A NEW APPROACH FOR THE DETERMINATION OF DUNE MIGRATION RATES USING TIME SERIES ASTER IMAGES: A CASE STUDY ON SAND DUNES WEST MAKKAH CITY

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1 A NEW APPROACH FOR THE DETERMINATION OF DUNE MIGRATION RATES USING TIME SERIES ASTER IMAGES: A CASE STUDY ON SAND DUNES WEST MAKKAH CITY ElSayed Hermas, Khalid Al-Ghamdi, Abdoul Jelil Niang Geography Department, Umm Al-Qura University, Makkah Al-Mukkarramah, KSA eaibrahim@uqu.edu.sa ABSTRACT Unlike field and traditional remote sensing techniques, the Co-registration of optically sensed images and Correlation (COSI-Corr) is capable to provide measurements of dune migration at high accuracy and over wide spatial coverages. The technique relies on accurate co-registration and ortho-rectification of two or more optically sensed images for eventual correlation using Fast Fourier Transform correlator. The correlation images comprises east-west and north-south displacement bands. Both bands can be integrated to produce annual dune migration rates in meters. In addition, both bands can integrated to produce vector displacement fields that demonstrate the direction of dune migration. The technique had been conducted on five ASTER images covering sand dune areas located west and northwest Makkah City. The averages of the annual rates of dune migration using COSI-Corr technology ranged from 4.2 to 7.9 m/yr with a mean of 6.25 m/yr. The produced vector displacement fields indicated that the direction of dune migration is southeast in response to the northerly dominant winds in the study area. The approach could be potential for studying sand dune systems in arid lands given the possibility of developing an automated operational system for monitoring dune migration using the intensive stream of satellite data available in Saudi Arabia. KEYWORDS: dune migration, COSI-Corr, hazards, remote sensing, Makkah, Saudi Arabia, ASTER. INTRODUCTION As an arid and hyper-arid environment, sand accumulations represent salient earth surface landforms, which occupy ~ 30% of the entire landscape of Saudi Arabia. In the east of Saudi Arabia, many large sand seas occur such as Al-Nufud sand sea, Al-Dahnaa sand sea, and Al-Rub a Al-Khali sand sea. To the east of Al-Dahnaa sand sea, Al-Jafura sand sea occur as well. Along with the large sand seas, many small sand seas occur to the west of al-dahnaa sand seas such as Irq Al-Rethmah, Nufud Urayq, and Nufud as Sirr. Although all the large and small sand seas occupy extensive spatial extents, they received limited scientific research works. However, some scientific activities have been carried out on Al-Nufud sand sea such as (Whitney et al., 1983; Vincent, 1984); Al Jafurah sand sea (Fryberger et al., 1984; Anton and Vincent, 1986; Shehata et al., 1992), Ad Dahna sand sea (Al-Saud, 1986; El-Nozahy, 1993), and Al Rub al Khali sand sea (McClure, 1978; Edgell, 1990). In contrast to sand seas in the eastern regions of Saudi Arabia, sand accumulations occur as small dune fields in the west of Saudi Arabia. They are scattered, and represented either over valley floors, adjacent to the mountain fronts, or over the wide coastal plains. Selective dune fields have received limited studies. The majority of them did not receive studies at all such as sand accumulations around Makkah 1

