Spatial Distribution of Human Population in<scp>F</scp>rance: Exploring the Modifiable Areal Unit Problem Using Multifractal Analysis

Sémécurbe, François; Tannier, Cécile; Roux, Stéphane

doi:10.1111/gean.12099

Cited by 30 publications

(39 citation statements)

References 34 publications

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“…Current spatial multifractal studies mainly focus on the analysis of the numerical fluctuation of spatial data and the grid fractal dimension and the radius fractal dimension of the physical space (Appleby, 1996;Ariza-Villaverde et al, 2013;Ihlen, 2012;Kantelhardt Jan. et al, 2002;Sémécurbe et al, 2016;Thomas et al, 2007Thomas et al, , 2008. The purpose of this approach is to determine the circumstances of the change in the overall and local characteristics of a spatial system along with the D q value of the generalized correlation dimension to clarify its evolutionary structure and developmental trend.…”

Section: Methodsmentioning

confidence: 99%

Multifractal features of spatial variation in construction land in Beijing (1985–2015)

Song

2019

Palgrave Commun

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Over the last 30 years, Beijing has experienced rapid development. The city's spatial pattern and changes are extremely complicated. Therefore, to reveal the spatial patterns at different scales and levels, the construction land in Beijing within the 6th ring road in 1985, 1999, 2008, and 2015, was analyzed using global and local multifractal analyses. The global analysis shows that, over the past 30 years, the development of new construction land in this region experienced a process that transformed it from being a hierarchical spatial structure with a low-evolution intensity (1985) to being a spatial structure with a higher evolution intensity and multi-scale differential development (1999, 2008) with a hierarchical spatial system (one main urban area with a number of satellite towns) (2015). Local analysis further shows that the spatial pattern of the construction land in this region tended to be simplified over the past 30 years. The construction land in this region displays specific evolutionary characteristics with the increase in breadth (q) and intensity (D q ) and a multifractal dimension spectrum (f(a) -a(q)) and dominant spectrum at various spatial scales over a four-year period. In general, the influence of high-density areas on the spatial pattern of the construction land is decreasing, while the influence of low-density areas is increasing. Based on this, this paper also summarizes the theoretical value of multifractal analysis in economic geography research, highlighting its advantages, limitations, and application range, and presents the technical analysis process and other suggestions for future research.

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Section: Methodsmentioning

confidence: 99%

Multifractal features of spatial variation in construction land in Beijing (1985–2015)

Song

2019

Palgrave Commun

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“…The classification of scaling indexes obtained with GWFA has enabled the identification of six types of built patterns whose multiscale spatial organization is well differentiated. Sémécurbe, Tannier & Roux (2016) have previously identified similar types of settlement patterns by applying a multifractal analysis on fine-grained population data. That previous study was coarser-grained as mainland France was divided into 992 square spatial units 25 km wide (the present study considered 145,178 estimation points i 2 km apart).…”

Section: For Twenty Middle-size Metropolitan Areas Identification Ofmentioning

confidence: 99%

Applying two fractal methods to characterise the local and global deviations from scale invariance of built patterns throughout mainland France

Sémécurbe¹,

Tannier²,

Roux

2018

J Geogr Syst

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In the early twentieth century a handful of French geographers and historians famously suggested that mainland France comprised two agrarian systems: enclosed field systems with scattered settlements in the central and western France, and openfield systems with grouped settlements in eastern France. This division between grouped and scattered settlements can still be found on the outskirts of urban areas. The objective of this paper is to determine whether the shape of urban areas varies with the type of built patterns in their periphery. To this end, we identify and characterise the local and global deviations from scale-invariance of built patterns in mainland France. For this, we propose a new method-Geographically Weighted Fractal Analysis-that can characterise built patterns at a fine spatial resolution without making any a priori distinction between urban patterns and suburban or rural patterns. By applying GWFA to the spatial distribution of buildings throughout mainland France we identify six geographically consistent types of built patterns that are distinctive in the way buildings are either concentrated or dispersed across scales. The relationship between the local built textures and the global shape of twenty metropolitan areas is then analysed statistically. It is found that the proportion of dispersed (or concentrated) outer suburban built patterns in metropolitan areas is closely related to the distance threshold that marks the morphological limit of their urban areas.

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“…For SPC problems, variances due to scale may be a critical aspect of pattern‐observation and thus comparison. Sémécurbe, Tannier, and Roux () provide an example of using multifractal analysis that quantifies MAUP to better understand spatial heterogeneities in population density in France, developing a typology of settlement patterns.…”

Section: Moving the Spatial Pattern Comparison Research Agenda Forwardmentioning

confidence: 99%

“…For SPC problems, variances due to scale may be a critical aspect of pattern-observation and thus comparison. Sémécurbe, Tannier, and Roux (2016) provide an example of using multifractal analysis that quantifies MAUP to better understand spatial heterogeneities in population density in France, developing a typology of settlement patterns. Yan and Li (2015) stress the need for both mathematical and psychological justifications in the definition of spatial similarity measures (i.e., linking similarity to the HVS).…”

Section: Scale and Maupmentioning

confidence: 99%

Comparing spatial patterns

Long

Robertson

2017

Geography Compass

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The comparison of spatial patterns is a fundamental task in geography and quantitative spatial modelling. With the growth of data being collected with a geospatial element, we are witnessing an increased interest in analyses requiring spatial pattern comparisons (e.g., model assessment and change analysis). In this paper, we review quantitative techniques for comparing spatial patterns, examining key methodological approaches developed both within and beyond the field of geography. We highlight the key challenges using examples from widely known datasets from the spatial analysis literature. Through these examples, we identify a problematic dichotomy between spatial pattern and process—a widespread issue in the age of big geospatial data. Further, we identify the role of complex topology, the interdependence of spatial configuration and composition, and spatial scale as key (research) challenges. Several areas ripe for geographic research are discussed to establish a consolidated research agenda for spatial pattern comparison grounded in quantitative geography. Hierarchical scaling and the modifiable areal unit problem are highlighted as ideas which can be exploited to identify pattern similarities across spatial and temporal scales. Increased use of “time‐aware” comparisons of spatial processes are suggested, which properly account for spatial evolution and pattern formation. Simulation‐based inference is identified as particularly promising for integrating spatial pattern comparison into existing modelling frameworks. To date, the literature on spatial pattern comparison has been fragmented, and we hope this work will provide a basis for others to build on in future studies.

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Spatial Distribution of Human Population inFrance: Exploring the Modifiable Areal Unit Problem Using Multifractal Analysis

Cited by 30 publications

References 34 publications

Multifractal features of spatial variation in construction land in Beijing (1985–2015)

Multifractal features of spatial variation in construction land in Beijing (1985–2015)

Applying two fractal methods to characterise the local and global deviations from scale invariance of built patterns throughout mainland France

Comparing spatial patterns

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