2023
DOI: 10.1016/j.apgeog.2023.102927
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Capturing open space fragmentation in high–density cities: Towards sustainable open space planning

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Cited by 19 publications
(8 citation statements)
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“…As typical geospatial remote sensing data, the LandScan high-resolution population dataset records global population density; it is produced by the US Department of Energy, Oak Ridge National Laboratory [51]. Compared to traditional statistical data, it provides convenient insights to understand population distribution on a large spatial scale with relatively low cost, facilitating the more accurate determination of urban form [52]. (2) During preprocessing, the remote sensing data are resampled to 1 km and the ADA is recorded to the prefecture-level city.…”
Section: Methodological Frameworkmentioning
confidence: 99%
“…As typical geospatial remote sensing data, the LandScan high-resolution population dataset records global population density; it is produced by the US Department of Energy, Oak Ridge National Laboratory [51]. Compared to traditional statistical data, it provides convenient insights to understand population distribution on a large spatial scale with relatively low cost, facilitating the more accurate determination of urban form [52]. (2) During preprocessing, the remote sensing data are resampled to 1 km and the ADA is recorded to the prefecture-level city.…”
Section: Methodological Frameworkmentioning
confidence: 99%
“…Although these forms of open space fragmentation have been separately recognised, they are seldom considered jointly in a research framework, which imposes a challenge in terms of transferring them as direct instructions to appropriate open space planning. Sources: [7,8].…”
Section: Literature Review 21 Forms and Evaluations Of Open Space Fra...mentioning
confidence: 99%
“…Despite these benefits and strong public demand for open space supply [3], many urban open spaces are fragmenting and disappearing. The complication of urban open space structure has increased because of anthropogenic interference [4,5], whereby open space has shifted from a homogeneous, integrated, and contiguous condition to a heterogeneous, divided, and incoherent state [6][7][8]. The most complicated types of open space mosaics are characterised by morphological segregation and connectional incompatibility [9].…”
Section: Introductionmentioning
confidence: 99%
“…where MFDI is the mean value of functional diversity of UBGS in subdistrict unit i; FDI j,i is the functional diversity index of UBGS j in subdistrict unit i; N is the number of UBGS in subdistrict unit i. (3) Structural connectivity: Referring to the relevant studies by Yu et al [52], the structural connectivity indicator was measured using the mean nearest-neighbor distance index (MNNDI). MNNDI means the sum of the distances between a space and its nearest neighbors divided by the number of spaces with neighbors.…”
Section: Single Indicators Measurementmentioning
confidence: 99%