[Type the document title]
ABDULLA AL-RAWABDEH
PhD candidate, M.Sc, B.Sc
(587) 897 – 8051
A B D U L L A A L - R A W A B D E H
P RO F FE S S I O N A L P O RTF O L I O
1. Resume
2. Publication Abstracts
3. Citation
4. References
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Abdulla Al-Rawabdeh amalrawa@ucalgary. ca
Research Interests:
Natural Hazard Monitoring
Application of Remote Sensing and GIS in Geology;
Application of Remote Sensing and GIS in Environmental Studies.
Water Resources and Environment.
Remote Sensing and GIS applications using UAV.
EDUCATION:
PhD Candidate in Digital Imaging Systems,
Geomatics Department, University of Calgary, Canada
completion 2016
Masters in Science, Water Resources and Environment,
Al-al Bayt University, Jordan. GPA: 89.5, Grade: Excellent
2004-2007
Bachelors in Science, Applied Geology and Environmental Science,
Al-al Bayt University, Jordan. GPA: 78.08, Grade: Very Good.
2000-2004
PROFFESSIONAL EXPERIENCES:
Teaching Assistant
Department of Geomatics Engineering, University of Calgary
Fall 2012, Fall 2013, Fall 2015, ENGG 233: Computing For
Engineers.
Fall 2015, ENGG 200: Design & Communication.
Winter 2015, ENGO 431: Principles of Photogrammetry.
Fall 2014, ENGO 531: Advanced Photogrammetric and
Ranging Techniques.
2011 – at present
Department of Earth and Environmental Sciences, Yarmouk University
Geographic Information Systems and Remote Sensing.
Mineralogy.
Hydroinforamtics
Introduction of Environmental Science.
Surveying
2010 - 2011
Department of Coastal Environment, The University of Jordan / AQABA
Geographic Information Systems and Remote Sensing.
Coastal Management.
Introduction of Environmental Science.
2009 - 2010
GIS Lab Technician Department of Earth & Environmental Sciences, Yarmouk University
2005-2009
Research Assistant Department of Earth & Environmental Sciences, Yarmouk University
2005-2009
Computer Administrator Department of Earth & Environmental Sciences, Yarmouk University
Technical and support assistant maintaining and administering computer
systems.
2005-2009
ADDITIONAL TRAINING:
Teaching Assistant Training Workshop,
SSE TA Training, University of Calgary, Alberta
Sept 2011
Ground Penetrating Radar,
Held at the TECTERA(Geomatics Lab) company by Sensors and Software,
Calgary, AB
Aug 2011
Teaching Assistant Preparedness Workshop,
University of Calgary, Alberta
May 2011
Operation of the Automatic Resistivity System ARES,
GF Instruments Brno, the Czech Republic
July 2009
Applied Groundwater Modeling,
UNESCO-IHE Delft, the Netherlands.
June - July 2008
Geographic Information System (GIS) Introduction in ArcGIS,
Queen Rania Center for Jordanian Studies and Community Services at Yarmouk
University, Jordan
2007
Wastewater Components. Volumes and Composition,
Earth and Environmental Sciences, Al al-Bayt University, Mafraq, Jordan
June 2006
Guidelines for Wastewater Reuse,
Earth and Environmental Sciences, Al al-Bayt University, Mafraq, Jordan
July 2006
Fundamentals of ERDAS Imagine Professional 9.0,
Info Graph. Amman, Jordan
July 2006
Geographic Information System (GIS) Introduction in Arcview 3.2,
Tiberias Cultural Center, Jordan
Aug 2005
SCHOLARSHIPS AND AWARDS:
Full Scholarship to Complete Ph.D. to Study Remote Sensing (Digital
Imaging System).Yarmouk University / Jordan.
Sept 2009 –
Present
Geomatics Department Travel Award, University of Calgary, (800 CAD).
The Schulich Student Activities Fund, University of Calgary, (715 CAD).
Geomatics Department Travel Award, University of Calgary, (800 CAD).
The Schulich Student Activities Fund, University of Calgary, (1000 CAD).
Winter 2013
Winter 2013
Spring 2013
Spring 2013
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Huangqi Sun Memorial Graduate Scholarship, University of Calgary,
Program Recommended Awards, (1800 CAD)
2013
GSC-Student Scholarship, University of Calgary, Program Recommended
Awards, Department of Geomatics Engineering, (2250 CAD)
2013
NUFFIC, to study (Applied Groundwater Modeling) at UNESCO-IHE
Delft, Netherlands.
