Data on spatiotemporal urban sprawl of Dire Dawa City, Eastern Ethiopia

The data presented in this paper shows the spatiotemporal expansion of Dire Dawa City (eastern Ethiopia) and the ensuing land use land cover changes in its peri-urban areas between 1985 and 2015. The data were generated from satellite images of Thematic Mapper (TM), Enhanced Thematic Mapper-Plus (ETM+) and OLI (Operational Land Image) with path/raw value of 166/053 by using Arc GIS 10.1 software. The precision of the images was verified by geolocation data collected from ground control points by using Geographic Positioning System (GPS) receiver. Four LULC classes (built up area, vegetation, barren land and farmland) with their respective spatiotemporal dimensions were clearly identified in the analysis. Built up area had shown an overall annual increment of 15.8% (82 ha per year) from 517 ha in 1985 to 2976 ha in 2015. Expansion took place in all directions but it was more pronounced along the main road towards other nearby towns, recently established business/service areas and the Industrial Park. Barren land, farmland and vegetation areas showed speedy decline over the years.


a b s t r a c t
The data presented in this paper shows the spatiotemporal expansion of Dire Dawa City (eastern Ethiopia) and the ensuing land use land cover changes in its peri-urban areas between 1985 and 2015. The data were generated from satellite images of Thematic Mapper (TM), Enhanced Thematic Mapper-Plus (ETMþ ) and OLI (Operational Land Image) with path/raw value of 166/053 by using Arc GIS 10.1 software. The precision of the images was verified by geolocation data collected from ground control points by using Geographic Positioning System (GPS) receiver. Four LULC classes (built up area, vegetation, barren land and farmland) with their respective spatiotemporal dimensions were clearly identified in the analysis. Built up area had shown an overall annual increment of 15.8% (82 ha per year) from 517 ha in 1985 to 2976 ha in 2015. Expansion took place in all directions but it was more pronounced along the main road towards other nearby towns, recently established business/service areas and the Industrial Park. Barren

OLI, and Google Earth
Data accessibility The data is with this article

Value of the data
The data is helpful to Dire Dawa City administrators to speculate the extent of the spatiotemporal expansion of Dire Dawa and its potential impacts on the surround areas.
The data provides information on the status of urban expansion towards rural peri-urban areas around Dire Dawa City.
The data is vital to model urban expansion towards rural peri-urban areas surrounding Dire Dawa City to mitigate its adverse impacts on the livelihoods of the people inhabiting the area and the ecosystem.
The data is useful to researchers, urban planners and experts working in the field.

Data
The data in this article provides information on the spatiotemporal expansion of Dire Dawa City (eastern Ethiopia) and the ensuing LULC changes in its peri-urban areas between 1985 and 2015.      this data article. The images were geo-referenced with World Geodetic System (WGS) 1984 datum and Universal Transverse Mercator (UTM) projection system zone 37 North. The analysis comprised of layer stacking, radiometric correction, image enhancement, haze reduction, band combination and false color combination. Google earth maps of each year were used for GPS-based ground verification with a minimum of 20 spatially distributed ground control points in the area. Reconnaissance survey and researchers' experience of the study area were also vital. With this pre-assessment, four LULC classification schemes such as built up area, farmland, vegetation and barren land were identified considering the standard classes defined by the US Geological Survey as well as the study detail and objectives [1,2]. Supervised classification technique was used for all images to identify the class features of the image. Moreover, post classification technique was applied to enhance the brightness of the classified images. Classification accuracy assessment was made at post classification stage to evaluate how well the classified images represented the real world. At the end, urban expansion change detection map of each year was produced. The extent and direction of the city's expansion were analyzed by calculating the corresponding areas with Arc GIS 10.1 software and related statistical formula [1].