The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIII-B4-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B4-2021, 135–140, 2021
https://doi.org/10.5194/isprs-archives-XLIII-B4-2021-135-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B4-2021, 135–140, 2021
https://doi.org/10.5194/isprs-archives-XLIII-B4-2021-135-2021

  30 Jun 2021

30 Jun 2021

EXPLORATORY SPATIAL ANALYSIS OF HOUSING PRICES OBTAINED FROM WEB SCRAPING TECHNIQUE

T. G. D. Souza1, F. D. R. Fonseca2, V. D. O. Fernandes1, and J. C. Pedrassoli1 T. G. D. Souza et al.
  • 1Post-Graduate Program in Civil Engineering (PPEC), Federal University of Bahia, Salvador-Bahia, Brazil
  • 2Polytechnic School of Engineering, Federal University of Bahia, Salvador-Bahia, Brazil

Keywords: Land price, Web Scraping, Real Estate Market, GIS, Spatial Autocorrelation, Moran’s Index

Abstract. The exploratory spatial analysis allows to describe patterns of spatial distribution, to identify clusters and outliers through specific techniques of spatial association and data model. The objective of the study is to verify the spatial autocorrelation between the mean prices of the housing obtained from web scraping technique in online platforms in the city of Salvador, on the coast of northeast Brazil. For this purpose, the Global Moran’s Index (which provides a general measure of association) and the Local Index of Spatial Association (LISA) were calculated. The results of Global Moran’s Index indicate positive autocorrelation between the mean prices of housing prices in the 163 districts of the municipally that are statistically significant, such as identification of clusters through LISA. Thus, the analysis allows to conclude the existence of a heterogeneous pattern in the distribution of these mean prices in the urban space of Salvador.