Advertisement

Spatiotemporal detection of land use/land cover change in the large basin using integrated approaches of remote sensing and GIS in the Upper Awash basin, Ethiopia

  • Alemayehu A. ShawulEmail author
  • Sumedha Chakma
Original Article
  • 106 Downloads

Abstract

Assessment of the changing environmental conditions is essential for planning the wise use of natural resources. The main objective of this paper is to analyze the historical and future modeled LULC changes using multi-temporal Landsat images in the Upper Awash basin, Ethiopia. The supervised image classification method was used to determine the historical LULC changes based on Landsat 1 MSS 1972, Landsat 5 TM 1984, Landsat 7 ETM + 2000, and Landsat 8 OLI TIRS 2014. The future LULC change was predicted using the machine-learning approaches of Land Change Modeler (LCM). The LULC change detection analysis exhibited significant increment in the areal extent of the cropland and urban areas, and decreasing trends in the pasture, forests and shrubland coverage. Mainly, the LULC change matrices indicated that larger conversion rate was observed from shrubland to cropland area. The urban area found to increase by 606.2% from the year 1972 to 2014 and cropland has also increased by 47.3%. Whereas, a decreasing trend was obtained in the forest by − 25.1%, pasture − 87.4%, shrubland − 28.8% and water − 21.0% in the same period. The modeled future LULC change scenarios of the year 2025 and 2035 have exhibited significant expansion of cropland and urban areas at the expense of forest, pasture and shrubland areas. The study has revealed the extent and the rate of LULC change at larger basin and subbasin level which can be useful for knowledge-based future land management practice in the Upper Awash basin.

Keywords

Land cover change Agricultural expansion Urban sprawl Land change modeler Classification accuracy Upper Awash basin 

Notes

Acknowledgements

The authors are thankful to the anonymous reviewers for their genuine comments and suggestions which has improved this paper. The authors are grateful to the Ethiopian Mapping Agency for providing topographic maps, and the Ministry of Agriculture of Ethiopia for providing crop-related data. The authors are also thankful to the United States Geological Survey (USGS) for providing all Landsat data series and DEM data free of cost which has been used in this study.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

