Land Cover Map Delineation, for Agriculture Development, Case Study in North Sinai, Egypt Using SPOT4 Data and Geographic Information System


Land cover map for a part of North Sinai was produced using the FAO—Land Cover Classification System (LCCS) of 2004. The standard FAO classification scheme provides a standardized system of classification that can be used to analyze spatial and temporal land cover variability in the study area. This approach also has the advantage of facilitating the integration of Sinai land cover mapping products to be included with the regional and global land cover datasets. The total study area is 7450 km2 (1,773,842) feddans. The landscape classification was performed on SPOT4 data acquired in 2011 using combined multi-spectral bands of 20 meter spatial resolution. Geographic Information System (GIS) was used to edit the classification result in order to reach the maximum possible accuracy. GIS was also used to include all necessary information. The identified vegetative land cover classes of the study area are irrigated herbaceous crops, irrigated tree crops and rain fed tree crops. The non-vegetated land covers in the study area include: bare rock, bare soil, bare soil stony, bare soil very stony, bare soil salt crusts, loose and shifting sands and sand dunes. The water bodies were classified as artificial perennial water bodies (fish ponds and irrigated canals) and natural perennial water bodies as lakes (standing) and rivers (flowing). Artificial surfaces in the study area include linear and non-linear. The produced maps and the statistics of the different land covers are included in the following sub-sections.

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N. Saleh and M. Aboelghar, "Land Cover Map Delineation, for Agriculture Development, Case Study in North Sinai, Egypt Using SPOT4 Data and Geographic Information System," Advances in Remote Sensing, Vol. 2 No. 1, 2013, pp. 35-43. doi: 10.4236/ars.2013.21005.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] UNEP/FAO, “Report of the UNEP/FAO Expert Meeting on Harmonizing Land Cover and Land Use Classifications,” GEMS Report Series, No. 25, Geneva, 23-25 November 1993.
[2] A. Di Gregorio and L. J. M. Jansen, “FAO Land Cover Classification System: A Dichotomous, Modular-Hierarchical Approach,” The Federal Geographic Data Committee Meeting, Vegetation Subcommittee and Earth Cover Working Group, Washington, 15-17 October 1996.
[3] E. F. Lambin and D. Ehrlich, “Land—Cover Changes in Sub-Saharan Africa (1982-1991): Application of a Change Index Based on Remotely Sensed Surface Temperature and Vegetation Indices at a Continental Scale,” Remote Sensing of Environment, Vol. 61, No. 2, 1997, pp. 181-200. doi:10.1016/S0034-4257(97)00001-1
[4] F. Rembold, S. Carnicelli, M. Nori and M, Ferrari, “Use of Aerial Photographs, Landsat TM Imagery and Multidisciplinary Field Survey for Land—Cover Change Analysis in the Lakes Region (Ethiopia),” International Journal of Applied Earth Observation and Geoinformation, Vol. 2, No. 3, 2000, pp. 181-189. doi:10.1016/S0303-2434(00)85012-6
[5] J. E. Mendoza and R. Etter, “Multitemporal Analysis (1940-1996) of Land Cover Changes in the Southwestern Bogota Highplain (Colombia),” Landscape and Urban Planning, Vol. 59, No. 3, 2002, pp. 147-158. doi:10.1016/S0169-2046(02)00012-9
[6] A. R. Palmer and A. F. van Rooyen, “Detecting Vegetation Change in the Southern Kalahari Using Landsat TM data,” Journal of Arid Environments, Vol. 39, No. 2, 1998, pp. 143-153. doi:10.1006/jare.1998.0399
[7] Ram and A. S. Kolarkar, “Remote Sensing Application in Monitoring Land-Use Changes in Arid Rajasthan,” International Journal of Remote Sensing, Vol. 14, No. 17, 1993, pp. 3191-3220. doi:10.1080/01431169308904433
[8] Sadek, “Use of Landsat Imagery for Monitoring Agricultural Expansion of East Nile Delta, Egypt,” Egyptian Journal of Soil Science, Vol. 33, No. 1, 1993, pp. 23-24.
[9] M. P. Lenney, C. E. Woodcock, J. B. Collins and H. Hamdi, “The Status of Agricultural Lands in Egypt: The Use of Multi Temporal NDVI Features Derived from Landsat TM,” Remote Sensing of Environment, Vol. 56, No. 1, 1997, pp. 8-20. doi:10.1016/0034-4257(95)00152-2
[10] T. M. Lillesand and R. W. Kiefer, “Remote Sensing and Image Interpretation,” 4th Edition, Wiley & Sons, Chichester, 2000.

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