June - July 2008
Al al-Bayt University, Mafraq- Jordan. Student Award of Non-Cullicular
Activities.
2003
SOFTWARE SKILLS:
Remote Sensing Software (ERDAS Imagine, ENVI, IDRISI, Photoscan, Pix4D, SfM).
ArcGIS (ESRI Arc/Info).
Geophysical surveying (Magnetic / Seismic / Gravity / Resistivity/Radar) Methods.
Groundwater modeling software (Modflow).
Environmental Modelling Software (Rockworks and Surfer).
MATLAB Programing Language.
SOIL AND WATER ANALYTICAL SKILLS:
Water chemical analysis (Spectrophotometer, Atomic Absorption AAS, and titration
analysis).
SEM. Scanning Electron Microscope.
MEMBERSHIPS:
Jordanian Geologists Association Member since 2004. (JGA).
Board Member at Jordanian Geologist Association (JGA) – Irbid Breach, from April
2008 at present
Society of Exploration Geophysicists Global Member.(SEG)
International Association of Hydrological Sciences.( IAHS)
American Society of Photogrammetry and Remote Sensing. (ASPRS).
Canadian Geophysical Union Hydrology Section (CGU).
VOLUNTEER EXPERIENCE
Calgary Youth Science Fair, April 18th, 2015.
APEGA Calgary Science Olympics, February 21, 2015.
18th Annual Geomatics Exposition, University of Calgary, January 29th, 2015.
Co-founder of the Urban Research Network at the University of Calgary (TRUN), 2015.
1st Year special event. Setting up the Low-Coast UAV Quad-Copter to show one of the
Geomatics Tools for Mapping, 2014.
ASPRS 2014 Annual Conference. Geospatial Power in Our Pockets Conference. Louisville,
Kentucky, 23-28 March 2014.
1st Year special event. Setting up the Faro Focus Laser Scanner to show one of the Geomatics
Tools for Indoor Mapping, 2013.
ASPRS 2012 Imaging and Geospatial Technologies -Into the Future Conference. 19-23 March
2012. Sacramento, California.
Reviewer’s member in Journal of Earth Science and Engineering since 2010. The Journal
published monthly in hard copy (ISSN 2159-581X) by David Publishing Company located at
9460 Telstar Ave Suite 5, EL Monte, CA 91731, USA.
JOURNALS, CONFERENCE PAPERS, AND PROJECTS
Al-Rawabdeh, A., He, F., Moussa, A., Habib, A., & El-Sheimy, N., 2015. Using an Unmanned
Aerial Vehicle-Based Digital Imaging System for the Derivation of 3D Point Cloud for Landslide
Scarps Recognition. Remote Sensing. Submitted (accepted January 18, 2015).
Al-Taani, A., Batayneh, A., El-Radaideh, N., Ghrefat, H., Zumlot, T., Al-Rawabdeh, A., Al-
Momani, T., & Taani, A., 2015. Spatial Distribution and Pollution Assessment of Trace Metals in
Surface Sediments of Ziqlab Reservoir, Jordan. Environmental Monitoring and Assessment,
Volume, 187, Issue, 2, pp.1-14.
Al-Rawabdeh, A., Al-Ansari, N., Al-Taani, A., Al-Khateeb, F., & Knutsson, S., 2014. Modeling
the Risk of Groundwater Contamination Using Modified DRASTIC and GIS in Amman-Zerqa
Basin, Jordan. World Applied Sciences Journal, Volume, 15, Issue, 5, pp.264-280.
Al-Rawabdeh, A., Al-Ansari, N., Attya, H., & Knutsson, S., 2014. GIS Applications for Building
3D Campus, Utilities and Implementation Mapping Aspects for University Planning
Purposes. Journal of Civil Engineering and Architecture, Volume, 8, Issue, 5, pp.19-28.
A Gharaibeh, A., J Zakzak, H., & Al-Rawabdeh, A., 2014. Assessing Site Selection of College
Student Housing: Commuting Efficiency across Time. Jordan Journal of Civil Engineering,
Volume, 8, Issue, 3, pp.282-302.
