Quantifying spatiotemporal pattern of urban greenspace: new insights from high resolution data
Quantifying spatiotemporal pattern of urban greenspace: new insights from high resolution data
复制标题
量化城市绿地的时空格局：高分辨率数据的新见解
DOI：
10.1007/s10980-015-0195-3
复制
发表时间：
2015-08-01
影响因子：
5.2
通讯作者：
Pickett, Steward T. A.
中科院分区：
文献类型：
--
作者：
Qian, Yuguo;Zhou, Weiqi;Pickett, Steward T. A.
Urban Greenspace提供无数的生态系统服务。为了充分了解城市绿空间提供的生态服务，至关重要的是，首先准确量化了城市绿色空间的组成和配置以及变化。（1）量化高度城市化地区的绿地动力学。 （2）比较和评估中等和高分辨率图像数据对量化城市绿色绿色空间动力学的疗效。使用两个非常发达的北京城市地区，我们根据两个不同的数据集比较和对比2005年的城市绿色城市空间的变化，最常用的Landsat TM数据分辨率为30 m，高空间分辨率图像。我们找到了Urban与先前研究的发现相比，北京两个发达的城市地区的绿色空间非常有活力，因为在内城市中绿色的绿地往往在很大程度上保持不变。但是，这种动态只能通过高空间分辨率图像来揭示，因为中等分辨率数据（例如TM数据）极大地低估了Greenspace的百分比覆盖率。低估了忽略绿色空间的较小要素以及较大贴片的配置的变化，从而限制了TM数据检测此类更改的能力。您的结果强调了使用高空间分辨率数据的重要性和必要性，以充分量化Urban Greenspace和Urban Greenspace和Urban Greenspace和Urban Greenspace和Urban Greenspace的分布它的变化。这项研究的结果对城市绿地管理和计划具有重要意义。此外，动态揭示了支持城市地区的新兴概念作为分层斑块马赛克。
ContextUrban greenspace provides myriad ecosystem services. To fully understand the ecological services provided by urban greenspace, it is crucial to first accurately quantify the composition and configuration, and change of urban greenspace.Objectives(1) Quantify the dynamics of greenspace in highly urbanized areas. (2) Compare and evaluate the efficacy of medium and high resolution image data on quantifying urban greenspace dynamics.MethodsUsing two very well-developed urban districts of Beijing, we compare and contrast the changes in urban greenspace from 2005 to 2009 based on two different datasets, the most commonly used Landsat TM data with 30 m resolution, and 2.5 m high spatial resolution imagery.ResultsWe found urban greenspace in the two well-developed urban districts of Beijing to be very dynamic, in contrast to findings from previous research that greenspace in inner cities tends to remain largely unchanged. Such dynamics, however, could only be revealed by high spatial resolution imagery because medium resolution data, such as TM data greatly underestimated the percent cover of greenspace. The underestimate neglects smaller elements of greenspace as well as changes in configuration of larger patches, limiting the ability of TM data to detect such changes.ConclusionsOur results underscore the importance and necessity of using high spatial resolution data to adequately quantify the distribution of urban greenspace and its change. Results from this study have important implications for urban greenspace management and planning. In addition, the dynamics revealed support emerging conceptions of urban areas as hierarchical patch mosaics.