Ecological analysis of an emerging urban landscape pattern - desakota: a case study in Suzhou, China.

摘要

Recent scholarly efforts to investigate the conventional wisdom of urban transition and conceptualize the distinct patterns of urbanization emerging in China, simply referred to as "desakota", have not yielded any conclusive validation. The possible existence of "desakota" is significant for landscape ecology and regional science research in that it challenges long cherished Western notions concerning the separation of urban processes from rural processes and the spatial uniqueness of the respective landscapes. This paper examines physical evidence of desakota from land use changes and tempo-spatial dynamics of desakota development in the lower Yangtze River Delta - one of the most populous and rapidly growing economic regions in China. The paper uses satellite data in 1990, 1995 and 2000 to spectrally disaggregate such rural landscape patterns as urban construction expanding from existing commercial and industrial centers, rural non-agricultural construction, special large infrastructure construction, and crop cultivation. The paper inspects one transect (60 km long and 12 km wide) cutting across Suzhou City in south and Changshu City in north. The transect is divided into four segments to investigate quantitative changes of land types between the two cities over time. The paper applies landscape ecological metrics to analyze tempo-spatial patterns of desakota changes in terms of counts, densities, shapes, compositions, spatial relationships and diversities. The paper concludes: (1) desakota occurred in Suzhou area before 1990 and witnessed two phases of development, dramatic expansion between 1990 and 1995 and consolidation during 1995-2000; (2) desakota dynamics show distinct spatial patterns, new growth of large and specialized urban districts dominant in the vicinity of large cities (Suzhou) and incremental expansion of existing urban places in small cities and rural areas; and (3) landscape metrics are very informative in discerning dynamics and patterns of land use and land cover changes and different metrics vary in descriptive power and sensitivity..