Al-Rawabdeh, A., Al-Ansari, N., Al-Taani, A., Knutson, S., 2013. A GIS-Based DRASTIC
Model for Assessing Aquifer Vulnerability in Amman-Zerqa Groundwater Basin, Jordan.
Scientific Research, Engineering. doi:10.4236/eng.2013. http://www.scirp.org/journal/eng.
Abu Rukah, Y., Rosenand, M., Al-Rawabdeh., A., 2012. Assessment of Metals Pollution in
Urban Road Dusts from Selected Highways of the Greater Toronto Area in Canada.
Environmental Monitoring and Assessment, ISSN: 1573-2959.
Al-Taani, A., Batayneh, A., El-Radaideh, N., Al-Momani., I and Al-Rawabdeh, A., 2012.
Monitoring of selenium concentrations in major springs of Yarmouk Basin, north Jordan. World
Applied Sciences Journal 18 (5): 704-714.
R. Jaradat, M. Awawdeh, Y. Fahjan, M.Qaryouti, O.Nuseir, and Al -Rawabdeh, A. 2008.
Deaggregation of probabilistic Ground Motion for Selected Jordanian Cities. Jordan Journal of
Civil Engineering vol 2. No.2172-196.
Al-Rawabdeh, A., Moussa, A., Habib, A., & El-Sheimy, N., 2015. Derivation of 3D Point Cloud
Using UAV-Based Digital Imaging System for Detecting and Identifying Landslide
Scars. ASPRS 2015 Annual Conference. Tampa, Florida, May 4-8, 2015.
He, F., A. Habib, and A. Al-Rawabdeh. 2015. “Planar Constraints For An Improved UAV-Image-
Based Dense Point Cloud Generation.” Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.
XL-1/W4 (August): 269–74. doi:10.5194/isprsarchives-XL-1-W4-269-2015.
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Lari, Z., A. Al-Rawabdeh, F. He, A. Habib, and N. El-Sheimy. 2015. “Region-Based 3d Surface
Reconstruction Using Images Acquired By Low-Cost Unmanned Aerial Systems.” Int. Arch.
Photogramm. Remote Sens. Spatial Inf. Sci. XL-1/W4 (August): 167–73.
doi:10.5194/isprsarchives-XL-1-W4-167-2015.
Al-Rawabdeh, A., Habib, A., 2015. Close Range Sensing Techniques for Natural Hazard
Detecting and Assessment. University of Innsbruck - Summer ISPRS program, Obergurgl,
Austria, July 5-11 2015.(Poster).
Al-Rawabdeh, A., Habib, A., & He, F., 2014. Multi-Sensory Data Integration for Extracting
Geotechnical Parameters for Landslides Hazard Assessment. ASPRS 2014 Annual Conference,
Louisville, Kentucky. March 23-28, 2014. (12pages).
Attya, H., Al-Rawabdeh, A., & Habib, A., 2014. Proposed Algorithm for Automatic Cleaning of
Terrestrial LiDAR Data. ASPRS 2014 Annual Conference. Louisville, Kentucky. March 23-28,
2014.
Al-Rawabdeh, A., Habib, A., & Attya, H., 2013. Terrestrial Laser Scanning and Discontinuity
Plane Characterization for Landslide Hazard Assessment. ASPRS 2013 Annual Conference.
Baltimore, Maryland. March 24-28, 2013. (10pages).
Al-Rawabdeh, A., Habib, A., Attya, H., & Lari, Z., 2013. Using Automatic Object Detection in
Rainwater Harvesting Assessment for a Small Size Urban Area. IAHS-IAPSO-IASPEI Joint
Assembly, Gothenburg, Sweden, July 22-26 2013.
Attya, H., Habib, A., Detchev, I., Al-Rawabdeh, A., 2012. Crowd Volume Estimation Using
Photogrammetric Techniques. ASPRS 2012 Annual Conference. Sacramento, California. March
19-23, 2012. (5pages).
R. Jaradat, M. Awawdeh, Y. Fahjan, A.Diabat, M.Qaryouti, O.Nuseir, and A. Al -Rawabdeh,
2008. Earthquake Risk Assessment of Greater Amman Municipality. Technical Report submitted
to the UNDP, Amman, 489pp.
