The purpose of this data collection is to provide spatial data on urban development patterns, with a particular emphasis on informal settlements, defined here as residential areas that have developed incrementally without a formal plan and consent of the municipal authority, and lack of adequate infrastructure (roads, water and sewer network). The data may be of use in decision support systems to address issues of vulnerability, risk to natural hazards, poverty alleviation, and urban planning.
The first data set is a representation of urban areas in the Continental U.S. in the year 2015 derived from Neural Network machine learning of satellite data. The input data for these models were two types of satellite imagery: Visible Infrared Imaging Radiometer Suite (VIIRS) Nighttime Light (NTL) data from the Day/Night Band (DNB), and Moderate Resolution Imaging Spectroradiometer (MODIS) corrected daytime Normalized Difference Vegetation Index (NDVI).
The second data set in this collection is based on Dar es Salaam, Tanzania, which is considered one of the most dynamic urban centers in Africa. The Dar es Salaam Land Use and Informal Settlement Data Set contains urban land use and consolidation of informal settlements for the years 1982, 1992, 1998, and 2002.
The third is a global data set containing location and size of urban populations over the last 6,000 years. The Historical Urban Population, 3700 BC - AD 2000 data set originally developed by the Yale School of Forestry & Environmental Studies can be used to improve the understanding of contemporary and historical urbanization trends.