Measuring fragmentation of open space in urbanised Flanders: an evaluation of four methods

Verbeek, Thomas; Tempels, Barbara

doi:10.4000/belgeo.17164

Cited by 6 publications

(8 citation statements)

References 35 publications

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“…For a focus on the human appreciation of open spaces, this straightforward approach is not very helpful because of the ambiguous relation that the cultural services offered by open spaces have with infrastructure: roads increase the accessibility of open spaces but may decrease their quality when they are large or intensively used. Similar differences between ecological and human-centred views are also noted by Verbeek and Tempels (2016) who point out that depending on the chosen perspective the fragmentation effects of similar landscape elements can be very different.…”

Section: Introductionsupporting

confidence: 57%

“…We deem open space to refer to all territorial space of the Netherlands that is not covered by built-up structures. (Chiesura, 2004;Verbeek & Tempels, 2016). In this respect they "reduce the restorative effect of everyday landscapes" (Di Giulio et al, 2009Giulio et al, , p. 2963.…”

Section: Methodology and Data Preparationmentioning

confidence: 99%

“…Frenkel & Ashkenazi, 2008;Mubareka, Koomen, Estreguil, & Lavalle, 2011;OECD, 2018;Schwarz, 2010). Our approach is different in the sense that we focus on the impacts of urban development on the remaining open spaces, which is more comparable to the way Verbeek and Tempels (2016), for example, evaluate the fragmentation of open space in Belgium (Flanders) from a spatial planning perspective. As such our approach is more closely related to planning efforts that try to preserve open space rather than contain urban development.…”

Section: Introductionmentioning

confidence: 99%

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An indicator set for capturing long-term open space fragmentation and urban development dynamics

Wagtendonk

Koomen

2019

Computers, Environment and Urban Systems

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Open space preservation is an important spatial policy issue in developed, densely populated countries. Understanding open space dynamics in relation to urban development is critical to the development and evaluation of such policies. Starting from a conceptual model that hypotheses how open space will have developed over the past century we use a set of landscape ecology based indicators to capture these changes from a societal (perceptional) perspective. The indicators are applied to a newly compiled geodatabase of urban development in the Netherlands to show their performance in detecting and understanding past and future trends in open space provision. Our combined indicator set consists of land-use-based metrics that capture the area ratio of open space in relation to the total available space and total unit density of open and built-up patches. The methodology is designed to fit the low spatial and thematic resolution of land-use models as is exemplified by the inclusion of a future land-use scenario in the evaluation of open space development. The indicators confirm the hypothesised intrusion, intermediate and fill-up phases in open space fragmentation, and indicate a strong correlation between fragmentation and loss of open area. The results facilitate the distinguishing of compact urban regions from more fragmented counterparts while taking their relative state of urban development into account. The combined indicator set is useful to summarise and compare spatial development status between regions, while in combination with the advent of more detailed historic land-use data, our approach can be used to analyse open-space dynamics in different socioeconomic contexts.

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Section: Introductionsupporting

confidence: 57%

Section: Methodology and Data Preparationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An indicator set for capturing long-term open space fragmentation and urban development dynamics

Wagtendonk

Koomen

2019

Computers, Environment and Urban Systems

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“…Control of built-up expansion through compact and ribbon development scheme is a strategy and better solution for controlling urban growth because it is related to spatialdensity patterns as the main key [44]. Compact and ribbon development in Cirebon's peri-urban should be implemented, due to reasons of accessibility, regional interactions with megapolitan areas, and its historical aspects [45,46,47]. In addition, compact and ribbon development is the path to a sustainable city because it prioritizes urban space efficiency.…”

Section: Lulc Simulation and Scenariosmentioning

confidence: 99%

Spatial dynamics model of land use and land cover changes: A comparison of CA, ANN, and ANN-CA

Dede

Asdak

Setiawan

2021

regist. j. ilm. teknol. sist. inf.