Assessment of Metal Pollution In Urban Road Dusts From Selected Highways of The Greater
Toronto Area In Canada
Authors: Y Nazzal, Marc A Rosen, Abdulla M Al-Rawabdeh Publication date: 2013/2/1 Journal: Environmental monitoring and assessment Volume: 185 Issue: 2 Pages: 1847-1858 Publisher: Springer Netherlands
Abstract
Over the last several decades, there has been increased attention on the heavy metal contamination
associated with highways because of the associated health hazards and risks. Here, the results are
reported of an analysis of the content of metals in roadside dust samples of selected major highways in
the Greater Toronto Area of Ontario, Canada. The metals analysed are lead (Pb), zinc (Zn), cadmium
(Cd), nickel (Ni), chromium (Cr), copper (Cu), manganese (Mn), calcium (Ca), potassium (K),
magnesium (Mg) and iron (Fe). In the samples collected, the recorded mean concentrations (in parts per
million) are as follows: Cd (0.51), Cu (162), Fe (40,052), Cr (197.9), K (9647.6), Mg (577.4), Ca
(102,349), Zn (200.3), Mn (1202.2), Pb (182.8) and Ni (58.8). The mean concentrations for the analysed
samples in the study area are almost all higher than the average natural background values for the
corresponding metals. The geo-accumulation index of these metals in the roadside dust under study
indicates that they are not contaminated with Cr, Mn and Ca; moderately contaminate with Cd and K;
strongly contaminated with Fe and Mg; strongly to extremely contaminate with Ni and Pb; and
extremely contaminated with Cu and Zn. The pollution load index (PLI) is used to relate pollution to
highway conditions, and the results show that PLI values are slightly low at different samples collected
from Highways 401 and 404 and high in many samples collected from Highway 400 and the Don Valley
Parkway. Highway 400 exhibits the highest PLI values.
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A GIS-Based Drastic Model for Assessing Aquifer Vulnerability in Amman-Zerqa Groundwater
Basin, Jordan
Authors: Abdulla M Al-Rawabdeh, Nadhir A Al-Ansari, Ahmed A Al-Taani, Sven Knutsson Publication date: 2013/5/23 Volume: 2013 Publisher: Scientific Research Publishing
Abstract
Amman-Zerqa Basin (AZB) is a major basin in Jordan. The concentration of economic, agricultural and
social activities within the basin makes it of prime importance to Jordan. Intensive agricultural practices
are widespread and located close to groundwater wells, which pose imminent threats to these resources.
Groundwater contamination is of particular concern as groundwater resources are the principal source of
water for irrigation, drinking and industrial activities. A DRASTIC model integrated with GIS tool has
been used to evaluate the groundwater vulnerability of AZB. The Drastic index map showed that only
1.2% of the basin’s total area of 3792 km2 lies in the no vulnerable zone and about 69% is classified as
having low pollution potential. The results also revealed that about 30% of the catchment area is
moderately susceptible to pollution potential and slightly 1% is potentially under high pollution risk.
These results suggest that almost one third of the AZB is at moderate risk of pollution potential. These
areas are mainly in the north-east and central parts of the basin where the physical factors (gentle slope
and high water table) would allow more contaminants to easily move into the shallow groundwater
aquifer. Areas with high vulnerability to pollution are largely located in the center of Amman old city.
Monitoring of Selenium Concentrations in Major Springs of Yarmouk Basin, North Jordan
Authors: Ahmed A Al-Taani, Awni Batayneh, Nazem El-Radaideh, Idrees Al-Momani, Abdullah Rawabdeh Publication date: 2012 Journal: World Applied Sciences Journal Volume: 18 Issue: 5 Pages: 704-714
Abstract
This is the first study to survey selenium levels in spring water of Yarmouk Basin north of Jordan.
Elevated selenium levels in spring waters have been observed indicating that selenium contamination is
widespread. In almost all of the spring water samples, selenium concentrations exceeded the maximum
allowable level based on the Jordan and World Health Organization for drinking water quality
guidelines of 10 µg/L. Evaluation of seasonal patterns in the concentrations of selenium showed higher
concentration in dry weather season. Preliminary assessment of the potential sources and factors
contributing to selenium contents of water has been reviewed. Adverse health risk assessment of
selenium exposure among residents consuming water from springs was estimated. The estimated
average daily dose and the noncarcinogenic hazard quotient values from selenium exposure were below
the threshold of concern for adverse health effects.
