Predicting the Dynamic Growth of Built-up Lands at the Expense of Green Patches in 2050
A scientific thesis which was presented at the University of Bahrain has called for the creation of a geographical database that utilizes space science, and artificial intelligence applications in order to monitor green spaces, and agricultural areas, as well as predicting their growth, and decline rates. Thus, stressing the importance of adopting such artificial intelligence techniques in the Kingdom of Bahrain and investing in space science.
The thesis was submitted by Engineer Ebrahim AlBurshaid, a student at the University of Bahrain as part of the requirements for obtaining a master’s degree in engineering management.
The examination committee discussed with the researcher Ebrahim Alburshaid in the thesis titled: “Spatiotemporal Land Use Analysis and Urban Growth Dynamic Prediction in the Kingdom of Bahrain.”
The thesis dealt with several technical, administrative, and economic aspects on the importance of applying remote sensing techniques in the Kingdom of Bahrain. And how it works by relying on satellite images as a main source of ground controlling information.
The thesis was able to achieve integration between the employment of space science, artificial intelligence techniques, and geographic information systems in developing an applicable economic solution in the Kingdom of Bahrain to monitor agricultural lands and bridge the information gap in the same field.
The researcher was able to study the urbanization expansion in the Northern Governorate during 2016 to 2020. Accordingly, the dynamic growth of built-up lands at the expense of green patches was predicted during 2030 and 2050 by applying the Multi-Layer Perceptron (MLP) Neural Network algorithm. The results concluded that urban construction will increase by 2048 hectares from 2020 to 2050, and green areas and barren lands will shrink by 702 and 1,340 hectares, respectively. On the other hand, the researcher was able to apply two types of deep learning algorithms.
The discussion committee was comprised of: A member of the faculty in the Department of Electrical and Electronic Engineering at the University of Bahrain, Dr. Mohab Abdel-Hamid Manjoud. The supervisor of the thesis and a member of the faculty in the same department, Dr. Ibrahim Matar, an internal examiner. The dean of the Faculty of Computers at the Arab Academy for Science, Technology, and Maritime Transport in Egypt, Prof. Dr. Yasser Alaeddin Al-Sunbati who is an external examiner.
The study monitored one type of tree, which is palm trees, and indicated the areas of their distribution in the various regions of Bahrain. This was accomplished through a deep learning model that was tested in several different areas, where the environment in which the palm tree is available, and the results were highly accurate.
Researcher Ebrahim Alburshaid, pointed out the possibility of using the developed model to monitor any target. Whether the target is agricultural trees or others, indicating the economic feasibility of applying a benefit-cost analysis that he implemented in his thesis on the agricultural land monitoring project and automatic palm monitoring.
In conclusion, researcher Alburshaid, extended his sincere thanks to the University of Bahrain for providing the scientific and educational environment in order to complete the thesis. And special thanks to Al Mabarrah Al-Khalifia Foundation, which has taken care of all the tuition costs under “Rayaat” scholarship program and the support it has provided to young people and enables them to raise the level of educational attainment in a way that serves our dear Kingdom. He also thanked the Board of Directors of the NSSA, and the Executive Management for their great support, and encouragement to face all challenges.