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Analytical methods for error propagation in planar space–time prisms

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Abstract

The space–time prism demarcates all locations in space–time that a mobile object or person can occupy during an episode of potential or unobserved movement. The prism is central to time geography as a measure of potential mobility and to mobile object databases as a measure of location possibilities given sampling error. This paper develops an analytical approach to assessing error propagation in space–time prisms and prism–prism intersections. We analyze the geometry of the prisms to derive a core set of geometric problems involving the intersection of circles and ellipses. Analytical error propagation techniques such as the Taylor linearization method based on the first-order partial derivatives are not available since explicit functions describing the intersections and their derivatives are unwieldy. However, since we have implicit functions describing prism geometry, we modify this approach using an implicit function theorem that provides the required first-order partials without the explicit expressions. We describe the general method as well as details for the two spatial dimensions case and provide example calculations.

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References

  • Alesheikh AA, Blais JAR, Chapman MA, Karimi H (1999) Rigorous geospatial data uncertainty model for GIS. In: Lowell K, Jaton A (eds) Spatial accuracy assessment: land information uncertainty in natural resources. Ann Arbor Press, Chelsea, pp 195–202

    Google Scholar 

  • Benichou J, Gail MH (1989) A delta-method for implicitly defined random variables. Am Stat 43(1):41–44

    Article  Google Scholar 

  • Burns LD (1979) Transportation, temporal, and spatial components of accessibility. Lexington Press, Lexington

  • Button KJ, Haynes KE, Stopher P, Hensher DA (eds) (2004) Handbook of transport geography and spatial systems, vol 5. Elsevier, Amsterdam

  • Ettema D, Timmermans H (2007) Space-time accessibility under conditions of uncertain travel times: theory and numerical simulations. Geogr Anal 39(2):217–240

    Article  Google Scholar 

  • Goodchild MF (2004) A general framework for error analysis in measurement-based GIS. J Geograph Syst 6(4):323–324

    Article  Google Scholar 

  • Hägerstrand T (1970) What about people in regional science? Pap Reg Sci Assoc 24(1):1–12

    Google Scholar 

  • Hall RW (1983) Travel outcome and performance: the effect of uncertainty on accessibility. Transp Res B 17B(4):275–290

    Article  Google Scholar 

  • Heuvelink G (1998) Error propagation in environmental modelling with GIS. Taylor and Francis, London

    Google Scholar 

  • Heuvelink GBM, Burrough PA, Stein A (1989) Propagation of errors in spatial modeling with GIS. Int J Geogr Inf Syst 3(4):303–322

    Article  Google Scholar 

  • Heuvelink GBM, Burrough PA, Stein A (2007) Developments in analysis of spatial uncertainty since 1989. In: Fisher P (ed) Classics from IJGIS: twenty years of the international journal of geographical science and systems. Taylor and Francis, London, pp 91–95

    Google Scholar 

  • Kiiveri HT (2007) Assessing, representing and transmitting uncertainty in GIS: ten years on. In: Fisher P (ed) Classics from IJGIS: twenty years of the international journal of geographical science and systems. Taylor and Francis, London, pp 389–393

    Google Scholar 

  • Kuijpers B, Othman W (2009) Modeling the uncertainty of moving objects on road networks via space-time prisms. Int J Geogr Inf Sci 23(9):1095–1117

    Article  Google Scholar 

  • Kuijpers B, Miller HJ, Neutens T, Othman W (2010) Anchor uncertainty and space-time prisms on road networks. Int J Geogr Inf Sci 24(8):1223–1248

    Article  Google Scholar 

  • Kwan MP, Hong XD (1998) Network-based constraints-oriented choice set formation using GIS. Geogr Syst 5(1):139–162

    Google Scholar 

  • Lenntorp B (1976) Paths in space-time environments: a time-geographic study of movement possibilities of individuals. Lund studies in geography, series B, human geography number 44. The Royal University of Lund, Sweden

  • Leung Y, Yan J (1998) A locational error model for spatial features. Int J Geogr Inf Sci 12(6):607–620

    Article  Google Scholar 

  • Leung Y, Ma J-H, Goodchild MF (2004a) A general framework for error analysis in measurement-based GIS. Part 1: the basic measurement-error model and related concepts. J Geograph Syst 6(4):325–354