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Modeling the risk of groundwater contamination using modified DRASTIC and GIS in Amman-
Zerqa Basin, Jordan
Authors: Abdulla Al-Rawabdeh, Nadhir Al-Ansari, Ahmed Al-Taani, Fadi Al-Khateeb, Sven Knutsson Publication date: 2014/9/1 Journal: Open Engineering Volume: 4 Issue: 3 Pages: 264-280
Abstract
Amman-Zerqa Basin (AZB) is the second largest groundwater basin in Jordan with the highest abstraction rate,
where more than 28% of total abstractions in Jordan come from this basin. In view of the extensive reliance on
this basin, contamination of AZB groundwater became an alarming issue. This paper develops a Modified
DRASTIC model by combining the generic DRASTIC model with land use activities and lineament density for
the study area with a new model map that evaluates pollution potential of groundwater resources in AZB to
various types of pollution. It involves the comparison of modified DRASTIC model that integrates nitrate loading
along with other DRASTIC parameters. In addition, parameters to account for differences in land use and
lineaments density were added to the DRASTIC model to reflect their influences on groundwater pollution
potential. The DRASTIC model showed only 0.08% (3 km2) of the AZB is situated in the high vulnerability area
and about 30% of the basin is located in the moderately vulnerable zone (mainly in central basin). After
modifying the DRASTIC to account for lineament density, about 87% of the area was classified as having low
pollution potential and no vulnerability class accounts for about 5.01% of the AZB area. The moderately
susceptible zone covers 7.83% of the basin’s total area and the high vulnerability area constitutes 0.13%. The
vulnerability map based on land use revealed that about 71% of the study area has low pollution potential and no
vulnerability area accounts for about 0.55%, whereas moderate pollution potential zone covers an area of 28.35%
and the high vulnerability class constitutes 0.11% of AZB. The final DRASTIC model which combined all
DRASTIC models shows that slightly more than 89% of the study area falls under low pollution risk and about
6% is considered areas with no vulnerability. The moderate pollution risk potential covers an area of about 4% of
AZB and the high vulnerability class constitutes 0.21% of the basin. The results also showed that an area of about
1761 km2 of bare soils is of low vulnerability, whereas about 28 km2 is moderately vulnerable. For agriculture
and the urban sector, approximately 1472 km2 are located within the low vulnerability zone and about 144 km2
are moderately vulnerable, which together account for about 8% of the total agriculture and urban area. These
areas are contaminated with human activities, particularly from the agriculture. Management of land use must be
considered when changing human or agricultural activity patterns in the study area, to reduce groundwater
vulnerability in the basin. The results also showed that the wells with the highest nitrate levels (81–107 mg/l)
were located in high vulnerable areas and are attributed to leakage from old sewage water.
Spatial distribution and pollution assessment of trace metals in surface sediments of Ziqlab
Reservoir, Jordan
Authors: Ahmed A Al-Taani, Awni T Batayneh, Nazem El-Radaideh, Habes Ghrefat, Taisser Zumlot, Abdulla M Al-Rawabdeh, Talal Al-Momani, Aymen Taani Publication date: 2015/2/1 Journal: Environmental monitoring and assessment Volume: 187 Issue: 2 Pages: 1-14 Publisher: Springer International Publishing
Abstract
Surface sediment samples were collected from Ziqlab dam in northwestern Jordan to investigate the
spatial distribution of selected trace metals and assess their pollution levels. The results showed that the
concentrations of Pb, Cd, and Zn exceeded the environmental background values. Cd, Ni, and Cr
contents were higher than the threshold effect level (TEL) in 63, 83, and 60 % of the reservoir
sediments, respectively; whereas Pb, Zn, and Cu were less than the TEL limit. The concentrations of
trace metals in reservoir sediment varied spatially, but their variations showed similar trends. Elevated
levels of metals observed in the western part (adjacent to the dam wall) were coincided with higher
contents of clay-silt fraction and total organic matters. Multivariate analysis indicated that Pb, Co, and
Mn may be related to the lithologic component and/or the application of agrochemicals in the upstream
agricultural farms. However, Cd and Zn concentrations were probably elevated due to inputs from
agricultural sources, including fertilizers. Evaluation of contamination levels by the Sediment Quality
Guidelines of the US-EPA, revealed that sediments were non-polluted to moderately polluted with Pb,
Cu, Zn, and Cr, but non-polluted to moderately to heavily polluted with Ni and non-polluted with Mn.
