Transactions Template JOURNAL OF ENGINEERING RESEARCH AND TECHNOLOGY, VOLUME 4, ISSUE 4, DECEMBER 2017 124 The Impact of Sea Groins in the Egyptian Side of Rafah on the Erosion of the Beaches of the Southern Area of the Gaza Strip Using Remote Sensing and GIS Maher A. El-Hallaq Associate Professor of Surveyingy and Geodesy, Civil Engineering Department, The Islamic University of Gaza, Palestine, mhallaq@iugaza.edu.ps Abstract— Understanding spatio-temporal changes is essential to many aspects of engineering, geographic and planning researches. The coastal zone is the most important and the most intensively used area compared with the other populated areas in the Gaza Strip. The rapid increase of population on Gaza coastal area leads to depletion of the coastal zone resources and change the coastal morphology. In this research, five Landsat satellite imageries are collected during the period from 2008 to 2016, First, all satellite images are radiometric and atmospherically corrected. Remote Sensing techniques and Geographic Information System are used for spatio- temporal analysis in order to detect changes in the shoreline position and coastal areas of the southern governorates. Results indicate that the net change on the beach area of Rafah Governorate equals to -71 donum during the analysis period, which is equivalent to -8.9 donum/year. The net change on the beach area of Khan Younis Governorate equals to -105.5 donum with the rate of -13.2 donum/year. The analysis of Digital Shoreline Analysis System (DSAS) indicates that the net average rate for Rafah’s beach is equal to -3.7 m/year (erosion) and -2.7 m/year for Khan Younis. All of these statistics indicate that the obvious trend in the Southern beach is under serious erosion problem. This study is emphasized that the coastal band is considered as a critical area, it is therefore necessary to move all stakeholders to monitor and protect the southern area of Gaza Strip beach from the risk of drift that threatens vital installations and environmental parameter along the beach, such as streets, hotels, tourism facilities, mosques and houses. Index Terms— Gaza Strip, Shoreline Erosion, Remote Sensing, Spatio-Temporal Analysis. I INTRODUCTION The coastal zone is one of the most important and most densely populated areas than other regions in the Gaza Strip. The rapid increase in population in this region leads to an increase in the consumption of its resources and is therefore subject to high pressure from both human and geomorpho- logical activities. In some parts of the southern coast of the Gaza Strip, the process of seashore erosion is sensitive as it threatens to demolish many buildings and roads that are di- rectly on the coast. In 2010, Egypt built a sea groins at the coast of the Egyptian side of Rafah using large rocks. It is placed 2 km from the sea border between Gaza and Egypt, and extends for about 1 km inside the sea. Recently, erosion can be clearly seen in the southern governorates of Gaza Strip, Figure 1. The beach is deteriorated as a result of the sea waves hitting the beach and in the case of high waves, water reaches the sand dunes and thus removes parts of it. When the establishment of a sea obstruction to the move- ment of sea currents that are loaded with sand, sand accumu- lation occurred south of the southern groin and on the other hand, erosion took place north of the northern groin [1]. It is expected to face serious problems in the coming few years. In the absence of enough number of studies on the coastal area of the Gaza Strip, therefore, this study is performed to highlight the impact of the Egyptian marine groins on the erosion of the southern shores of the Gaza Strip using GIS. GIS is one of the most advanced technologies that is capable to deal with a large amount of data and conduct many com- puterized operations as well as extensive spatial analysis. Figure 1 Seashore Erosion of Rafah City- Palestine mailto:mhallaq@iugaza.edu.ps Maher A. El-Hallaq / The Impact of Sea Groins in the Egyptian Side of Rafah on the Erosion of the Beaches of the Southern Area of the Gaza Strip Using Remote Sensing and GIS (2017) 125 II THE STUDY AREA Rafah is an Egyptian-Palestinian City, half of which is located