Scale selecting of building information statistical grids with spatial autocorrelation

Jiangping Chen, Lin Ding, Wen Zhong Shi

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

The difference in statistical scales will bring different statistical results, so it is important and necessary to select statistical grids for the geographical conditions information statistics. This paper proposes a method of selecting statistical scale of geographical information with spatial autocorrelation being taken into account. By using geographic conditions census data and taking building information statistics as an example, this study gets building statistical information at different scales from 100m to 10000m, and meanwhile analyzes change trends of spatial autocorrelation of building information at different scales to make statistical scale selection. The results show that for building information statistics, 1000m is the turning point of statistical scales, and can be used as a suitable statistical scale in city region.
Original languageEnglish
Title of host publicationICSDM 2015 - Proceedings 2015 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services
PublisherIEEE
Pages77-81
Number of pages5
ISBN (Electronic)9781479977482
DOIs
Publication statusPublished - 13 Oct 2015
Event2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services, ICSDM 2015 - Fuzhou, China
Duration: 8 Jul 201510 Jul 2015

Conference

Conference2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services, ICSDM 2015
CountryChina
CityFuzhou
Period8/07/1510/07/15

Keywords

  • Geographic conditions
  • Scale selecting
  • Spatial autocorrelation
  • Statistical grids

ASJC Scopus subject areas

  • Software
  • Computer Science Applications

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