Predictive land value modelling in Guatemala City using a geo-statistical approach and Space Syntax

  • J. Andres Morales (Creator)



The datasets were produced during the doctoral research titled "A modelling framework to estimate the effects of future transport interventions on land values". Specifically, the datasets were produced and prepared with the purpose of training a geostatistical model and construct a residential land value map for Guatemala City using a predictive approach. The file "gc_log" contains a set of spatial points representing parcel centroids of the observations that were used to train a regression-kriging model. A spatialized variable selection was implemented in order to retain only important variables. The "grid_prediction.csv" contains a set of spatial points representing the centroids of an hexagonal tessellation containing values for all the required predictors of land value. The "research_code.R" file contains the scripts developed to implement the spatial variable selection, train the regression-kriging model and construct the land value map.
Date made available5 Jun 2020
PublisherDATA Archiving and Networked Services (DANS)
Temporal coverage2008 - 2014
Date of data production2008 - 2014
Geographical coverageGuatemala City
Geospatial point14.627507, -90.504244Show on map

Cite this