Yu Zhoulu, Wang Yaohui, Deng Jinsong, Shen Zhangquan, Wang Ke, Zhu Jinxia, Gan Muye
Institute of Applied Remote Sensing and Information Technology, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China.
State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China.
Sensors (Basel). 2017 Jun 6;17(6):1304. doi: 10.3390/s17061304.
Accurately quantifying the variation of urban green space is the prerequisite for fully understanding its ecosystem services. However, knowledge about the spatiotemporal dynamics of urban green space is still insufficient due to multiple challenges that remain in mapping green spaces within heterogeneous urban environments. This paper uses the city of Hangzhou to demonstrate an analysis methodology that integrates sub-pixel mapping technology and landscape analysis to fully investigate the spatiotemporal pattern and variation of hierarchical urban green space patches. Firstly, multiple endmember spectral mixture analysis was applied to time series Landsat data to derive green space coverage at the sub-pixel level. Landscape metric analysis was then employed to characterize the variation pattern of urban green space patches. Results indicate that Hangzhou has experienced a significant loss of urban greenness, producing a more fragmented and isolated vegetation landscape. Additionally, a remarkable amelioration of urban greenness occurred in the city core from 2002 to 2013, characterized by the significant increase of small-sized green space patches. The green space network has been formed as a consequence of new urban greening strategies in Hangzhou. These strategies have greatly fragmented the built-up areas and enriched the diversity of the urban landscape. Gradient analysis further revealed a distinct pattern of urban green space landscape variation in the process of urbanization. By integrating both sub-pixel mapping technology and landscape analysis, our approach revealed the subtle variation of urban green space patches which are otherwise easy to overlook. Findings from this study will help us to refine our understanding of the evolution of heterogeneous urban environments.
准确量化城市绿地的变化是充分理解其生态系统服务的前提。然而,由于在异质城市环境中绘制绿地仍面临多重挑战,关于城市绿地时空动态的知识仍然不足。本文以杭州市为例,展示一种整合亚像素映射技术和景观分析的分析方法,以全面研究分层城市绿地斑块的时空格局和变化。首先,将多端元光谱混合分析应用于陆地卫星时间序列数据,以获取亚像素级别的绿地覆盖率。然后采用景观指标分析来表征城市绿地斑块的变化模式。结果表明,杭州城市绿地显著减少,形成了更加破碎和孤立的植被景观。此外,2002年至2013年期间,城市核心区域的城市绿化显著改善,其特征是小型绿地斑块显著增加。杭州新的城市绿化策略形成了绿地网络。这些策略极大地分割了建成区,丰富了城市景观的多样性。梯度分析进一步揭示了城市化进程中城市绿地景观变化的独特模式。通过整合亚像素映射技术和景观分析,我们的方法揭示了城市绿地斑块容易被忽视的细微变化。本研究结果将有助于我们深化对异质城市环境演变的理解。