Projection of Urban/Settlement Growth for 9 Coastal Cities to 2050 with SLEUTH under SSP Scenarios

The provided datasets capture the projected urban growth of nine coastal cities worldwide up to 2050, based on an urban growth modeling framework. These cities include Abidjan (ABI), Ivory Coast; Lagos (LAG), Nigeria; Dar es Salaam (DAR), Tanzania; Ho Chi Minh City (HCM), Vietnam; Khulna (KHL), Bangladesh; Surabaya (SBY), Indonesia; Surat (STV), India; Barranquilla (BAQ), Colombia; and Guayaquil (GYE), Ecuador. Each study area extends beyond administrative city limits to include satellite cities, towns, villages, and rural lands, forming larger settlement agglomerations. A detailed table in the repository outlines the specific administrative units considered for each city. Urban growth projections were generated using the SLEUTH model (DOI: 10.1068/b240247), incorporating key input layers such as slope, hillshade, and exclusion zones. Historical urban extent data from the World Settlement Footprint (WSF) (DOI: 10.1553/giscience2021_01_s33) supported model calibration. The projections were guided by urban population share scenarios from the Shared Socioeconomic Pathways (SSPs), simulating future expansion under SSP2 (moderate growth) and SSP1/SSP5 (rapid growth). The integration of SSPs involved adjusting SLEUTH’s spread and breed coefficients to reflect the underlying socioeconomic narratives. To enhance model accuracy, we applied a zonation approach based on Kernel Density Estimation (KDE), dividing each study area into zones with distinct urban and rural characteristics. This method better aligns projections with actual settlement structures and urbanization trends, ensuring a more refined representation of future urban expansion. File descriptions: ZIP file (Urban_Growth_Modelling_2050_Coastal_Cities.zip) contaioning: Study_areas.pdf: Outlines the administrative units covered represented with a rectangular study area. 9 folders with respective urban agglomeration names containing 3 files each (XXX = city abbreviation, see abstract or Study_areas.pdf):1) Seed_WSF2015_XXX.tif : Seed file derived from the WSF2015 (= base/start year of modelling). Source DLR Geoservice (geoservice.dlr.de)2) SSP1_SSP5_prediction_XXX.tif (urban extent modelled under SSP1/SSP5 scenario for the year 2050)3) SSP2_prediction_XXX.tif (urban extent modelled under SSP2 scenario for the year 2050)The *.tif files (GeoTiff) are binary raster layers with 0 = non urban and 1 =urban/settlement area. The GCS is EPSG:4326 - WGS 84.