中国地理科学 ›› 2021, Vol. 31 ›› Issue (1): 93-108.doi: 10.1007/s11769-021-1177-9

• Big Data and Urban Study • 上一篇    下一篇

Rapid Urbanization Induced Extensive Forest Loss to Urban Land in the Guangdong-Hong Kong-Macao Greater Bay Area, China

YANG Chao1,2, LIU Huizeng1, LI Qingquan1, CUI Aihong3, XIA Rongling4, SHI Tiezhu1,5, ZHANG Jie1, GAO Wenxiu5, ZHOU Xiang1, WU Guofeng1,5   

  1. 1. MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area & Guangdong Key Laboratory of Urban Informatics & Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen 518060, China;
    2. College of Information Engineering, Shenzhen University, Shenzhen 518060, China;
    3. Department of Geography, Hong Kong Baptist University, Hong Kong 999077, China;
    4. School of Land and Resources Engineering, Kunming University of Science and Technology, Kunming 650093, China;
    5. School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China
  • 收稿日期:2020-05-21 发布日期:2021-01-05
  • 通讯作者: LI Qingquan, WU Guofeng E-mail:liqq@szu.edu.cn;guofeng.wu@szu.edu.cn
  • 基金资助:
    Under the auspices of National Natural Science Foundation of China (No. 41890854), Basic Research Program of Shenzhen Science and Technology Innovation Committee (No. JCYJ20180507182022554), National Key R & D Program of China (No. 2017YFC0506200), National Natural Science Foundation of China (No. 7181101150), National Natural Science Foundation of China (No. 41901248), Shenzhen Future Industry Development Funding Program (No. 201507211219247860)

Rapid Urbanization Induced Extensive Forest Loss to Urban Land in the Guangdong-Hong Kong-Macao Greater Bay Area, China

YANG Chao1,2, LIU Huizeng1, LI Qingquan1, CUI Aihong3, XIA Rongling4, SHI Tiezhu1,5, ZHANG Jie1, GAO Wenxiu5, ZHOU Xiang1, WU Guofeng1,5   

  1. 1. MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area & Guangdong Key Laboratory of Urban Informatics & Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen 518060, China;
    2. College of Information Engineering, Shenzhen University, Shenzhen 518060, China;
    3. Department of Geography, Hong Kong Baptist University, Hong Kong 999077, China;
    4. School of Land and Resources Engineering, Kunming University of Science and Technology, Kunming 650093, China;
    5. School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China
  • Received:2020-05-21 Published:2021-01-05
  • Contact: LI Qingquan, WU Guofeng E-mail:liqq@szu.edu.cn;guofeng.wu@szu.edu.cn
  • Supported by:
    Under the auspices of National Natural Science Foundation of China (No. 41890854), Basic Research Program of Shenzhen Science and Technology Innovation Committee (No. JCYJ20180507182022554), National Key R & D Program of China (No. 2017YFC0506200), National Natural Science Foundation of China (No. 7181101150), National Natural Science Foundation of China (No. 41901248), Shenzhen Future Industry Development Funding Program (No. 201507211219247860)

摘要: China has experienced rapid urbanizations with dramatic land cover changes since 1978. Forest loss is one of land cover changes, and it induces various eco-environmental degradation issues. As one of China’s hotspot regions, the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) has undergone a dramatic urban expansion. To better understand forest dynamics and protect forest ecosystem, revealing the processes, patterns and underlying drivers of forest loss is essential. This study focused on the spatiotemporal evolution and potential driving factors of forest loss in the GBA at regional and city level. The Landsat time-series images from 1987 to 2017 were used to derive forest, and landscape metrics and geographic information system (GIS) were applied to implement further spatial analysis. The results showed that: 1) 14.86% of the total urban growth area of the GBA was obtained from the forest loss in 1987–2017; meanwhile, the forest loss area of the GBA reached 4040.6 km2, of which 25.60% (1034.42 km2) was converted to urban land; 2) the percentages of forest loss to urban land in Dongguan (19.14%), Guangzhou (18.35%) and Shenzhen (15.81%) were higher than those in other cities; 3) the forest became increasingly fragmented from 1987–2007, and then the fragmentation decreased from 2007 to 2017); 4) the landscape responses to forest changes varied with the scale; and 5) some forest loss to urban regions moved from low-elevation and gentle-slope terrains to higher-elevation and steep-slope terrains over time, especially in Shenzhen and Hong Kong. Urbanization and industrialization greatly drove forest loss and fragmentation, and, notably, hillside urban land expansion may have contributed to hillside forest loss. The findings will help policy makers in maintaining the stability of forest ecosystems, and provide some new insights into forest management and conservation.

关键词: forest loss to urban land, urbanization, spatiotemporal pattern, remote sensing, Guangdong-Hong Kong-Macao Greater Bay Area (GBA)

Abstract: China has experienced rapid urbanizations with dramatic land cover changes since 1978. Forest loss is one of land cover changes, and it induces various eco-environmental degradation issues. As one of China’s hotspot regions, the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) has undergone a dramatic urban expansion. To better understand forest dynamics and protect forest ecosystem, revealing the processes, patterns and underlying drivers of forest loss is essential. This study focused on the spatiotemporal evolution and potential driving factors of forest loss in the GBA at regional and city level. The Landsat time-series images from 1987 to 2017 were used to derive forest, and landscape metrics and geographic information system (GIS) were applied to implement further spatial analysis. The results showed that: 1) 14.86% of the total urban growth area of the GBA was obtained from the forest loss in 1987–2017; meanwhile, the forest loss area of the GBA reached 4040.6 km2, of which 25.60% (1034.42 km2) was converted to urban land; 2) the percentages of forest loss to urban land in Dongguan (19.14%), Guangzhou (18.35%) and Shenzhen (15.81%) were higher than those in other cities; 3) the forest became increasingly fragmented from 1987–2007, and then the fragmentation decreased from 2007 to 2017); 4) the landscape responses to forest changes varied with the scale; and 5) some forest loss to urban regions moved from low-elevation and gentle-slope terrains to higher-elevation and steep-slope terrains over time, especially in Shenzhen and Hong Kong. Urbanization and industrialization greatly drove forest loss and fragmentation, and, notably, hillside urban land expansion may have contributed to hillside forest loss. The findings will help policy makers in maintaining the stability of forest ecosystems, and provide some new insights into forest management and conservation.

Key words: forest loss to urban land, urbanization, spatiotemporal pattern, remote sensing, Guangdong-Hong Kong-Macao Greater Bay Area (GBA)