Assessment of Coastal Vulnerability to Climate Change Impacts using GIS and Remote Sensing: A Case Study of Al-Alamein New City

Recently, climate change has become a catastrophic phenomenon in the whole world. It has not only devastating effects on the environment but also on the social and economic aspects of societies, especially those seeking to achieve sustainable development. Coastal areas are classified as one of the areas that are particularly exposed to current and projected risks connected to climate change. Selection of suitable climate adaptation means requires an integrated evaluation of climate change impacts and detects the vulnerability degree of various areas exposed to climate change. Therefore, this paper uses Remote Sensing (RS) and Geographic Information System (GIS) techniques to develop a GIS data model (Climate-Coastal Model) for evaluating the long-term impacts of climate changes and delineating the most vulnerable areas in coastal zones. In this regard, specific indicators are needed to detect the vulnerable areas. Four main effective parameters of climate change impacts were selected, which are meteorological parameter, topographical structures parameter (Earth Shape), engineering geology parameter, and shoreline parameter. The paper considered that all indicators in the four parameters have equal weights, where the results depended on changing the values of model indicators during the study period, which is 30 years. Al-Alamein New City in Egypt is presented as a case study to demonstrate the practical features of the proposed model. The results of a developed model according to 30 years study period reveal that the affected areas from climate change impacts are those located along the shoreline. Vulnerability along the shoreline has divided into three categories. The first one represents the least vulnerable areas, which located in Al-Alamein city and constitute about 0.00154 km(2) from the total area (227.65 km(2)). This is due to being affected by low values of meteorological indicators and minor erosion and accretion processes comparing to the other sections. The second one represents the moderate vulnerable areas, which scattered throughout all sections of the case study: Al-Alamein City, Tel Al-Eis, and Sidi Abd El-Rahman. It constitutes about 0.9941 km(2) from the total area. The last one represents the most vulnerable areas, which located also in all sections of the study area and forms about 0.72092 km(2) from the total area which have low elevations below the average mean of sea water level that means it is most vulnerable to any climate change scenarios. It is also affected by high values of coastal erosion, costal accretion, and wind speed as well as a high percentage of dew point. The proposed model is considered as a decision support tool, which helps the decision-makers to detect the vulnerability degree of any areas exposed to climate-change impacts based on multi-criteria and parameter to give the priority for such areas. (C) 2020 Published by Elsevier Ltd.

Automated summary

This paper utilizes Remote Sensing and Geographic Information System techniques to develop a GIS data model for evaluating the long-term impacts of climate change on coastal zones and identifying the most vulnerable areas. By selecting suitable climate adaptation means, the devastating effects of climate change can be minimized.