Change detection of Manzala Lake using remote sensing and geographic information system

Abdelazim Mohamed Negm, Hickmat Hossen

Abstract


Change detection in land use and land cover is one of the most important indicators
of global and regional environmental sustainability. In this paper, the maximum
likelihood supervised classification is applied to subsets of the Landsat TM, ETM+
and OLI/TIRS images acquired on 1984, 1998 and 2015, respectively to monitor
changes in Manzala Lake. Manzala Lake is the largest natural lake in Egypt, it is
located between longitudes 31° 45ʹ and 32° 22ʹ E and latitudes 31° 00ʹ and 31° 35ʹ
N. Six classes are detected including sea water, lake water (water bodies), floating
vegetation, Islands, sand bar and urban, and agriculture. ERDAS IMAGINE and
ArcGIS software are used in this study for processing of the images and managing
the database of each image. The results showed that the water bodies of the lake
decreased by 57.06% (47,419.1 ha), while floating vegetation and islands area
increased mostly by the same amount during the period from 1984 to 2015. This
increase in floating vegetation is due to the discharge of agriculture wastes and
municipal wastes in the lake without adequate treatment. The sea water has minor
changes during the period of study. The agriculture area increased by 28.57%
(19,285.6 ha), while the sand bar and urban area decreased mostly by the same
amount during the period from 1984 to 2015. The future prediction was conducted
using the annual rate of change over the next 15 years, resulted from this prediction
that the water bodies of the lake will be reduced by 84.67% (70,363.85 ha), and this
decrease leads to a negative impact on fisheries and the environment. The results of
this study shall help the decision-makers to take the necessary measures to reduce
the environmental risk and maintain the lake to sustain the lake water area against
further reduction.


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