The geoaccumulation index showed that Ziqlab sediments were unpolluted with Pb, Cu, Zn, Ni, Cr, Co,
and Mn, but unpolluted to moderately polluted with Cd. The high enrichment values for Cd and Pb (>2)
indicate their anthropogenic sources, whereas the remaining elements were of natural origins consistent
with their low enrichment levels.
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GIS Applications for Building 3D Campus, Utilities and Implementation Mapping Aspects for
University Planning Purposes
Authors: Abdulla Al-Rawabdeh, Nadhir Al-Ansari, Hussain Attya, Sven Knutsson Publication date: 2014/2/11 Journal: Journal of Civil Engineering and Architecture Volume: 2 Pages: 3
Abstract
In city planning managing, the third dimension is becoming a necessity. Using 3D GIS modeling offers
a flexible interactive system while providing one of the best visual interpretation of data which supports
planning and decision processes for city planners. As a result, 3D GIS model expresses terrain features
in an intuitive way which enhances the management and analysis of a proposed project through 3D
visualization. This paper discusses the concept of 3D GIS modeling techniques using a simple procedure
to generate a university campus model (real 3D GIS model) which will show the effectiveness of this
approach. The 3D GIS model provides access to mapping data to support planning, design and data
management. Intelligent GIS models and GIS tools help community planning and apply regional and
discipline-specific standards. Integration of GIS spatial data with campus organization helps to improve
quality, productivity and asset management. The following study built 3D GIS map and all utility
information for Al al-Bayt University campus as an example. The primary objective is to improve data
management (e.g., maps, plans, usage of facilities and services) and to develop methods using 3D spatial
analysis for specific applications at the university.
Assessing Site Selection of College Student Housing: Commuting Efficiency across Time
Authors: A Gharaibeh, A., J Zakzak, H, & Al-Rawabdeh Publication date: 2014 Journal: Jordan Journal of Civil Engineering Volume: 8 Issue: 3
Abstract
Universities around the world are promoting walking for their students because it provides many health
and environmental benefits at the personal as well as the community level. This paper aims to help
universities, city planners and housing investors in the process of efficient site selection for future
student housing projects, by analyzing off-campus students’ commuting habits and travel time
preferences to and from the university campuses. An online survey is operated to collect responses of
students (n= 527) from two Jordanian universities located within the city of Irbid (N-Jordan). Results
indicate that the mean value for students’ longest preferred one-way walking duration is 17.04± 8.25
minutes for the whole sample. A statistically significant negative correlation is found between students’
longest preferred one-way walking duration and age. The percentage of students who would accept this
duration was represented in a formula in order to calculate the accumulated walking potential of varied
sites around university campuses. The paper presented a local scenario using GIS mapping where this
process was implemented to evaluate prospect vacant sites' walking potential around Yarmouk
University, Irbid, Jordan.
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Deaggregation of Probabilistic Ground Motions for Selected Jordanian Cities Authors: Rasheed A Jaradat, Osama K Nusier, Muheeb M Awawdeh, Mahmoud Y Al-Qaryouti, Yasin M Fahjan Publication date: 2008 Journal: Jordan Journal of Civil Engineering Volume: 2 Issue: 2
Abstract
Probabilistic Seismic Hazard Analysis (PSHA) approach was adopted to investigate seismic hazard
distribution across Jordan. Potential sources of seismic activities in the region were identified, and their
earthquake recurrence relationships were developed from instrumental and historical data. Maps of peak
ground acceleration and spectral accelerations (T=0.2 and T=1.0 sec.) of 2% and 10% probability of
exceedance in 50 years were developed. This study deaggregated the PSHA results of 2% and 10%
probability of exceedance in 50 years results of twelve Jordanian cities to help understand the relative
control of these sources in terms of distances and magnitudes. Results indicated that seismic hazard
across these cities is mainly controlled by area sources located along the Dead Sea Transform (DST)
fault system. Cities located at short distances from the DST tend to show close deaggregation behavior.
Some discrepancies may exist due to the proximity or remoteness of these cities relative to the DST
seismic sources and local seismicity. The modal or most probable distance distribution indicated that the
distance to the earthquake which contributes most to the hazard at each city is mainly controlled by
shaking along faults associated with near seismic area sources. The influence of adjacent seismic
sources to the seismic hazard of each city is more evident for the long period spectral acceleration.
