Investigating the Patterns and Dynamics of Urban Green Space in China’s 70 Major Cities Using Satellite Remote Sensing
Urban green space (UGS) plays a pivotal role in improving urban ecosystem services and building a livable environment for urban dwellers. However, remotely sensed investigation of UGS at city scale is facing a challenge due to the pixels’ mosaics of buildings, squares, roads and green spaces in citi...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-06-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/12/12/1929 |
| _version_ | 1797565322083958784 |
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| author | Wenhui Kuang Yinyin Dou |
| author_facet | Wenhui Kuang Yinyin Dou |
| author_sort | Wenhui Kuang |
| collection | DOAJ |
| description | Urban green space (UGS) plays a pivotal role in improving urban ecosystem services and building a livable environment for urban dwellers. However, remotely sensed investigation of UGS at city scale is facing a challenge due to the pixels’ mosaics of buildings, squares, roads and green spaces in cities. Here we developed a new algorithm to unmix the fraction of UGS derived from Landsat TM/ETM/8 OLI using a big-data platform. The spatiotemporal patterns and dynamics of UGSs were examined for 70 major cities in China between 2000 and 2018. The results showed that the total area of UGS in these cities grew from 2780.66 km<sup>2</sup> in 2000 to 6764.75 km<sup>2</sup> in 2018, which more than doubled its area. As a result, the UGS area per inhabitant rose from 15.01 m<sup>2</sup> in 2000 to 18.09 m<sup>2</sup> in 2018. However, an uneven layout of UGS occurred among the coastal, western, northeastern and central zones. For example, the UGS percentage in newly expanded urban areas in the coastal zone rose significantly in 2000–2018, with an increase of 2.51%, compared to the decline in UGS in cities in the western zone. Therefore, the effective strategies we have developed should be adopted to show disparities and promote green infrastructure capacity building in those cities with less green space, especially in western China. |
| first_indexed | 2024-03-10T19:10:28Z |
| format | Article |
| id | doaj.art-c2f3f6db8f324b52ba072b3866787ea5 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T19:10:28Z |
| publishDate | 2020-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-c2f3f6db8f324b52ba072b3866787ea52023-11-20T03:51:30ZengMDPI AGRemote Sensing2072-42922020-06-011212192910.3390/rs12121929Investigating the Patterns and Dynamics of Urban Green Space in China’s 70 Major Cities Using Satellite Remote SensingWenhui Kuang0Yinyin Dou1Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaKey Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, ChinaUrban green space (UGS) plays a pivotal role in improving urban ecosystem services and building a livable environment for urban dwellers. However, remotely sensed investigation of UGS at city scale is facing a challenge due to the pixels’ mosaics of buildings, squares, roads and green spaces in cities. Here we developed a new algorithm to unmix the fraction of UGS derived from Landsat TM/ETM/8 OLI using a big-data platform. The spatiotemporal patterns and dynamics of UGSs were examined for 70 major cities in China between 2000 and 2018. The results showed that the total area of UGS in these cities grew from 2780.66 km<sup>2</sup> in 2000 to 6764.75 km<sup>2</sup> in 2018, which more than doubled its area. As a result, the UGS area per inhabitant rose from 15.01 m<sup>2</sup> in 2000 to 18.09 m<sup>2</sup> in 2018. However, an uneven layout of UGS occurred among the coastal, western, northeastern and central zones. For example, the UGS percentage in newly expanded urban areas in the coastal zone rose significantly in 2000–2018, with an increase of 2.51%, compared to the decline in UGS in cities in the western zone. Therefore, the effective strategies we have developed should be adopted to show disparities and promote green infrastructure capacity building in those cities with less green space, especially in western China.https://www.mdpi.com/2072-4292/12/12/1929urban green spaceremote sensingurban parkurban ecosystem servicesChina |
| spellingShingle | Wenhui Kuang Yinyin Dou Investigating the Patterns and Dynamics of Urban Green Space in China’s 70 Major Cities Using Satellite Remote Sensing Remote Sensing urban green space remote sensing urban park urban ecosystem services China |
| title | Investigating the Patterns and Dynamics of Urban Green Space in China’s 70 Major Cities Using Satellite Remote Sensing |
| title_full | Investigating the Patterns and Dynamics of Urban Green Space in China’s 70 Major Cities Using Satellite Remote Sensing |
| title_fullStr | Investigating the Patterns and Dynamics of Urban Green Space in China’s 70 Major Cities Using Satellite Remote Sensing |
| title_full_unstemmed | Investigating the Patterns and Dynamics of Urban Green Space in China’s 70 Major Cities Using Satellite Remote Sensing |
| title_short | Investigating the Patterns and Dynamics of Urban Green Space in China’s 70 Major Cities Using Satellite Remote Sensing |
| title_sort | investigating the patterns and dynamics of urban green space in china s 70 major cities using satellite remote sensing |
| topic | urban green space remote sensing urban park urban ecosystem services China |
| url | https://www.mdpi.com/2072-4292/12/12/1929 |
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