DOI: 10.25349/d9sp5g
title: Historical and Forecast Land use Data for Ibadan, Nigeria 1984 - 2040

description: The SLEUTH model was implemented for Ibadan Nigeria, a city in West Africa
 with a mostly unregulated growth trajectory. The input physiographic and
 historical data for SLEUTH was compiled at spatial resolutions ranging
 between 15m – 90m. The temporal resolution of inputs was based on 35 years
 of historical data spanning the years 1984 to 2020. The urban (built-up
 commercial, residential, and industrial) land use increased almost
 four-fold from 3.0% of the total area in 1984 to 11.2% by 2020. The Forest
 extent was halved from 73.1% to 36.7% while agriculture and savanna
 extents have expanded over time.  Predictors of growth and the
 effect of tiling and spatiotemporal resolution on calibration and future
 growth forecasts with SLEUTH were determined. Transport and suburban edge
 spread were found to be the best predictors of growth. Model calibration
 metrics were found to generally improve with finer spatial resolution.
 Uncertainty reduced as the time interval between input land use data
 shortened but other accuracy metrics tended to improve as the time
 interval increased. An intermediate time interval and pixel resolution
 provided the best compromise of uncertainty and other accuracy metrics.
 Tiling the data allows a good fit within individual tiles but a reduction
 in pattern and trend recognition across land-use types. Year 2040
 projections when optimized to allow the highest confidence and lowest
 uncertainty, suggest a continuation of rapid growth in suburban clusters
 and along transport routes. This collection of citywide data and growth
 forecasts for Ibadan can aid other researchers and planners interested in
 inputs for related projects and models in transport, water resources,
 planning, policy evaluation, and environmental management.
description: The land use and urban data were derived from Landsat satellite
 imagery. The overall accuracy (OA) of the classification for specific
 dates was 98.5% (1984), 80.7% (2000), 85.4% (2006), 87.5% (2013) and 94.5%
 (2020). Vector datasets for the period of study were derived from
 OpenStreetMap datasets and comparisons with historical satellite imagery. 
 All data have been reprojected to UTM Zone 31, WGS 1984 to allow for
 uniformity and measurements in metric units. Calibration was initially
 carried out using data spanning the entire study period. Subsequently,
 data up to 2013 was used to predict 2020 actual land use. Calibration
 validation was then carried out using pixel-based accuracy metrics.
 Finally, optimum calibration values were used for forecasting growth up to
 year 2040 at 30m resolution.
description: The files in this folder include :<br> 1. An unzipped data
 folder named "Ibadan" with 6 subfolders described
 below:<br>     A. Ibadan_Physical_and_Transport_shapefiles: This
 folder contains input vector datasets including historical transport
 layers as well as areas of interest (AOI), rivers, waterbodies,
 Metropolitan Local Government Area (LGAs), Calibration and accuracy
 metrics for tiled data  (Ibadan_15m_metro and Ibadan_30m_metro).<br>
     B. Ibadan_Physical_and_Landuse_Rasters: The folder includes all
 landuse and urban raster data at 15m resolution in GeoTIFF format for 1984
 -2020. It also includes Exclusion, Hillshade, slope and DEM GeoTIFF
 rasters at 15m resolution.<br>     C.
 Ibadan_SLEUTH_GA_Inputs_and_Log_Files: This folder contains all input
 files in GIF format at 15 – 90m resolution,  scenario files for running
 SLEUTH as well as calibration log files<br>     D.
 Ibadan_SLEUTH_Ouput_Calibration_Validation_Image_and_Statistic_Files: The
 folder contains GIF image files from calibration validation at 15, 30, 60
 and 90m resolutions as well as calibration validation
 statistics. <br>     E. Ibadan_SLEUTH _30m_Forecasts_2020_to_2040:
 This folder contains tiled and untiled 2040 forecast results at 30m
 resolution.<br>     F. Figures_From_Paper: This folder contains the
 figures found in the companion paper 2.  A zipped file
 containing bash scripts for running preprocessing steps
 3.  A zipped folder containing custom c coded for tiling SLEUTH
 input datasets 4. A README file with information about
 the provenance, overall structure, organization, and relationships between
 files <br>    as well as links to download SLEUTH and other required
 stand alone software.<br>