Abstract

Urbanization and the associated change in land cover has been intensifying across the globe in recent decades. Regional studies on the rate and amount of urban expansion are critical for understanding how patterns of change differ within and among cities with varying structure and development characteristics. Yet spatially consistent and timely information on urban development is difficult to access particularly across international jurisdictions. Remote sensing based technologies offer a unique perspective on urban land cover with the data offering significant potential to urban studies due to its consistent and ubiquitous nature. In this research we applied a pixel-based image composite technique to generate annual gap-free surface reflectance Landsat composites from 1984 to 2012 for 25 urban environments across 12 countries in the Pacific Rim. Using time series composites, spectral indices were calculated and compared using a hexagonal grid ring model to assess changes in vegetative and urban patterns. Trajectories were then clustered to further investigate the spatio-temporal dynamics and relationships among the 25 cities. Performance of the clustering analyses varied depended on the temporal and spatial metrics however overall clustering results indicated relatively strong spatio-temporal similarities among a number of key cities. Three pairs of cities—Melbourne and Sydney; Tianjin and Manila; and Singapore City and Kuala Lumpur were found to be highly similar in their urban and vegetation dynamics temporally and spatially. In contrast Vancouver and Las Vegas had no similar analogous. This work demonstrates the value of utilising annual Landsat time series composites for assessing urban vegetation and urban dynamics at regional scales and potential use in sustainable urban planning, resources allocation, and policy making.

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