Researchers used geospatial data to improve house price indexes in Sydney, Australia. By incorporating a geospatial spline into their model, they found that the resulting indexes were 8-30% higher than those using postcode dummies. This method better accounted for locational characteristics, leading to more accurate price estimates and less bias in the data.