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Land use and land cover (LULC) changes through built-up area expansion always increases linearly with land demand as a consequence of population growth and urbanization. Cirebon City is a center for Ciayumajakuning Region that continues to grow and exceeds its administrative boundaries. This phenomenon has led to peri-urban regions which show urban and rural interactions. This study aims to analyze (1) the dynamics of LULC changes using cellular automata (CA), artificial neural network (ANN), and ANN-CA; (2) the influential factors (drivers); and (3) change probability in the period 2030 and 2045 for Cirebon’s peri-urban. We used logistic regression as quantitative approach to analyze the interaction of drivers and LULC changes. The LULC data derived from Landsat series satellite imagery in 1999-2009 and 2009-2019, validation of dynamic spatial model refers to 100 LULC samples. This research shows that LULC changes are dominated by built-up area expansion which causes plantations and agricultural land to decrease. The drivers have a simultaneous effect on LULC changes with r-square of 0.43, where land slope, distance from existing built-up area, distance from CBD, and accessibility are significant triggers. LULC simulation of CA algorithm is the best model than ANN and ANN-CA based on overall accuracy and overall accuracy (0.96, 0.75, 0.73 and 0.95, 0.66, 0.66 respectively), it reveals urban sprawl through the ribbon and compact development. The average probability of built-up area expansion is 0.18 (2030) and 0.19 (2045). If there is no intervention in spatial planning, this phenomenon will decrease productive agricultural lands in Cirebon's peri-urban.

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“…Angel et al [5] defined ribbon development as built-up areas that are less than 100 m wide and have less than 30% built-up neighborhoods. Verbeek et al [48,49] identified ribbon development as any patch with 200 m minimum length or if the ratio between the patch length and the adjoining road is more than 80%. In our study, edge-ribbon is any edge-expansion patch that adjoins a corridor (i.e., roads and irrigation networks) such that the patch has a linear shape.…”

Section: Identifying Human Settlement Growth Typesmentioning

confidence: 99%

Spatial and Temporal Human Settlement Growth Differentiation with Symbolic Machine Learning for Verifying Spatial Policy Targets: Assiut Governorate, Egypt as a Case Study

et al. 2020

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Since 2005, Egypt has a new land-use development policy to control unplanned human settlement growth and prevent outlying growth. This study assesses the impact of this policy shift on settlement growth in Assiut Governorate, Egypt, between 1999 and 2020. With symbolic machine learning, we extract built-up areas from Landsat images of 2005, 2010, 2015, and 2020 and a Landscape Expansion Index with a new QGIS plugin tool (Growth Classifier) developed to classify settlement growth types. The base year, 1999, was produced by the national remote sensing agency. After extracting the built-up areas from the Landsat images, eight settlement growth types (infill, expansion, edge-ribbon, linear branch, isolated cluster, proximate cluster, isolated scattered, and proximate scattered) were identified for four periods (1999:2005, 2005:2010, 2010:2015, and 2015:2020). The results show that prior to the policy shift of 2005, the growth rate for 1999–2005 was 11% p.a. In all subsequent periods, the growth rate exceeded the target rate of 1% p.a., though by varying amounts. The observed settlement growth rates were 5% (2005:2010), 7.4% (2010:2015), and 5.3% (2015:2020). Although the settlements in Assiut grew primarily through expansion and infill, with the latter growing in importance during the last two later periods, outlying growth is also evident. Using four class metrics (number of patches, patch density, mean patch area, and largest patch index) for the eight growth types, all types showed a fluctuated trend between all periods, except for expansion, which always tends to increase. To date, the policy to control human settlement expansion and outlying growth has been unsuccessful.

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Measuring fragmentation of open space in urbanised Flanders: an evaluation of four methods

Cited by 6 publications

References 35 publications

An indicator set for capturing long-term open space fragmentation and urban development dynamics

An indicator set for capturing long-term open space fragmentation and urban development dynamics

Spatial dynamics model of land use and land cover changes: A comparison of CA, ANN, and ANN-CA

Spatial and Temporal Human Settlement Growth Differentiation with Symbolic Machine Learning for Verifying Spatial Policy Targets: Assiut Governorate, Egypt as a Case Study

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