Categorization of green and grey infrastructure complexity in the rural–urban interface of Bengaluru, India: an unsupervised volumetric approach with relevance for urban quality

被引:0
|
作者
Nils Nölke
Lutz Fehrmann
Tobias Plieninger
Christoph Kleinn
机构
[1] University of Göttingen,Forest Inventory and Remote Sensing
[2] University of Göttingen,Department of Agricultural Economics and Rural Development
[3] University of Kassel,Faculty of Organic Agricultural Sciences
来源
Urban Ecosystems | 2023年 / 26卷
关键词
Rurban configurations; Satellite imagery; Machine learning; 3D metric;
D O I
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中图分类号
学科分类号
摘要
Trees are key elements of urban green infrastructure and provide multiple ecosystem services that are essential for the quality of life of people in urban environments. Grey infrastructure is made up of buildings or built-up area, generally characterized by imperviousness of the surface. The complexity of urban green and grey infrastructure and their interactions co-define the quality of urban life and the ecological value of urban areas. Using conventional dichotomies by separation into “urban” and “rural” contexts does hardly allow to comprehensively assess the situation in rapidly urbanizing environments of the Global South. We present an unsupervised remote sensing-based approach that integrates 3D information to objectively categorize the complexity of green and grey infrastructure. Using the rural–urban interface of Bengaluru, India, as a case example, we distinguished five categories that describe the composition and configuration of green and grey infrastructure, where three variables served as indicators for categorization into five clusters. We argue that such integrated 3D assessment of green and grey infrastructure is particularly useful for understanding and classifying “rurban” environments, where a distinction between urban and rural is often no longer possible. Our final map allows to quantitatively characterize such rurban configurations.
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页码:161 / 172
页数:11
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