Advertisement

Modeling Earth Systems and Environment

, Volume 4, Issue 2, pp 517–526 | Cite as

Detection and impact of land encroachment in El-Beheira governorate, Egypt

  • Ahmed A. Afifi
  • Khaled M. Darwish
Original Article
  • 68 Downloads

Abstract

Mainly, the high fertile land of Egypt is limited and threatened by the problem of land dwindling. In this context, three temporal satellite imagers were utilized to generalize the land cover changes. This is to reliable monitoring the urban sprawl changes and its action on farming area in El-Beheira governorate, Egypt, after the revolution of January 25th. The two algorithms of supervised maximum likelihood and post-classification change detection were implemented through cross tabulation for monitoring the urban sprawl to achieve change detection. Implementing ancillary data, digital interpretation and the area expert knowledge further refined the classification results. GIS utilities assist to argue out the risk of urban expansion at the expense of highly productive units. The output results showed that the rapid imbalance changes occurred among three land cover classes (urban, desert and cultivated land). During the (1985–2013) period, the urban land cover area was increased from 137.9 to 579.4 km2 (23.8%). Nevertheless, in just 3 years (2010–2013) urban sprawl expanded from 381.9 to 579.4 km2 (65.9%) as a total loss of cultivated land, during the insecure situation of the 25th revolution. Exclusively, these changes strengthened the land fragmentation processes over the green land as a result of urban encroachment. Information on urban growth, land use/cover change are essential for local government and urban planners for the amelioration of future sustainable development.

Keywords

Encroachment on land Change detection Land cover Remote sensing GIS 

Notes

Acknowledgements

The authors would gratefully acknowledge Mr. Ihab Y. Ahmed, researcher in the National Authority for Remote Sensing and Space Sciences (NARSS), Cairo, Egypt, for his valuable assistance in image analysis.

