License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.GIScience.2021.I.2
URN: urn:nbn:de:0030-drops-130375
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2020/13037/
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Bucher, Dominik ; Martin, Henry ; Jonietz, David ; Raubal, Martin ; Westerholt, René

Estimation of Moran’s I in the Context of Uncertain Mobile Sensor Measurements

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LIPIcs-GIScience-2021-I-2.pdf (2 MB)

Abstract

Measures of spatial autocorrelation like Moran’s I do not take into account information about the reliability of observations. In a context of mobile sensors, however, this is an important aspect to consider. Mobile sensors record data asynchronously and capture different contexts, which leads to considerable heterogeneity. In this paper we propose two different ways to integrate the reliability of observations with Moran’s I. These proposals are tested in the light of two case studies, one based on real temperatures and movement data and the other using synthetic data. The results show that the way reliability information is incorporated into the Moran’s I estimates has a strong impact on how the measure responds to volatile available information. It is shown that absolute reliability information is much less powerful in addressing the problem of differing contexts than relative concepts that give more weight to more reliable observations, regardless of the general degree of uncertainty. The results presented are seen as an important stimulus for the discourse on spatial autocorrelation measures in the light of uncertainties.

BibTeX - Entry

@InProceedings{bucher_et_al:LIPIcs:2020:13037,
  author =	{Dominik Bucher and Henry Martin and David Jonietz and Martin Raubal and Ren{\'e} Westerholt},
  title =	{{Estimation of Moran’s I in the Context of Uncertain Mobile Sensor Measurements}},
  booktitle =	{11th International Conference on Geographic Information Science (GIScience 2021) - Part I},
  pages =	{2:1--2:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-166-5},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{177},
  editor =	{Krzysztof Janowicz and Judith A. Verstegen},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2020/13037},
  URN =		{urn:nbn:de:0030-drops-130375},
  doi =		{10.4230/LIPIcs.GIScience.2021.I.2},
  annote =	{Keywords: mobile sensors, Moran’s I, uncertainty, probabilistic forecasting}
}

Keywords: mobile sensors, Moran’s I, uncertainty, probabilistic forecasting
Collection: 11th International Conference on Geographic Information Science (GIScience 2021) - Part I
Issue Date: 2020
Date of publication: 25.09.2020

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