Modeling Urban Encroachment on the Agricultural Land of the Eastern Nile Delta Using Remote Sensing and a GIS-Based Markov Chain Model

• Main Authors: Kelsee Bratley, Eman Ghoneim
• Format: Article
• Language: English
• Published: MDPI AG 2018-10-01
• Series: Land
• Subjects: land change modeler; Land Use Land Cover; cluster-busting; multi-layer perceptron neural network; minimum noise fraction; Egypt
• Online Access: http://www.mdpi.com/2073-445X/7/4/114

Historically, the Nile Delta has played an integral part in Egyptian civilization, as its fertile soils have been cultivated for centuries. The region offers a lush oasis among the expansive arid climate of Northern Africa; however, in recent decades, many anthropogenic changes to the environment have jeopardized Egypt’s agricultural productivity. Political instability and lack of sufficient regulations regarding urban growth and encroachment have put agricultural land in the area at risk. Advanced geospatial techniques were used to assess the rate at which urban areas are increasing within the region. A hybrid classification of Landsat satellite imagery for the eastern sector of the Nile Delta, between the years 1988 and 2017, was conducted to map major land-use and land-cover (LULC) classes. The statistical change analysis revealed that urban areas increased by 222.5% over the study period (29 years). Results indicated that urban areas are encroaching mainly on established agricultural lands within the Nile Delta. Most of the change has occurred within the past nine years, where approximately 235.60 km2 of the cultivated lands were transitioned to urban. Nonetheless, at the eastern delta flank, which is bordered by desert, analysis indicated that agricultural lands have experienced a considerable growth throughout the study period due to a major desert reclamation effort. Areas most at risk from future urban expansion were identified. A simulation of future urban expansion, using a Markov Chain algorithm, indicated that the extent to which urban area is simulated to grow in the region is 16.67% (277.3 km2) and 37.82% (843 km2) by the year 2026, and 2050, respectively. The methods used in this study are useful in assessing the rate of urban encroachment on agricultural lands and can be applied to similar at-risk areas in the regions if appropriate site-specific modifications are considered.