Change Detection of Inland Water Bodies Using Remote Sensing Techniques. A Case Study: Lake Maryuit, Egypt
Mahmoud A. Hassaan: (Lecturer, Geography Department, Faculty of Arts in Damanhour – University of Alexandria. Email: mhassaan@hotmail.com).
pp: 73 – 100
Abstract:
Lake Maryuit is one of the northern Egyptian lakes, located in the north western coast of Egypt. The lake contributes to fish production, serves as a drainage basin for the adjacent cultivated land, and adjusts the climate of Alexandria city. Also, the lake has great potentials for recreational and tourism activities. Moreover, the lake is considered as an ecosystem, which provides a habitat for various species. Nevertheless, the lake has been suffering from a wide range of stresses including high levels of pollution in addition to land filling activities to acquire land for urban expansion, which led to a significant decline in the lake area over the past decades. Such stresses, consequently, restricts the services provided by the lake. This, in turn, highlights the need for continuous monitoring of the changes in the area of the lake and analyzing the main reasons underlying the decline in the lake area.
The main objective of this paper is to detect changes in the area of Lake Maryuit through remote sensing techniques over the period 1984 – 2002. In this study, Post-classification technique was employed, using Landsat Thematic Mapper (TM), and Enhanced Thematic Mapper (ETM+) data to detect such changes. It was found that the lake area has declined about 4.63% over the stated period. Most of the reduction in the lake area was concentrated in the eastern and northern parts of the lake, due to land filling activities and urban encroachment on the lake as well as the construction of new highways. This study could support the monitoring and management of natural resources in the case of Lake Maryuit and similar cases as it provides an accurate quantitative analysis of the development of the lake area.
Keywords: Remote sensing, inland water bodies, change detection.