inside the Egyptian border and is called Rafah-Egypt. The other half is located in the Gaza Strip and is called Rafah-Palestine. The latter is located in the southern part of the Gaza Strip. Its population in 2016 is about 233,490 people [2] and is located 13 km from Khan Younis, 16 km from the village of Sheikh Zuwayd in Sinai, and 45 km from the Egyptian City of El Arish, Rafah rises from the sea by 48 meters. It is characterized by sandy land, surrounded by sand dunes from each side, then less rainfall and ends fertile towards the desert. The average temperature is between 30 degrees in summer and 10 degrees in winter. The average rainfall in Rafah is 250 mm [3]. Figure 2 shows the Egyptian and Palestinian sides of Rafah City. III THE STUDY AIM This study aims to conduct spatio-temporal analysis to de- tect the changes of the southern coastline of the Gaza Strip during the period between (2008-2016) based on analyzing satellite imagery using remote sensing techniques and geo- graphic information system. To implement this study, the following objectives should be achieved: • Detecting the amount and rate of change in the area of the coast of the southern Gaza Strip. • Calculating the linear rate of change along the shoreline using the Digital Shoreline Analysis System (DSAS). • Making recommendations to those responsible for ad- vancement. IV METHODOLOGY There are multiple approaches used in geographic research, as each approach meets the requirements of a particular stage of research, but this study depends mainly on: (A) de- scriptive approach: It addresses the geographical, historical, social and economic profile of the study area, as well as concepts and knowledge of GIS. It also involves data collec- tion from the USGS website with the focus on satellite im- agery captured by Landsat satellites,(B) Historical Ap- proach: This approach is to follow a historical phenomenon, which is not to understand the past but for future planning as well, (C) Applied or analytical approach: The use of an ap- propriate image processing environment such as ERDAS software to preprocess, enhance, classify and transform im- agery. In addition to, the use of ArcGIS and its tools in de- tecting changes and rates of change along the coast of the study area. Figure 3 outlines the overall framework of the used methodology. A Data Collection In this study, satellite images from the U. S. Geological Survey (USGS) website are downloaded during the period between (2008-2016) as shown in Table 1 according to the following criteria: downloading images of January, choosing images that are nearly free from noise to reduce preprocessing operations, preferring Thematic Mapper (TM) images than Multi Spectral Scanner (MSS) and Enhanced Thematic Mapper plus (ETM+) to avoid black gaps [4]. Landsat 7 ETM+ downloaded image- ries (2008-2012) are SLC-off data (contains black gaps, DN=0). This type of gaps should be minimized by taking two ETM+ scenes, radiometrically corrected, and then combines them for more complete coverage. At last, using all bands in GeoTIFF format. Figure 3 Methodology Framework Figure 2 Rafah-Egypt and Rafah-Palestine Maher A. El-Hallaq / The Impact of Sea Groins in the Egyptian Side of Rafah on the Erosion of the Beaches of the Southern Area of the Gaza Strip Using Remote Sensing and GIS (2017) 126 B Preprocessing Task Preprocessing of downloaded images involves various oper- ations as clipping the study area by image subset, perform- ing the radiometric and geometric corrections, enhancing and reducing image noise by removing black gaps. Since the digital sensors record the electromagnetic radiation intensity of each point displayed on the surface of the earth in the form of Digital Number (DN) for each spectral range, the range of the DN value that is captured by the sensor depends on its radiation discrimination. The Landsat MSS sensors measure the radiation on a scale of DN (0 - 63) while Land- sat TM and ETM + measure it on a scale of (0 – 255), which includes the correction of the digital image processing to improve the accuracy of the amount of brightness value [5]. It should be noted that the sources of noise and the correct ways to correct them depend in part on the type of sensor, the