Quantifying spatiotemporal pattern of urban greenspace: new insights from high resolution data

Abstract

Urban 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. (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. Using 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. We 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. Our 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.