Daytime population refers to the number of people present within a defined geographic area during standard working hours, as opposed to the residential or nighttime population captured in traditional census data. This distinction is critical for accurate spatial analysis, as the actual human presence in a given location fluctuates significantly based on commuting patterns, employment centers, and land use characteristics.

In GIS, daytime population data is derived by integrating multiple geospatial datasets, including census records, employment statistics, mobility data, and point-of-interest layers. Analysts apply spatial modeling techniques to redistribute residential populations across geographic units — such as census tracts, ZIP codes, or custom service areas — accounting for inflows and outflows driven by commuter behavior.

The practical applications of daytime population mapping are extensive. Emergency management agencies use it for evacuation planning and resource allocation. Retailers and real estate developers leverage it for site suitability analysis and market assessment. Urban planners rely on it to optimize infrastructure and public transit networks. By enabling more accurate demand modeling, daytime population analysis strengthens decision-making across industries where understanding true human geography is essential.