Zonal boundaries on choropleth maps demarcate by administrative units, while zonal boundaries on dasymetric maps are based on changes in the statistical zones derived from ancillary information.Dasymetric maps are closely related to choropleth maps, however, they are difference in several ways: In dasymetric mapping, a source layer or population data is converted into a surface and an ancillary data layer is added to the surface with a weighting scheme applied to cells coinciding within the zonal boundaries of ancillary data. Dasymetric mapping depicts quantitative distribution of population using boundaries that divide an area into zones of relative homogeneity. Meanwhile, dasymetric mapping is a method for mapping the distribution of population relative to land use or other ancillary data, such as building footprints, locations of roads, slope and elevation etc. Choropleth maps aggregate population data with administrative units (census tracts or block groups) whose boundaries do not always reflect the natural distribution of human populations. Population distributions are commonly displayed using choropleth maps of decennial census data. Familiarize the reader with the available global population distribution maps.Understand the concept of population distribution models.An example of local level population data is also described to demonstrate the application for small island countries of the Caribbean. In the following sections, the concept of population distribution model is explained and the current global gridded population datasets including Gridded Population of the World (GPW) database, Global Rural Urban Mapping Project (GRUMP), Land Scan, WorldPop, and HRSL population data are introduced. Since the 1990s, a spatially gridded population distribution map has also been developed by incorporating land use information and other ancillary data relevant to the distribution of population.
Population distribution maps are mainly based on population count from census data which used administrative units as basic map units. Furthermore, census data are often only available at an aggregated level. However, collection of census data is a costly affair and resource intensive and it is normally completed once in a decade in most countries. Census data is the basis for governments for policy development, management and evaluation of development programs.
They are also used as benchmark data for studying population changes (trend/direction), and are a key input for making population projections including gender, poverty, labor force, employment etc. It is the most reliable information for describing households, neighborhoods, cities, and countries. Census is the only consistent source for demographic data with a wide geographic scope. Rapid urbanization and population growth over the past decade has brought population distribution to forefront from a risk perspective. High resolution and spatially accurate data on population distribution are very important for disaster and risk management. Use Case 7.5 Using census data for characterizing elements-at-risk at local scale.Keywords: Population distribution, Dasymetric mapping, Gridded population data, GPW, GRUMP, LandScan, WorldPop, High Resolution Settlement Layer (HRSL) Population DataĪuthors: Manzul Kumar Hazarika, Syams Nashrrullah, Mujeeb Alam, Cees van Westen, Adityo Dwijananto, It also provides an example from Grenada on the generation of population distribution at building level, by combining building footprints and census data at enumeration district level. This chapter discusses the various sources for population distribution maps.