In this paper we consider how viewing population distribution as a landscape can aid our understanding of urban morphology and process. Such surfaces are characterised by a highly positively skewed distribution and usually appear ‘spikey’ when viewed obliquely. Two methods are suggested to overcome this problem, namely local and focal transformations. An alternative measure of population density, that of linear density, is suggested as a way of normalising the data. Quadratic smoothing is suggested as a method of focal transformation that allows surface properties to be quantified and generalised. With the Greater London area as an example, population surfaces are visualised in a variety of ways including animation. Properties of the surface such as slope and curvature are calculated and visualised. These help to describe the morphology of the London area population with respect to its evolution over time, planning regulation, and transport links. More sophisticated properties of the surface including morphometric features and inverted basins are identified and related to urban neighbourhoods.
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References
1.
BarnesJ ARobinsonA H, 1940, “A new method for the representation of dispersed rural population”Geographical Review30, 134–137
2.
BattyMLongleyP, 1994Fractal Cities: A Geometry of Form and Function (Academic Press, London)
BrackenI, 1994, “Towards improved visualization of socio-economic data”, in Visualization in Geographical Information Systems Eds HearnshawHUnwinD (John Wiley, Chichester, Sussex) pp 76–84
5.
BrackenIMartinD, 1995, “Linkage of the 1981 and 1991 censuses using surface modelling techniques”Environment and Planning A27, 379–390
6.
ChorleyR J (Ed.), 1969, “The drainage basin as the fundamental geomorphic unit”, in Introduction to Physical Hydrology (Methuen, London) pp 37–59
7.
ClarkP JEvansF C, 1954, “Distance to nearest neighbour as a measure of spatial relationships in populations”Ecology35, 445–453
8.
CourtA, 1966, “The inter-neighbor interval”Yearbook of the Association of Pacific Coast Geographers28, 180–182
9.
EvansI S, 1972, “General geomorphometry, derivatives of altitude and descriptive statistics”, in Spatial Analysis in Geomorphology Ed. ChorleyR J (Methuen, London) pp 17–90
10.
EvansI S, 1977, “The selection of class intervals”Transactions of the Institute of British Geographers, New Series2(1) 98–124
11.
EvansI S, 1980, “An integrated system of terrain analysis and slope mapping”Zeitschrift fur GeomorphologieSupplBd 36, 274–295
12.
HearnshawH MUnwinD J (Eds), 1994Visualization in Geographical Information Systems (John Wiley, Chichester, Sussex)
13.
JensonJ, 1978, “Three-dimensional choropleth maps: Development and aspects of cartographic communication”The Canadian Cartographer15, 123–141
14.
LangfordMUnwinD, 1994, “Generating and mapping population density surfaces within a geographical information system”The Cartographic Journal31, 21–26
15.
LynchK, 1960The Image of the City (MIT Press, Cambridge, MA)
MarkD M, 1975, “Computer analysis of topography: A comparison of terrain storage methods”Geografiska Annaler57A (3–4) 179–188
18.
MarksDDozierJFrewJ, 1983, “Automated basin delineation from digital terrain data”, NASA Technical Memorandum 84984 Goddard Space Flight Center Greenbelt, Maryland 2D771, USA
19.
MartinD, 1989, “Mapping population data from zone centroid locations”Transactions of the Institute of British Geographers, New Series14(1) 90–97
20.
MartinD, 1991Geographic Information Systems and Their Socioeconomic Applications (Routledge, London) pp 153–158
21.
MartinD, 1996, “An assessment of surface and zonal models of population”International Journal of Geographical Information Systems10, 973–989
22.
MartinDBrackenI, 1991, “Techniques for modelling population related raster databases”Environment and Planning A23, 1069–1075
23.
MC, 19941981 and 1991 Population Surface Models: A Guide. Manchester Information Datasets and Associated ServicesManchester Computing, University of Manchesterhttp://cs6400.mcc.ac.uk/docs.html
24.
NordbeckSRystedtB, 1970, “Isarithmic maps and the continuity of reference interval functions”Geografiska Annaler52B(2) 92–123
25.
ObergSSpringfeldtP, 1991The Population (SNA Publishing, Stockholm)
26.
OpenshawS, 1984The Modifiable Areal Unit Problem, in the Concepts and Techniques in Modern Geography series, number 38 (Geo Books, Norwich)
SilvermanB, 1986Density Estimation for Statistics and Data Analysis (Chapman and Hall, London)
29.
ToblerW, 1973, “Choropleth maps without class intervals”Geographical Analysis5, 262–265
30.
ToblerW, 1995, “The Resel-based GIS”International Journal of Geographic Information Systems91(1) 95–100
31.
ToblerWDeichmannUGottsegenJMaloyK, 1995, “The global demography project”, technical report 95–6, National Center for Geographic Information and Analysis, Santa Barbara, CA
32.
TomlinC D, 1990Geographic Information Systems and Cartographic Modelling (Prentice-Hall, Englewood Cliffs, NJ)
33.
TufteE R, 1983The Visual Display of Quantitative Information (Graphics Press, Cheshire, CT)
34.
WarntzW, 1966, “The topology of social economic terrain and spatial flows”Papers of the Regional Science Association17, 47–61
35.
WolfG W, 1984, “A mathematical model of cartographic generalisation”Geo-Processing2, 271–286
36.
WoodJ D, 1996, “Scale based characterisation of digital elevation models”, in Innovations in GIS 3 Ed. ParkerD (Taylor and Francis, London) pp 163–175