nature of the image and the nature of the imaging kind used to capture digital image data. Figure 4 shows examples of some preprocessing tasks of the collected imagery. C Image Classification The supervised classification is used because the difference is clear between land and water in the collected images [6]. Several land and water training samples are selected using ERDAS Imagine 2014 software. The user specifies the vari- ous pixels values or spectral signatures that should be asso- ciated with each class (here, land or water). This is done by selecting representative sample sites of known cover type called training sites. It is important to choose training sites that cover the full range of variability within each class to allow the software to accurately classify the rest of the im- age. The computer algorithm then uses the spectral signa- tures from these training sites to classify the whole image. Figure 5 shows an example of a supervised classification of one of the images under consideration D Change Detection Analysis At this stage, two types of analysis are conducted.; the change of the beach area between any two sequent shore- lines of any selected interval and the other is the linear rate of change of the shoreline of the considered interval using the Digital Shoreline Analysis System (DSAS) tool. To cal- culate the change in the area between the two shorelines of the beach, ArcGIS tools are used, first the shorelines are merged using the append tool until they become in one fea- ture class. Then, they are processed to form a closed space and the lines are converted to polygon using "feature to pol- ygon" tool. Finally, accretion and erosion areas for both Rafah and Khan Younis can be calculated. To calculate the linear rate of change along the shoreline, the DSAS is used. It enables the user to calculate the rate of change over differ- ent time periods for different locations along the shoreline. The DSAS tool creates vertical transects that are defined by the user and calculates statistics for the rate of change of the shoreline within the attribute table. The tool requires two shorelines and a reference line; the reference line is done by the user, which is the starting point for the generation of transects that are perpendicular to it at regular distances specified by the user and depend on the tool in the conduct Figure 5 Supervised Classification of Images Figure 4 Part of Preprocessing Task TABLE 1 Imagery Characteristics. Spatial Resolution, m Imagery Date Image Source Image No. 30 x 30 9-1-2008 Landsat7 1 30 x 30 9-1-2010 Landsat7 2 30 x 30 9-1-2012 Landsat7 3 30 x 30 9-1-2014 Landsat8 4 30 x 30 9-1-2016 Landsat8 5 Maher A. El-Hallaq / The Impact of Sea Groins in the Egyptian Side of Rafah on the Erosion of the Beaches of the Southern Area of the Gaza Strip Using Remote Sensing and GIS (2017) 127 of statistical calculations. Figure 6 illustrates the basic steps to generate transects and the corresponding statistical calcu- lations by DSAS tool [7]. Thus, all data entered for the DSAS tool must be within the personal geodatabase, which involves the reference line and shorelines for every two-year periods in a single feature class. The End Point Rate (EPR) is calculated by determining the distance between the old date and modern date shorelines divided by the number of years between them. The basic advantage of this method is the simplicity of calculations and the spread of their applica- tion and also gives excellent accuracy over long periods. But the main drawback is that they cannot handle more than two beach lines. V ANALYSIS AND RESULTS The study area is classified into two zones; (A) Rafah, 2.4 km shoreline long and (B) Khan Younis, 10.4 km shoreline long. The two zones are shown in Figure 7. Figure 8 highlights the extracted shorelines of Rafah- Palestine in the period (2008–2016). A The Change in Area Analysis The study interval between 2008 to 2016 is divided into four periods, each of two-year period. Using GIS tools, the con- fined space between each of the four time periods is calcu- lated and presented in Tables 2 and 3, where the negative values represent the erosion case and the positive values represent the accretion case. Table 2 illustrates