References

  1. Alem S, Duraisamy J, Legesse E, Seboka Y, Mitiku E (2010) Wood charcoal supply to Addis Ababa city and its effect on the environment. Energy Environ 21:602–609CrossRefGoogle Scholar
  2. Amsalu A, Stroosnijder L, de Graaff J (2007) Long-term dynamics in land resource use and the driving forces in the Beressa watershed, highlands of Ethiopia. J Environ Manage 83:448–459CrossRefGoogle Scholar
  3. Ashenafi TT (2009) Impact assessment of land use / land cover changes on Shaya river flow using SWAT. MSc Thesis, Arba Minch University. 130pGoogle Scholar
  4. Asres RS, Tilahun SA, Ayele GT, Melesse AM (2016) Analyses of land use/land cover change dynamics in the upland watersheds of Upper Blue Nile Basin. In: Landscape dynamics, soils and hydrological processes in varied climates. Springer, Berlin, pp 73–91CrossRefGoogle Scholar
  5. Ayele GT, Demessie SS, Mengistu KT, Tilahun SA, Melesse AM (2016) Multi-temporal land use/land cover change detection for the Batena Watershed, Rift Valley Lakes Basin, Ethiopia. In: Melesse AM, Abtew W (eds) Landscape dynamics, soils and hydrological processes in varied climates. Springer Geogr.  https://doi.org/10.1007/978-3-319-18787-7_4
  6. Bewket W (2002) Land cover dynamics since the 1950s in Chemoga watershed, Blue Nile basin, Ethiopia. Mt Res Dev 22(3):263–269CrossRefGoogle Scholar
  7. Bewket W (2003) Towards integrated watershed management in highland Ethiopia: the Chemoga watershed case study. Ph.D. thesis, Wageningen University and Research Centre, ISBN 90-5808-870-7Google Scholar
  8. Bishop YMM, Feinberg SE, Holland PW (1975) Discrete multivariate analysis—theory and practice. MIT Press, Cambridge, 575pGoogle Scholar
  9. Campbell DJ, Lusch DP, Smucker T, Wangui EE (2003) Root causes of land use change in the Loitokitok Area, Kajiado District, Kenya. By land use change impacts and dynamics (LUCID) Working Paper Series No. 19Google Scholar
  10. Congalton RG (1991) A review of assessing the accuracy of classification of remotely sensed data. Remote Sens Environ 37:35–46CrossRefGoogle Scholar
  11. CSA (2008) Summary and statistical report of the 2007 population and housing census of Ethiopia. December, 2008, Central Statistical Agency (CSA), Addis Ababa, Ethiopia. 113Google Scholar
  12. CSA (2013) Population projection of Ethiopia for all regions at Wereda level from 2014 to 2017. Central Statistical Agency of Ethiopia, Addis Ababa, EthiopiaGoogle Scholar
  13. Dessie G, Kleman J (2007) Pattern and magnitude of deforestation in the South Central Rift Valley Region of Ethiopia. Mt Res Dev 27(2):162–168CrossRefGoogle Scholar
  14. Dewan AM, Yamaguchi Y (2009) Using remote sensing and GIS to detect and monitor land use and land cover change in Dhaka Metropolitan of Bangladesh during 1960–2005. Environ Monit Assess 150:237–249.  https://doi.org/10.1007/s10661-008-0226-5 CrossRefGoogle Scholar
  15. Dilnesaw A (2006) Modeling of hydrology and soil erosion of Upper Awash River Basin. Ph.D. Dissertation, University of Bonn, Germany. 236pGoogle Scholar
  16. Eastman JR (1999) Guide to GIS and image processing (Volume 1). Clark Labs. Clark University, USAGoogle Scholar
  17. Eastman JR (2016) IDRISI Terrset Manual. Clark Labs. Clark University, WorcesterGoogle Scholar
  18. El-Swaify SA, Hurni H (1996) Trans-boundary effects of soil erosion and conservation in the Nile basin. Land Husb 1:6–21Google Scholar
  19. ERDAS (2013) Module for ERDAS IMAGINE 2014, User’s Guide Version 4.x. ERDAS. Inc., AtlantaGoogle Scholar
  20. Gebrelibanos T, Assen M (2015) Land use/land cover dynamics and their driving forces in the Hirmi watershed and its adjacent agroecosystem, highlands of Northern Ethiopia. J Land Use Sci 10(1):81–94.  https://doi.org/10.1080/1747423X.2013.845614 CrossRefGoogle Scholar
  21. Geist HJ, Lambin EF (2001) What Drives Tropical Deforestation. Glob Environ Change 1(1):136.  https://doi.org/10.1016/0959-3780(90)90005-T CrossRefGoogle Scholar
  22. Gete Z, Hurni H (2001) Implications of land use and land cover dynamics for mountain resource degradation in the Northwestern Ethiopian highlands. Mt Res Dev 21(2):184–191CrossRefGoogle Scholar
  23. Hord RM (1982) Digital image processing of remotely sensed data. Academic Press, New York, 256pGoogle Scholar
  24. Hurni H (1993) World soil erosion and conservation: land degradation, famine, and land resource scenarios in EthiopiaGoogle Scholar
  25. Hurni H, Tato K, Zeleke G (2005) The implications of changes in population, land use, and land management for surface runoff in the upper Nile basin area of Ethiopia. Mt Res Dev 25(2):147–154CrossRefGoogle Scholar
  26. Jadin I, Vanacker V, Hoang HTT (2013) Drivers of forest cover dynamics in smallholder farming systems: the case of northwestern Vietnam. Ambio 42:344–356CrossRefGoogle Scholar
  27. Kassa MT (2009) Watershed hydrological responses to changes in land use and land cover, and management practices at hare watershed, Ethiopia. Ph.D. Thesis, Universität Siegen. 244pGoogle Scholar
  28. Kindu M, Schneider T, Teketay D, Knoke T (2015) Drivers of land use/land cover changes in Munessa–Shashemene landscape of the south-central highlands of Ethiopia. Environ Monit Assess 187(7):452CrossRefGoogle Scholar
  29. Kinfe H (1999) Impact of climate change on the water resources of Awash River Basin, Ethiopia. Clim Res 12(2/3):91–96Google Scholar
