmental factors on human running behaviors. This study collected nine urban environmental variables and preference tracks in Beijing’s main urban area. We used the Maximum Entropy Model (MaxEnt) to analyze the relationship between running behaviors and environmental variables and identify suitable areas for running in Beijing. The results showed that: firstly, the variables of attractions, sports and sidewalk density contributed the most to running suitability. Secondly, 47.5% of the main urban areas in Beijing are suitable for running, mainly in the main urban areas with better economic development. Thirdly, the distribution of suitable places for running is unfair in that some places with large populations do not have a matching running environment. |
| first_indexed | 2024-03-10T08:46:03Z |
| format | Article |
| id | doaj.art-96626244b3e1447bada7811a1d90f91c |
| institution | Directory Open Access Journal |
| issn | 2220-9964 |
| language | English |
| last_indexed | 2024-03-10T08:46:03Z |
| publishDate | 2021-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj.art-96626244b3e1447bada7811a1d90f91c2023-11-22T07:53:19ZengMDPI AGISPRS International Journal of Geo-Information2220-99642021-08-0110853410.3390/ijgi10080534Predict the Suitable Places to Run in the Urban Area of Beijing by Using the Maximum Entropy ModelLiuyi Song0An Zhang1State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaState Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaMany people in the world do not have enough physical activities to maintain good health, which has recently become a threat to public health. In addition to individual genetic and social factors, we considered the geographical environment of the city as a factor that affects these healthy physical activities. We used the location-based data in social media combined with the open geographic data to explore the impact mechanism of urban environmental factors on human running behaviors. This study collected nine urban environmental variables and preference tracks in Beijing’s main urban area. We used the Maximum Entropy Model (MaxEnt) to analyze the relationship between running behaviors and environmental variables and identify suitable areas for running in Beijing. The results showed that: firstly, the variables of attractions, sports and sidewalk density contributed the most to running suitability. Secondly, 47.5% of the main urban areas in Beijing are suitable for running, mainly in the main urban areas with better economic development. Thirdly, the distribution of suitable places for running is unfair in that some places with large populations do not have a matching running environment.https://www.mdpi.com/2220-9964/10/8/534running routesphysical activitiesurban environmentMaxEnt |
| spellingShingle | Liuyi Song An Zhang Predict the Suitable Places to Run in the Urban Area of Beijing by Using the Maximum Entropy Model ISPRS International Journal of Geo-Information running routes physical activities urban environment MaxEnt |
| title | Predict the Suitable Places to Run in the Urban Area of Beijing by Using the Maximum Entropy Model |
| title_full | Predict the Suitable Places to Run in the Urban Area of Beijing by Using the Maximum Entropy Model |
| title_fullStr | Predict the Suitable Places to Run in the Urban Area of Beijing by Using the Maximum Entropy Model |
| title_full_unstemmed | Predict the Suitable Places to Run in the Urban Area of Beijing by Using the Maximum Entropy Model |
| title_short | Predict the Suitable Places to Run in the Urban Area of Beijing by Using the Maximum Entropy Model |
| title_sort | predict the suitable places to run in the urban area of beijing by using the maximum entropy model |
| topic | running routes physical activities urban environment MaxEnt |
| url | https://www.mdpi.com/2220-9964/10/8/534 |
| work_keys_str_mv | AT liuyisong predictthesuitableplacestorunintheurbanareaofbeijingbyusingthemaximumentropymodel AT anzhang predictthesuitableplacestorunintheurbanareaofbeijingbyusingthemaximumentropymodel |