2 City. Although the area of Makkah City and its surrounding have been receiving particular scientific emphasis from the geomorphic, geologic, and environmental perspectives, none of the previous studies paid attention to sand dune accumulations. These accumulations occur within the floodplain of Wadi Fatmah, Wadi Ash Shmaysi, Wadi As Saluli, Wadi Uranah, and Wadi Ayidiyah at various spatial extents (Hermas, 2015). In this research, dune migration rates of sand accumulations in Wadi Ash Shmaysi and a selective dune field from Wadi Fatmah northwest of Makkah City has been determined using the stateof-the-art remote sensing technology. Earth observation satellites has been serving the community through providing a systematic and long archive of remote sensing images through the last 50 years. They enable mapping and studying earth surface features for various purposes including different dune characteristics such as dune mapping and taxonomy (McKee, 1979; Breed et al., 1979), pattern analysis of dune field (Ewing et al., 2006; Ewing and Kocurek, 2010a,b), spatial analysis of dune field (Hugenholtz and Barchyn, 2010; Hugenholtz et al., 2012), topographic and morphologic variations of dune field (Blumberg, 1998; Levin et al., 2004; Ojeda et al., 2005), Mineralogic and sedimentologic characteristics (Kocurek, 1996), and climatic changes (Hugenholtz and Wolfe, 2005). The aspect of determining the rates of dune migration using remote sensing have received particular interest as well (e.g., Finkel,1959; Merk, 1962; Long and Sharp, 1964; Calkin and Rutford, 1974; Wiegand, 1977; Maxwell and Vance Haynes Jr., 2001; Aql, 2002; El-Banna, 2004; Mitasova et al., 2005; Bourke et al., 2009; Tsoar, 1978; El-Banna, 2004; Tsoar et al., 2004). Through this aspect, two or more remote sensing images are georeferenced and then dune boundaries or axes could be digitized for eventual comparing these boundaries and axes to calculate the lateral displacement. Although the approach allow constraining dune migration over wide spatial coverage relative to field measurements, many shortcomings can be highlighted. Aerial photographs are expensive and analyzing them manually is time consuming. Although satellite imagery provides systematic multitemporal images of large areas at low cost, the classical definition of sand dune boundaries is highly affected by satellite geometry and illumination conditions (Liu et al. 1997). Personal bias is another source either through interpretation of dune patterns or through tracing dune boundaries and/or axes. These shortcomings make determination of sand dune movements from satellite images inaccurate (Liu et al. 1997). Developing a new technique that fills in the gaps of the previously mentioned technique is required. The Co-registration of optically sensed images and Correlation (COSI-Corr) is considered one of the recent quantitative approach of dune migration. It relies on correlating two or more ortho-recified images using Fast Fourier Transform Correlator to produce a displacement images where the value and signs of each pixel expresses the amount of surface change (in meters) and its direction respectively. The approach submitted to the scientific community by Leprince et al. (2007). Recently, the approach has been used in many studies for the purpose of determining dune migration rates and directions (Vermeesch and Drake, 2008; Necsoiu et al., 2009; Hermas et al., 2012; Al-Ghamdi and Hermas, 2015; Hermas, 2015; Al-Mutiry et al., 2016). In this research activity, the COSI- Corr approach has been conducted on five ASTER images to determine dune migration and its direction west of Makkah City. 2

3 STUDY AREA The area of Makkah city and its surroundings comprises granitic basement rocks that belong to the Pre-Cambrian. In the north and east of Makkah City, sedimentary rocks are represented as well. Complex sets of faults and fractures characterize the area and imply long tectonic history. These sets occurs either parallel or perpendicular to the direction of Red Sea. Since the initiation of the tectonic processes in Tertiary, both the basement and sedimentary rocks have been uplifted resulting in rugged topographic mountains that range in the elevation from 200 to 400 m asl. Well-developed surface stream networks incise in the rugged mountains resulting in different drainage basins around Makkah City. The trunk valleys of these drainage basins developed wide alluvial plains. The trunk valleys of Wadi Fatmah and Wadi Uranah valleys transmit mass of water and sediments from the rugged mountains around Makkah City to Red Sea in the east (Figure 1). Between both Wadi Fatmah valley in the north and Wadi Uranah in the south, a northsouth trending wide valley is located which is Wadi Ash Shmaysi (Figure 1). The abovementioned valleys have wide alluvial plains that enable wind speed to slow down resulting in the formation of sand dunes. In the northern half of Wadi Ash Shmaysi, significant sand accumulations occur west Makkah City. To the north where Wadi Ash Shmaysi is linked to Wafi Fatmah, other sand accumulations occur as well in the northwest area of Makkah City. The determination of migration rates of sand dunes in these accumulations using remote sensing images is the principal target of this research activity. METHODOLOGY Five ASTER images of spatial resolution 15 m were collected through the USGS glovis facility (website). These images were acquired in May 2005, November 2011, November 2011, November 2013, and September Table 1 presents the technical specifications of these images. They have almost similar pointing and orientation angles which is suitable for achieving successful correlation results. All images have been accurately ortho-rectified and co-registered for eventual sub-pixel correlation. The orthorectification involves iteratively careful selection of the tie points between a previously ortho-rectified image and a slave image (the raw image) (User's Guide to COSI-Corr 2009).The tie points were then converted into GCP's and eventually optimized using the reference image, a free sinks Shuttle Radar Topographic Mission Digital Elevation Model (DEM), and the ancillary file of each image that contains the various parameters of ASTER L1A sensor system along with solar zenith and azimuth angles at the time of acquisition. Once the GCP's had been optimized, mapping matrices associating the ground coordinates with the raw pixel coordinates of the raw images has been computed. These matrices define the resampling grid from the raw images to the ortho-rectified images (Figure 2). After the ortho-rectification and the co-registration processes, The Fast Fourier Transform (FFT) correlation engine was then automated to correlate each two successive ortho-rectified images. The frequency correlation with multi-scale window sizes ranging from 64 to 32 pixels and a shifting step with size of 2 pixels between the sliding windows were adopted. The correlation produced a horizontal displacement image composed of three bands: east-west, north-south, and signal-to-noise ratio bands. To remove the noise values, the Non-Local Means filter had been applied (Buades et al. 2008). 3

