2019
DOI: 10.3390/su11154091
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A Recursive Definition of Goodness of Space for Bridging the Concepts of Space and Place for Sustainability

Abstract: In a good system, we would expect to find the following conditions: Any identifiable subsystems, we would hope, would be well -that is to say, in good condition. And we would hope that the larger world outside the complex system is also in good order, and well. Thus, the mark of a good system would be that it helps both the systems around it and those which it contains. And the goodness and helping towards goodness is, in our ideal complex system, also reciprocal. That is, our good system, will turn out to be … Show more

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Cited by 12 publications
(12 citation statements)
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References 27 publications
(34 reference statements)
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“…In this process, the aggregation distance is set as 615 meters, which is the mean length of whole TIN edges determined by head/tail breaks [ 54 , 55 ]. Head/tail breaks is a classification scheme or recursive function for deriving inherent hierarchy or heterogeneity of a dataset [ 56 , 57 ]. Step 3: defining urban boundaries.…”
Section: Resultsmentioning
confidence: 99%
“…In this process, the aggregation distance is set as 615 meters, which is the mean length of whole TIN edges determined by head/tail breaks [ 54 , 55 ]. Head/tail breaks is a classification scheme or recursive function for deriving inherent hierarchy or heterogeneity of a dataset [ 56 , 57 ]. Step 3: defining urban boundaries.…”
Section: Resultsmentioning
confidence: 99%
“…The value of these fractal metrics has been interpreted as the degree of wholeness [61], which is conceptualized by the architect Christopher Alexander as a kind of structure of physical space [62]. It has been argued that the greater the fractal metric of a structure has, the more sustainable the structure is [63].…”
Section: Discussionmentioning
confidence: 99%
“…Jiang [13,14] introduced the head/tail breaks as a new classification scheme that enhances the visualization of geographic data that follow a heavy-tailed distribution. The principle underlying the head/tail breaks is straightforward: to split the data into a "head" part and a "tail" part, and optionally to repeat this binary classification process to classify the original data into several categories in a recursive manner [15]. The division rule of head/tail breaks can be based on a preset head-to-tail ratio such as 1:9, or to use the arithmetic mean value as the breakpoint.…”
Section: Head/tail Break As a Methods Of Data Reductionmentioning
confidence: 99%