References

  1. Abd El-Kawy OR, Rød JK, Ismail HA, Suliman AS (2011) Land use and land cover change detection in the western Nile delta of Egypt using remote sensing data. Appl Geogr 31:483–494CrossRefGoogle Scholar
  2. AbdelRahman MA, Shalaby A, Aboelsoud MH, Moghanm FS (2017) GIS spatial model based for determining actual land degradation status in Kafr El-Sheikh governorate, North Nile Delta. Model Earth Syst Environ.  https://doi.org/10.1007/s40808-017-0403-z Google Scholar
  3. Almutairi A, Warner AT (2010) Change detection accuracy and image properties: a study using simulated data. Remote Sens 2(6):1508–1529.  https://doi.org/10.3390/rs2061508 CrossRefGoogle Scholar
  4. ASRT (1982) Soil map of Egypt, final report. Academy of Scientific Research and Technology (ASRT), CairoGoogle Scholar
  5. Bajocco S, Angelis A, Perini L, Ferrara A, Salvati L (2012) The impact of land use/land cover changes on land degradation dynamics. A Mediterranean case study. Environ Manag 49:980–989.  https://doi.org/10.1007/s00267-012-9831-8 CrossRefGoogle Scholar
  6. Bayramov E, Buchroithner M, Bayramov R (2016) Quantitative assessment of 2014–2015 land-cover changes in Azerbaijan using object-based classification of LANDSAT-8-time series. Model Earth Syst Environ 2:35.  https://doi.org/10.1007/s40808-016-0088-8 CrossRefGoogle Scholar
  7. Chen SQ, Liu JY, Zhuang DF, Xiao XM (2003) Characterization of land cover types in the Xilin river basin using multi-temporal Landsat images. J Geogr Sci 13(2):130–138Google Scholar
  8. Deng J, Wang K, Li J, Feng X (2005) Integration of SPOT-5 and ETM + images to detect land cover change in urban environment. In: IEEE international geoscience and remote sensing symposium, Seoul, 25–29 JulyGoogle Scholar
  9. Deng JS, Wang K, Deng YH (2008) PCA-based land-use change detection and analysis using multi-temporal and multi-sensor satellite data. Int J Remote Sens 29(16):4823–4838CrossRefGoogle Scholar
  10. El Bastawesy M, Ramadan AR, Faid A (2013a) Assessment of waterlogging in agricultural megaprojects in the closed drainage basins of the western desert of Egypt. Hydrol Earth Syst Sci 17:1493–1501.  https://doi.org/10.5194/hess-17-1493-2013 CrossRefGoogle Scholar
  11. Eladawy A, Negm AM, Valeriano OCS, El-Shinawy I (2013) Assessment of climate change impacts on El-Burullus lake, Egypt, based on hydrodynamic modeling. Int Water Technol J (IWTJ) 3(4):207–216Google Scholar
  12. Hassan MAER, Omran ESE (2017) Modelling of land-use changes and their effects by climate change at the southern region of Port Said governorate, Egypt. Model Earth Syst Environ 3:13.  https://doi.org/10.1007/s40808-017-0276-1 CrossRefGoogle Scholar
  13. Hegazy IR, Kaloop MR (2015) Monitoring urban growth and land use change detection with GIS and remote sensing techniques in Daqahlia governorate Egypt. Int J Sustain Built Environ.  https://doi.org/10.1016/j.ijsbe.2015.02.005 Google Scholar
  14. Hegazy AK, Medany MA, Kabiel HF, Maez MM (2008) Spatial and temporal projected distribution of four crop plants in Egypt. Nat Resour Forum UN 32:316–324CrossRefGoogle Scholar
  15. Jain M, Dawa D, Mehta R, Dimri AP, Pandit MK (2016) Monitoring land use change and its drivers in Delhi, India using multi-temporal satellite data. Model Earth Syst Environ 2:19.  https://doi.org/10.1007/s40808-016-0075-0 CrossRefGoogle Scholar
  16. Keshtkar H, Voigt W (2016b) Potential impacts of climate and landscape fragmentation changes on plant distributions: coupling multi-temporal satellite imagery with GIS-based cellular automata model. Ecol Inform 32:145–155CrossRefGoogle Scholar
  17. Khorram S, Biging GS, Chrisman NR (1999) Accuracy assessment of remote sensing-derived change detection. American Society of Photogrammetry and Remote Sensing, Maryland, p 64Google Scholar
  18. Kumar A, Rajput PS (2013) Changing scenario of land use/land cover of Chitrakoot area. District Satna, Madhya Bharti, LVII:62–66Google Scholar
  19. Lenney MP, Woodcock CE, Collins JB (1996) The status of agricultural lands in Egypt: the use of multi temporal NDVI features derived from Landsat TM. Remote Sens Environ 56(1):8–20.  https://doi.org/10.1016/0034-4257(95)00152-2 CrossRefGoogle Scholar
  20. Lunetta RS, Elvidge CD (1998) Remote sensing change detection. Ann Arbor Press, MichiganGoogle Scholar
  21. Maldonado FD, dos Santos JR, de Carvalho VC (2002) Land use dynamics in the semi-arid region of Brazil (Quixaba, PE): characterization by principal component analysis (PCA). Int J Remote Sens 23(23):5005–5013CrossRefGoogle Scholar
  22. 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 2:168.  https://doi.org/10.1007/s40808-016-0233-4 CrossRefGoogle Scholar
  23. Parsa VA, Yavari A, Nejadi A (2016) Spatio-temporal analysis of land use/land cover pattern changes in Arasbaran biosphere reserve: Iran. Model Earth Syst Environ 2:178.  https://doi.org/10.1007/s40808-016-0227-2 CrossRefGoogle Scholar
  24. Richter R, Schlapfer D (2013) Atmospheric/topographic correction for satellite imagery: ATCOR-2/3 User Guide, DLR IB 565-01/13, Wessling, GermanyGoogle Scholar
  25. Selvam S (2012) Use of remote sensing and GIS techniques for land use and land cover mapping of Tuticorin Coast, Tamilnadu. Univers J Environ Res Technol 2(4):233–241Google Scholar
  26. Shalaby A, Gad A (2010) Urban sprawl impact assessment on the fertile agricultural land of Egypt using remote sensing and digital soil database, case study: Qalubiya governorate. US Egypt workshop on space technology and geoinformation for sustainable development, CairoGoogle Scholar
  27. Shalaby A, Moghanm FS (2015) Assessment of urban sprawl on agricultural soil of northern Nile delta of Egypt using RS and GIS. Chin Geogra Sci 25(3):274–282CrossRefGoogle Scholar
  28. Shalaby A, Tateishi R (2007) Remote sensing and GIS for mapping and monitoring land cover and land-use changes in the Northwestern coastal zone of Egypt. Appl Geogr 27(1):28–41.  https://doi.org/10.1016/j.apgeog.2006.09.004 CrossRefGoogle Scholar
  29. Soil Survey Staff (2014) Keys to soil taxonomy, 12th edn. USDA-Natural Resources Conservation Service, Washington, DCGoogle Scholar
  30. Van Engelen VWP, Wen TT (1995) Global and national soils and terrain digital database (SOTER). Procedures manual (revised edition). ISSS-UNEP-FAO-ISRIC, WageningenGoogle Scholar
  31. Wu X, Shen Z, Liu R, Ding X (2008) Land use/cover dynamics in response to changes in environmental and socio-political forces in the upper reaches of the Yangtze river. China Sens 8:8104–8122.  https://doi.org/10.3390/s8128104 CrossRefGoogle Scholar
  32. Yikalo HA, Pedro C (2010) Analysis and modeling of urban land cover change in Setúbal and Sesimbra, Portugal. Remote Sens 2(1):1549–1563.  https://doi.org/10.3390/rs2061549 Google Scholar
  33. Yuan D, Elvidge CD, Lunetta RS (1999) Survey of multi-spectral methods for land cover change analysis. In: Lunetta RS (ed) Remote sensing change detection: environmental monitoring methods and applications. Taylor & Francis, London, pp 21–39Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Soils and Water Use DepartmentNational Research Centre (NRC)GizaEgypt
  2. 2.Land and Water Technologies Dept., Arid Lands Cultivation Research Inst.City for Scientific Research and Technological ApplicationsBorg El-ArabEgypt

Personalised recommendations