Modeling Earth Systems and Environment

, Volume 3, Issue 4, pp 1285–1301 | Cite as

Modeling the Spatio-temporal dynamics and evolution of land use and land cover (1984–2015) using remote sensing and GIS in Raya, Northern Ethiopia

  • Eskinder Gidey
  • Oagile Dikinya
  • Reuben Sebego
  • Eagilwe Segosebe
  • Amanuel Zenebe
Original Article


This study models the spatio-temporal dynamics, patterns, and evolution of land use and land cover (LULC) (1984–2015) using remote sensing and GIS supported by in-suit measurements in Raya, Northern Ethiopia. Landsat thematic mapper (TM), and operational land imager (OLI) path 168/169 and row 051/52 were acquired from the United States Geological Survey Landsat archive. All necessary image pre-processing techniques were applied to remove the distortions due to sensors. Eight major LULC types based on a supervised image classification and maximum likelihood decision rule were identified. Post-classification change detection method was also applied to detect the dynamics in LULC. Significant change in forestland, shrub/bush land, built-up area, grassland, cropland, barren land, and floodplain areas were observed over the period 1984–2015. Considerable losses were observed in grasslands (36.9%), water body (8.7%), and floodplain areas (74.4%), while other LULC types increased. This explains why the study area is frequently affected by drought and other related disasters. An overall accuracy of 88.5, 86.5 and 90.5% were observed for the 1984, 1995 and 2015 LULC, respectively. The overall Kappa coefficient of 0.87, 0.85, and 0.90 were also observed for the same periods. Besides, the Pearson pairwise correlation matrix among the 1984–1995, 1995–2015 and 1984–2015 LULC shows positive and strong correlation (r = 0.916, r = 0.908, r = 0.914) at p < 0.005 significance level. Therefore, there is no much difference in identifying LULC types using TM and OLI products. This study is crucial to implement scientific land use policies and strategies in the study area.


LULC dynamics, patterns and evolution LULC gain and loss LULC (TM) and OLI relationships Multi-temporal Landsat imagery Remote sensing GIS Ethiopia 



Lead author is grateful for the PhD scholarship given by the Transdisciplinary Training for Resource Efficiency and Climate Change Adaptation in Africa (TreccAfrica II) project. This research was funded by Mekelle University under grant number CRPO/ICS/PhD/001/09 and the Open Society Foundation-Africa Climate Change Adaptation Initiative (OSF-ACCAI) project of Mekelle University. The authors would also like to thank the National Aeronautics and Space Administration (NASA), United States Geological Survey (USGS) for the provision satellite data.

Compliance with ethical standards

Conflict of interest

The authors declare no conflict of interest.


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Eskinder Gidey
    • 1
    • 2
    • 3
  • Oagile Dikinya
    • 1
  • Reuben Sebego
    • 1
  • Eagilwe Segosebe
    • 1
  • Amanuel Zenebe
    • 2
    • 3
  1. 1.Department of Environmental ScienceUniversity of BotswanaGaboroneBotswana
  2. 2.Department of Land Resource Management and Environmental ProtectionMekelle UniversityMekelleEthiopia
  3. 3.Institute of Climate and SocietyMekelle UniversityMekelleEthiopia

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