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Dynamic Pattern of Agricultural Landscapes in Response to Urbanization across Hangzhou Metropolitan Region: A Remote Sensing Approach

机译:杭州都市圈农业景观对城市化响应的动态格局:遥感方法

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This paper applied multiple endmember spectral mixture analysis (MESMA) to interpret Landsat satellite imageries and then analyzed the spatiotemporal dynamics of agricultural landscapes within Hangzhou metropolitan region. Between 1994 and 2003, this region has witnessed accelerated urbanization based on four indicators: total population, percentage of non-agriculture population, GDP per capita, and area of impervious surface. Meanwhile, conversion, fragmentation, irregularity and isolation of agricultural landscapes were also captured according to four class-level metrics: total area, patch density, area-weighted mean shape index, and Euclidean nearest neighbor distance. Statistics showed that increased impervious area was significantly correlated with declined area and configuration of agricultural landscapes. Growth in GDP per capita was also correlated with increased irregularity of agricultural landscapes. Changes of total population and percentage of non-agriculture population were weakly associated with all the agricultural landscape metrics, denoting that the two indicators did not have direct influences on agricultural landscape patterns. Further, distance to the nearest road was also a good indicator of how the cultivated land was lost and transformed. Our results demonstrated complexities of relationships between urbanization and agricultural landscapes, and highlighted the importance of selected variables, spatiotemporal scales and land-use classification when quantifying these relationships.
机译:本文应用多端元光谱混合分析法(MESMA)解释Landsat卫星图像,然后分析了杭州市区内农业景观的时空动态。从1994年到2003年,该地区的城市化进程基于四个指标:总人口,非农业人口百分比,人均GDP和不透水面积。同时,还根据四个类别级别的指标捕获了农业景观的转化,破碎,不规则和孤立:总面积,斑块密度,面积加权平均形状指数和欧几里得最近邻距离。统计数据表明,不透水面积的增加与农业景观面积的减少和格局的显着相关。人均国内生产总值的增长也与农业景观的不规则性增加有关。总人口和非农业人口百分比的变化与所有农业景观指标均呈弱关联,表明这两个指标对农业景观格局没有直接影响。此外,到最近道路的距离也很好地指示了耕地如何流失和转化。我们的结果证明了城市化与农业景观之间关系的复杂性,并强调了量化这些关系时所选变量,时空尺度和土地利用分类的重要性。

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