    Article  Google Scholar 

  • Leung Y, Ma J-H, Goodchild MF (2004b) A general framework for error analysis in measurement-based GIS. Part 2: the algebra-based probability model for point-in-polygon analysis. J Geograph Syst 6(4):355–379

    Article  Google Scholar 

  • Leung Y, Ma J-H, Goodchild MF (2004c) A general framework for error analysis in measurement-based GIS. Part 3: error analysis in intersections and overlays. J Geograph Syst 6(4):381–402

    Article  Google Scholar 

  • Leung Y, Ma J-H, Goodchild MF (2004d) A general framework for error analysis in measurement-based GIS. Part 4: error analysis in length and area measurements. J Geograph Syst 6(4):403–428

    Article  Google Scholar 

  • Lewis JS, Rachlow JL, Garton EO, Vierling LA (2007) Effects of habitat on GPS collar performance: using data screening to reduce location error. J Appl Ecol 44(3):663–671

    Article  Google Scholar 

  • Miller HJ (1991) Modeling accessibility using space-time prism concepts within geographical information systems. Int J Geogr Inf Syst 5:287–301

    Google Scholar 

  • Miller HJ (1999) Measuring space-time accessibility benefits within transportation networks: basic theory and computational methods. Geogr Anal 31(2):187–212

    Google Scholar 

  • Miller HJ (2005) A measurement theory for time geography. Geogr Anal 37(1):17–45

    Article  Google Scholar 

  • Miller HJ, Bridwell SA (2009) A field-based theory for time geography. Ann Assoc Am Geogr 99(1):49–75

    Article  Google Scholar 

  • Milton R, Steed A (2007) Mapping carbon monoxide using GPS tracked sensors. Environ Monit Assess 124(1–3):1–19

    Article  Google Scholar 

  • Neutens T, Van de Weghe N, Witlox F, De Maeyer P (2008) A three-dimensional network-based space-time prism. J Geograph Syst 10(1):89–107

    Article  Google Scholar 

  • Pfoser D, Jensen CS (1999) Capturing the uncertainty of moving-object representations. In: Güting RH, Papadias D, Lochovsky F (eds) Advances in spatial databases: 6th international symposium (SSD’99). Springer lecture notes in computer science. Berlin, Germany, pp 111–131

  • Rudin W (1976) Principles of mathematical analysis, 3rd edn. McGraw-Hill, New York

    Google Scholar 

  • Ryan PG, Petersen SL, Peters G, Grémillet D (2004) GPS tracking a marine predator: the effects of precision, resolution and sampling rate on foraging tracks of African penguins. Mar Biol 145(2):215–223

    Article  Google Scholar 

  • Taylor JR (1997) An introduction to error analysis: the study of uncertainties in physical measurements, 2nd edn. University Science Books, Sausalito

    Google Scholar 

  • Tomkiewicz SM, Fuller MR, Kie JG, Bates KK (2010) Global positioning system and associated technologies in animal behaviour and ecological research. Philos Trans R Soc B Biol Sci 365(1550):2163–2176

    Article  Google Scholar 

  • Zhang J, Goodchild MF (2002) Uncertainty in geographical information. Taylor and Francis, London

    Book  Google Scholar 

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Correspondence to Harvey J. Miller.

Appendix: spatial sets involved in prisms and prism–prism intersections

Appendix: spatial sets involved in prisms and prism–prism intersections

See (Tables 2, 3, 4, 5, 6).

Table 2 Temporal subintervals and prism geometry: stationary activity time
Table 3 Equations describing temporal boundaries in Table 2
Table 4 Spatial sets involved in prism–prism intersections: no stationary activity time in both prisms
Table 5 Spatial sets involved in prism–prism intersections: stationary activity time in one prism (prism r)
Table 6 Spatial sets involved in prism–prism intersections: stationary activity time in both prisms

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Kobayashi, T., Miller, H.J. & Othman, W. Analytical methods for error propagation in planar space–time prisms. J Geogr Syst 13, 327–354 (2011). https://doi.org/10.1007/s10109-010-0139-z

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