4.7 Article

Measuring long-term ecological changes in densely populated landscapes using current and historical high resolution imagery

期刊

REMOTE SENSING OF ENVIRONMENT
卷 100, 期 4, 页码 457-473

出版社

ELSEVIER SCIENCE INC
DOI: 10.1016/j.rse.2005.11.002

关键词

human dominated ecosystems; land-use change; feature-based mapping; landscape classification; long-term ecological change; ecological history; urban landscapes; suburbs; villages; landscape ecology

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Long-term ecological changes within densely populated landscapes account for a growing share of global environmental change. Measuring the causes and consequences of these changes remains a challenge because of their fine spatial scale and complexity. Here, we measure long-term ecological changes, circa 1950 to 2002, within six 1 km(2) sites in densely populated rural China and in urban and suburban Baltimore, Maryland, USA using a standardized procedure for fine-scale feature-based ecological mapping from high spatial resolution (<= 1 in) imagery. The median size of ecologically distinct landscape features (ecotopes) mapped by this procedure was just 520 m(2), though size, count and perimeter of features varied considerably both within and between sites. Land management and vegetation cover changed substantially, over 28% to 87% of site areas, but most of this change occurred in small patches with area < 4000 m(2). Landscape complexity also increased over time by the fragmentation of landscapes into a larger number of smaller features with an increasing diversity of ecotope classes. Detailed analysis of fine-scale landscape transformations helped identify the causes and consequences of ecologically significant changes within and across sites, including unexpected increases in perennial vegetation cover and the linkage of impervious surface area with population density. These and other results demonstrate the general utility of anthropogenic ecotope mapping as a tool for cross-site comparison and sampled regional estimates of long-term ecological changes within densely populated landscapes. (c) 2005 Elsevier Inc. All rights reserved.

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