the results of zone A that corresponds to the analysis of the shoreline of Rafah-Palestine Governorate. It is noticed that the quantities of the erosion are in the case of continuous increase with time, especially in the periods between (2012-2014) and (2014-2016). As for the amounts of accretion is somewhat instable and closer to be fixed with time. The total erosion area during the study period (2008-2016) is about 71 donum with a rate of -8.9 m 2 /year. TABLE 2 The change of area analysis for Rafah-Palestine shoreline Image Period Erosion Accretion Net of Change Total x 10 3 [m 2 ] Rate x 10 3 [m 2 / year ] Total x 10 3 [m 2 ] Rate x 10 3 [m 2 / year] Total x 10 3 [m 2 ] Rate x 10 3 [m 2 / year] 2008- 2010 -10.25 -5.12 4.28 2.14 -5.96 -2.98 2010- 2012 -11.14 -5.57 6.05 3.02 -5.10 -2.55 2012- 2014 -30.84 -15.42 1.18 0.59 -29.66 -14.83 2014- 2016 -35.12 -17.56 4.54 2.27 -30.57 -15.29 Total -87.35 -10.92 16.05 2.01 -71.29 -8.91 Note: (+) sign indicates accretion, (-) sign indicates erosion . Figure 7 The study Area Zones Figure 8 The shoreline of zone A (2008 – 2016) Figure 6 DSAS Basic Steps Maher A. El-Hallaq / The Impact of Sea Groins in the Egyptian Side of Rafah on the Erosion of the Beaches of the Southern Area of the Gaza Strip Using Remote Sensing and GIS (2017) 128 Table 3 summarizes the results of zone B which corresponds to the analysis of the shoreline of Khan Younis Governorate. One can notice that starting in 2010, there is an increase in the quantities of erosion at a linear rate as expected due to the presence of the Egyptian marine groins, and the quanti- ties of accretion are also oscillatory and atypical. The total erosion area is about 105.5 donum during the study period (2008-2016) with a rate of -13.2 m 2 /year. B The Linear Change in Shoreline Analysis Coastline linear change rates are calculated using the DSAS tool with the EPR statistical technique. 341 transects are cre- ated and spaced at a regular distance of 40 m. Zone A is cov- ered by 56 transects. Table 4 shows the average linear change rate results for zone A, Rafah-Palestine. Its average erosion rate is 3.7 m/year. Transects from 57 to 341 are generated by DSAS tool to cover zone B, Khan Younis City which has a shoreline of 10.4 km long. Table 5 summarizes the average linear change rate of this zone. Its average erosion rate is 2.69 m/year. TABLE 3 The change of area analysis for Khan Younis shoreline Image Period Erosion Accretion Net of Change Total x 10 3 [m 2 ] Rate x 10 3 [m 2 / year] Total x 10 3 [m 2 ] Rate x 10 3 [m 2 / year] Total x 10 3 [m 2 ] Rate x 10 3 [m 2 / year] 2008- 2010 -52.83 -26.42 26.25 13.13 -26.58 -13.29 2010- 2012 -28.86 -14.43 67.43 33.72 38.57 19.29 2012- 2014 -60.34 -30.17 2.02 1.01 -58.31 -29.16 2014- 2016 -89.78 -44.89 30.62 15.31 -59.16 -29.58 Total -231.8 -28.98 126.32 15.79 -105.48 -13.19 Note: (+) sign indicates accretion, (-) sign indicates erosion . Figure 9 Annual shoreline linear change rate (2008–2016) TABLE 4 Average linear change rate for Rafah-Palestine (2008-2016) Image period Transect Erosion Accretion Net Average (m/year) Average (m/yr) Max (m/yr) Average (m/yr) Max (m/yr) 2008- 2010 1-56 -5.45 -9.33 3.21 6.99 -3.44 2010- 2012 1-56 -4.36 -9.00 3.32 8.87 -1.15 2012- 2014 1-56 -8.03 -15.45 1.85 2.92 -6.78 2014- 2016 1-56 -5.35 -15.97 6.34 10.83 -3.44 Average linear change rate from 2008-2016 -3.70 Note: (+) sign indicates accretion, (-) sign indicates erosion TABLE 5 Average linear change rate for Khan Younis (2008-2016) Image period Transect Erosion Accretion Net Average (m/year) Average (m/yr) Max (m/yr) Average (m/yr) Max (m/yr) 2008- 2010 57-341 -5.23 -13.83 4.91 13.45 -1.71 2010- 2012 57-341 -3.53 -8.43 4.59 11.05 1.70 2012- 2014 57-341 -8.11 -21.24 1.51 4.15 -7.51 2014- 2016 57-341 -6.00 -15.54 5.74 12.87 -3.25 Average linear change rate from 2008-2016 -2.69 Note: (+) sign indicates accretion, (-) sign indicates erosion Maher A. El-Hallaq / The Impact of Sea Groins in the Egyptian Side of Rafah on the Erosion of the Beaches of the Southern Area of the Gaza Strip Using Remote Sensing and GIS (2017) 129 The results for both zones which are obtained above is pre- sented graphically in Figure 9. From Figure (9), the follow- ing notes can be