4 Figure 1: location of the study area. Table 1: Image specification of ASTER images used in the study. Acquisition date Pointing angle Orientation angle Sun azimuth angle Sun elevation angle November 09, November 27, November 14, September 30, September 24, spatial resolution The pixels of the east-west and the north-south displacement bands comprise values and signals. The values denote the pixel displacement between the master and slave images while the signals refer to the direction of such displacement. For instance, the positive values indicate the amount of pixel displacements in the east and north whereas the negative values indicate the amount of pixel displacements in the west and south. However, both the east-west and the north-south displacement bands were used to calculate the net migration rates using the approach proposed by Necsoiu et al. (2009). 4

5 Figure 2: The frequency of wind speeds of the various wind directions. RESULTS AND DISCUSSION The correlation of the five ortho-rectified ASTER optical images using COSI-Corr technology produces four correlation images (Figure 3). Each correlation image comprises three bands which are the east-west, north-south, and signal to noise ration bands. The east-west and north-south bands represent the horizontal displacement between the pixels of the correlating images. Each band comprises pixel values and signals. The values represent the horizontal displacements in meters whereas the signals represent the direction of movements (Figure 3). For instance, the positive values in the east-west bands indicate eastern horizontal displacement, and the negative values indicate western horizontal displacement. Similarly, the positive values in the north-south bands refer to northern horizontal displacement whereas the negative values represent a southern horizontal displacement. The highest values in the east-west bands are positive values denoting dominant eastern movements of dunes. On the other hand, the lowest negative values of the north-south bands are limited to the same dune areas referring to dominant southern directions. Both the highest positive values of the east-west bands and the lowest negative values of the north-south bands imply a southeast dominant movement. However, the net annual movements of dunes can be calculated and produced in a single band through the integration of both east-west and north-south bands. The integration of the east-west and north-south bands of the correlation images produces four annual rates of the time periods , , , and (Figure 4). Zonal statistics of the annual rates were extracted using the boundaries of the dune area (Figure 4). The annual rates of the dune areas ranged from 0.0 to 26.5 m/yr with an average of 7.1 m/yr through the time laps

Figure 3: the east-west and north-south displacement bands of the correlation images. The annual rates of the dune areas ranged from 0.0 to 24.4 m/yr with an average of 5.