  30. Lambin EF, Baulies X, Bockstael N, Fischer G, Krug T, Leemans R, Moran EF, Rindfuss RR, Sato Y, Skole D, Turner BL, Vogel C (1999) Land-Use and Land-Cover Change (LUCC)—implementation strategy. A core project of the International Geosphere-Biosphere Programme and the International Human Dimensions Programme on Global Environmental Change. Stockholm and IHDP Secretariat: Bonn, IGBP SecretariatGoogle Scholar
  31. Lo CP, Yang X (2002) Drivers of land-use/land-cover changes and dynamic modeling for the Atlanta, Georgia metropolitan area. Photogramm Eng Remote Sens 68(10):1073–1082Google Scholar
  32. Mather PM (2004) Computer processing of remotely-sensed images: an introduction, 3rd edn. Wiley, ChichesterGoogle Scholar
  33. Mekuria DA (2005) Forest conversion, soil degradation, farmers’ perception nexus: implications for sustainable land use in the Southwest of Ethiopia, vol 26. Cuvillier VerlagGoogle Scholar
  34. Meshesha TW, Tripathi SK, Khare D (2016) Analyses of land use and land cover change dynamics using GIS and remote sensing during 1984 and 2015 in the Beressa Watershed Northern Central Highland of Ethiopia. Model Earth Syst Environ 2(4):168CrossRefGoogle Scholar
  35. Meyer WB, Turner BL (1992) Human population growth and global land-use/cover change. Annu Rev Ecol Syst 23(1):39–61CrossRefGoogle Scholar
  36. Mundia CN, Aniya M (2005) Analysis of land use/cover changes and urban expansion of Nairobi city using remote sensing and GIS. Int J Remote Sens 26(13):2831–2849.  https://doi.org/10.1080/01431160500117865 CrossRefGoogle Scholar
  37. Mustard J, DeFries R, Fisher T, Moran EF (2004) Land use and land cover change pathways and impacts. In: Cochrane MA (ed) Land change science: observing, monitoring, and understanding trajectories of change on the earth’s surface. Springer, DordrechtGoogle Scholar
  38. Niehoff D, Fritsch U, Bronstert A (2002) Land-use impacts on storm-runoff generation: scenarios of land-use change and simulation of hydrological response in a meso-scale catchment in SW-Germany. J Hydrol 267(1–2):80–93CrossRefGoogle Scholar
  39. Pandey BK, Khare D (2017) Analysing and modeling of a large river basin dynamics applying integrated cellular automata and Markov model. Environ Earth Sci 76(22):779CrossRefGoogle Scholar
  40. Paul HB (2000) Layers of time. In: Layers of time. Palgrave Macmillan, New York, pp 1–21.  https://doi.org/10.1007/978-1-137-11786-1_1 CrossRefGoogle Scholar
  41. Qian J, Zhou Q, Hou Q (2007) Comparison of pixel-based and object-oriented classification methods for extracting built-up areas in the arid zone. In: ISPRS Workshop on Updating Geo-Spatial Databases with Imagery and the 5th ISPRS Workshop on DMGISs, pp 163–171Google Scholar
  42. Richards JA, Xiuping J (2006) Remote sensing digital image analysis: an introduction. New York.  https://doi.org/10.1007/978-3-642-30062-2
  43. Smith AM (2008) How to convert ASTER radiance values to reflectance: an online guide. University of Idaho, USAGoogle Scholar
  44. Solomon A (1994) Land use dynamics, soil conservation and potential for use in Metu area, Illubabor region, Ethiopia. African Studies Series A, 13Google Scholar
  45. Story M, Congalton R (1986) Accuracy assessment: a user’s perspective. Photogramm Eng Remote Sens 52(3):397–399Google Scholar
  46. Sun Y, Zhao S, Qu W (2015) Quantifying spatiotemporal patterns of urban expansion in three capital cities in Northeast China over the past three decades using satellite data sets. Environ Earth Sci 73:7221–7235.  https://doi.org/10.1007/s12665-014-3901-6 CrossRefGoogle Scholar
  47. Taddese G, Sonder K, Peden D (2012) The Water of the Awash River basin a future challenge to Ethiopia. International Livestock Research Institute (ILRI), a working paper. http://www.iwmi.cgiar.org/assessment/files/pdf/publications/WorkingPapers/WaterofAwasBasin.pdf. Accessed 18 May 2015
  48. UN DESA (2014) World urbanization prospects, the 2011 revision. Population Division, Department of Economic and Social Affairs, United Nations SecretariatGoogle Scholar
  49. UNDP (1999) Afar region—awash river floods. Rapid Assessment Mission for Ethiopia. Emergency Unit, 7–10 September 1999Google Scholar
  50. Weng Q (2002) Land use change analysis in the Zhujiang Delta of China using satellite remote sensing, GIS and stochastic modelling. J Environ Manag 64(3):273–284CrossRefGoogle Scholar
  51. Wilson CO, Weng Q (2011) Simulating the impacts of future land use and climate changes on surface water quality in the Des Plaines River watershed, Chicago Metropolitan Statistical Area, Illinois. Sci Total Environ 409(20):4387–4405CrossRefGoogle Scholar
  52. Wilson EH, Hurd JD, Civco DL, Prisloe S, Arnold C (2003) Development of a geospatial model to quantify, describe and map urban growth. Remote Sens Environ 86(3):275–285.  https://doi.org/10.1016/S0034-4257 (03)00074 – 9CrossRefGoogle Scholar
  53. Yuan F, Sawaya KE, Loeffelholz BC, Bauer ME (2005) Land cover classification and change analysis of the Twin Cities (Minnesota) metropolitan area by multi-temporal Landsat remote sensing. Remote Sens Environ 98(2–3):317–328.  https://doi.org/10.1016/j.rse.2005.08.006 CrossRefGoogle Scholar
  54. Zewdie W, Csaplovies E (2015) Remote Sensing based multitemporal land cover classification and change detection in northwestern Ethiopia. Eur J Remote Sens 48(1):121–139.  https://doi.org/10.5721/EuJRS20154808 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Civil Engineering DepartmentIndian Institute of Technology DelhiNew DelhiIndia

Personalised recommendations