concluded:  During the period (2008-2010), fluctuations in the values of erosion and accretion along the coast be- fore the construction of the Egyptian marine groins is observed. • During the periods (2010-2012), (2012-2014) and (2014-2016), the prevailing pattern on the shoreline is the erosion as the quantities of shoreline deterio- ration are much larger than the amounts of accre- tion that are negligible on these periods. • The period (2012-2014) is the most exposed period of erosion relative to otherl periods. • Presence of accretion amounts distributed along the shore during the period (2014-2016) is noticed, due to the construction of several small marine groins on the Palestinian side as a partial solution to re- duce the erosion of the shore. • The effect of the Egyptian marine groin is equal to both Rafah and Khan Younis governorates as the pattern during each period is similar to the entire length of the beach. VI CONCLUSION The analysis of satellite observations of Landsat for the Mediterranean coast in the governorates of Rafah and Khan Younis during the period (2008-2016) shows that there are a change in the patterns of erosion and accretion. The results reveal that the net change in the area of Rafah Governorate equals about 71 donum of sand at an erosion average of -8.9 donum annually. The net erosion on the area of Khan Younis beach equals about 105.5 donum at a rate of -13.2 donum annually. The impact of the Egyptian sea groin on Rafah, about three times greater than Khan Younis. This confirms the previous results that the mean net change of Rafah beach using EPR analysis is equal to 3.7 m / year (erosion) and for Khan Younis is 2.69 m / year (erosion). It is recommended to support researchers and projects in this field as its great- est importance. For future studies, it is suggested to calculate the volume change of critical areas and to refine the analysis taken into account the tidal data. The concerned authorities should conduct periodic studies to follow the future changes. To benefit from the results of this study, strategies and sys- tematic steps to solve the problem of erosion of the coast of the study area, namely Rafah and Khan Younis should be made. REFERENCES [1] Zviely, D. and M. Klein, "The environmental impact of the Gaza Strip coastal constructions" J.Coast. Res.Vol. 19 (4):1122-1127, 2003. [2] Palestinian Central Bureau of Statistics (PCBS), "Popu- lation, Housing and Establishment Census 2007-2016". Rafah Governorate . Census Final Results, Accessed on 01 April 2017. URL: http://www.pcbs.gov.ps/Portals/_Rainbow/Documents/r afaa.htm [3] Wikipedia, The Free Encyclopedia. Accessed on 10 March 2017. URL:https://en.wikipedia.org/wiki/Rafah [4] El-Hallaq, M.A. and Habboub, M.O. "Using GIS for Time Series Analysis of the Dead Sea from Remotely Sensing Data". Open Journal of Civil Engineering, 4, 386-396, 2014. http://dx.doi.org/10.4236/ojce.2014.44033 [5] Edmund Green, Peter Mumby, Alasdair Edwards and Christopher Clark.. Remote Sensing Handbook for Trop- ical Coastal Management Vol. 3, UNESCO Publishing, Paris, 2000. [6] Jesús D. Chinea. Supervised Classification. Universidad de Puerto Rico, Recinto Universitario de Mayagüez. [Online] 2006. [Cited: 3 7, 2017.] http://www.uprm.edu/biology/profs/chinea/gis/lectesc/tu t4_3.pdf. [7] Himmelstoss, E.A., Zichichi, J.L., and Ergul, Ayhan. 2009 Digital Shoreline Analysis System (DSAS) version 4.0 — An ArcGIS extension for calculating shoreline change: U.S. Geological Survey Open-File Report 2008-1278. *updated for version 4.3. Maher A. El-Hallaq An associate professor of Surveying and Geodesy. He is a member of Civil Engineering Department at the Islamic University of Gaza since 1996. He also works as a consult- ant of many local municipalities and private institutions in the Gaza Strip. His primary research and professional interests are in the various fields of Geomatics. In addition to, he published a book and a great number of conference and Journal papers as well as being a reviewer to local and world Journals. http://www.pcbs.gov.ps/Portals/_Rainbow/Documents/rafaa.htm http://www.pcbs.gov.ps/Portals/_Rainbow/Documents/rafaa.htm https://en.wikipedia.org/wiki/Rafah http://dx.doi.org/10.4236/ojce.2014.44033