6 Figure 3: the east-west and north-south displacement bands of the correlation images. The annual rates of the dune areas ranged from 0.0 to 24.4 m/yr with an average of 5.8 m/yr through the time laps The annual rates of the dune areas ranged from 0.0 to 37.8 m/yr with an average of 7.9 m/yr through the time laps Finally, the annual rates of the dune areas ranged from 0.0 to 34.1 m/yr with an average of 4.2 m/yr through the time laps (Table 2). The values of the averages indicate that there is no significant differences in the dune migration rates through the period of measurements ranging from 2011 to In addition, there is no pattern of changes of dune migration values as well. To determine the direction of movements, the east-west and north-south bands are integrated as well to produce a vector displacement field. This field is simply vector arrows. The lengths of the arrows denote the amount of movements whereas the heads denote the direction of movements. Figure (5) represent the vector displacement field of the study area. The length of the arrows over the dune areas seems 6

Figure 4: The calculated annual migration rates from the east-west and north-south bands of the correlation images. Time periods Minimum (m/yr) Maximum (m/yr) 2011-2012 0.0 26.5 7.1 2012 2013 0.0 24.

7 Figure 4: The calculated annual migration rates from the east-west and north-south bands of the correlation images. Time periods Minimum (m/yr) Maximum (m/yr) Averages (m/yr) longer than those arrows over the inter-dunal areas and the valley floors (Figure 5). The salient contribution of the vector displacement field is the determination of the direction of dune movements. Over the dune areas, the heads of the arrows refer to southeast direction of dune migration. The analysis of wind data extracted from Makkah meteorological data assert the southeast dune migration where the dominant winds are the northerly (Figure 6). 7

8 Figure 5: The calculated vector displacement field form the east-west and north-south displacement bands of the correlation images. 8

9 Wind Frequency (%) N NNE NE ENE ENE ESE SE SSE S SSW SW WSW W WNW NW NNW Figure 6: the frequency of the dominant winds in various directions. CONCLUSION Sand accumulations occupy significant areas of many valley floors around Makkah city. However, these accumulations did not receive scientific attention. This study represent a pioneer one for identifying one of these sand accumulations around Makkah City in addition to the determination of their migration rates and directions. The COSI-Corr technology enabled the ability of using optical remote sensing images such as ASTER images for the purpose of detection and measurements of horizontal dune migrations and directions. Although the technology is capable to provide quantitative measurements of dune migration in meters, the accuracy of the results requires validation through the integration of these results with intensive field works. Given the integration of the COSI- Corr with field works, a potential strategy for studying the dynamic of dune migration around Makkah City could be established. 9

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12 Necsoiu, M., Leprince, S., Hooper, D. M., Dinwiddie, C. L., McGinnis, R. N., Walter, G. R. (2009). Moniktoring migration rates of an active subarctic dune field using optical imagery. Remote Sensing of Environment, 113, Ojeda, J., Vallejo, I., Malvarez, G. C. (2005). Morphometric evolution of the active dunes system of the Doñana National Park, Southern Spain ( ). Journal of Coastal Research, 49, Shehata, W. M., Bader, T., Irtem, O., Ali, A., Abdallah, M. and Aftab, S. (1992) Rate and mode of barchan dunes advance in the central part of the Jafurah sand sea. Journal of Arid Environments, 23: Tsoar, H. (1978). The Dynamics of Longitudinal Dunes. Final Technical Report, European Research Office, U.S. Army, London, 171 pp. Tsoar, H., Blumberg, D. G., Stoler, Y. (2004). Elongation and migration of sand dunes. Geomorphology, 57, Vincent, P.J. (1984) Particle size variation over a transverse dune in the Nafud as Sirr, central Saudi Arabia. Jour. Arid Envir., 7: Vermeesch, P., and Drake, N. (2008). Remotely sensed dune celerity and sand flux measurements of the world's fastest barchans (Bodele, Chad). Geophysical Research Letters, 35, L24404, 6 PP. Wiegand, J.P. (1977). Dune Morphology and Sedimentology at Great Sand Dunes National Monument. M.S. Dissertation, Colorado State University, Fort Collins. Whitney, J. W. (1983). Erosional history and surficial geology of western Saudi Arabia. Technical Report USGS-TR-04-1, Ministry of Petroluem and Mineral Resources, Jeddah, Kingdom of Saudi Arabia. 12

Remote Sensing of Environment

Remote Sensing of Environment 121 (2012) 51 60 Contents lists available at SciVerse ScienceDirect Remote Sensing of Environment journal homepage: www.elsevier.com/locate/rse Retrieving sand dune movements