This paper provides a high‐level review of different approaches for spatial interpolation
using areal features. It groups these into those that use ancillary data to constrain or guide …

Data on population at building level is required for various purposes. However, to protect
privacy, government population data is aggregated. Population estimates at finer scales can …

Control data are critical for improving areal interpolation results. Remotely sensed imagery,
road network, and parcels are the three most commonly used ancillary data for areal …

Climate change poses a significant threat to our planet, particularly affecting intricate marine
ecosystems like coral reefs. These ecosystems are crucial for biodiversity and serve as …

To measure population changes in areas where census unit boundaries do not align across
time, a common approach is to interpolate data from one census's units to another's. This …

Comparability among population data enumerated within different time periods may be
complicated by changing enumeration boundaries over time. Areal interpolation methods …

Areal interpolation is routinely used when spatial data are unavailable at desired
geographical units. While many methods are available, few of them were developed …

This paper investigates how ancillary geographic data–in particular, information on land or
assessor parcels–might be used to improve estimates for small area populations and …

This paper presents a granular computing approach to spatial classification and prediction
of land cover classes using rough set variable precision methods. In particular, it presents an …

Areal interpolation is a technique used to transfer attribute information from source zones
with known values to target zones with unknown values. This paper presents and describes …