Distant sources, such as the eastern Mediterranean, Cyprus, Suez and the southern region of the Gulf of
Aqaba are relatively low, but can not be neglected due to the intrinsic uncertainties and incomplete
seismic data.
Using an Unmanned Aerial Vehicle-Based Digital Imaging System to Derive A 3D Point Cloud for
Landslide Scarp Recognition
Authors: Abdulla Al-Rawabdeh, Fanging He, Adel Mousaa, Ayman Habib, and Naser El-Sheimy Publication date: 2016 Journal: Remote sensing, earth observation for geo-hazard Volume: 7 Issue: 2
Abstract
Landslides often cause economic losses, property damage, and loss of lives. Monitoring landslides using
high spatial and temporal resolution imagery and the ability to quickly identify landslide regions are the
basis for emergency disaster management. This study presents a comprehensive system that uses
unmanned aerial vehicles (UAVs) and Semi-Global dense Matching (SGM) techniques to identify and
extract landslide scarp data. The selected study area is located along a major highway in a mountainous
region in Jordan, and contains creeping landslides induced by heavy rainfall. Field observations across
the slope body and a deformation analysis along the highway and existing gabions indicate that the slope
is active and that scarp features across the slope will continue to open and develop new tension crack
features, leading to the downward movement of rocks. The identification of landslide scarps in this
study was performed via a dense 3D point cloud of topographic information generated from high-
resolution images captured using a low-cost UAV and a target-based camera calibration procedure for a
low-cost large-field-of-view camera. An automated approach was used to accurately detect and extract
the landslide head scarps based on geomorphological factors: the ratio of normalized Eigenvalues (i.e.,
λ1/λ2 ≥ λ3) derived using principal component analysis, topographic surface roughness index values,
and local-neighborhood slope measurements from the 3D image-based point cloud. Validation of the
results was performed using root mean square error analysis and a confusion (error) matrix between
manually digitized landslide scarps and the automated approaches. The experimental results using the
fully automated 3D point-based analysis algorithms show that these approaches can effectively
distinguish landslide scarps. The proposed algorithms can accurately identify and extract landslide
scarps with centimeter-scale accuracy. In addition, the combination of UAV-based imagery, 3D scene
reconstruction, and landslide scarp recognition/extraction algorithms can provide flexible and effective
tool for monitoring landslide scarps and is acceptable for landslide mapping purposes.
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Using Automatic Object Detection in Rainwater Harvesting Assessment for a Small Size Urban
Area Authors: Zahra Lari Al-Rawabdeh, A., Habib, A., Attya, H. Publication date: 2013/6 Conference: IAHS-IAPSO-IASPEI Joint Assembly, Gothenburg Sweden
Abstract
Water resources are essential for economic development, agricultural productivity, industrial growth and
above all human well-being in every community. The availability of a clean, safe and secure water
resource has always been a major concern for human populations. Rainwater harvesting (RWH) is
defined as the methods for collecting and storing rainwater in reservoirs such tanks, ponds or dams.
RWH also reduces urban flooding and prevents runoff from going into sewer systems. Therefore, these
techniques reduce loads of treatment plants. RWH from rooftops, roads, and parking can increase the
water supply for various applications and help to compensate the chronic water shortage in many parts
of the world. The applicability of RWH as a possible and inexpensive alternative to more traditional
water resources has been discussed in many research works, in the past few years. Nowadays, LiDAR
systems have been recognized as an efficient technology for the generation of high resolution digital
surface models of any study area. This research evaluates the potential of using rainwater for potable
and non-potable water savings in a specific case study and provides recommendations for increasing the
efficient water usage by minimizing water waste and deflates water bills. This paper utilizes a new
processing approach to classify the LiDAR data into which belong to ground and non-ground surfaces.
The non-ground points are then categorized into planer surfaces such as building rooftops to exclude the
non-planer objects such as trees using a parameter-domain segmentation approach. The ground points
have been classified into planar surfaces mostly represent roads and parking, and non-planar surfaces
represent the bare earth. It is assumed that building rooftops, roads, and parking lots are the main
rainwater reservoirs in urban areas. Therefore, the area of these objects’ surfaces are calculated using the
derived planes’ parameters from the segmentation process of the LiDAR data.
Terrestrial Laser Scanning and Discontinuity Plane Characterization for Landslide Hazard
Assessment Authors: H Al-Rawabdeh, A., Habib, A., Attya Publication date: 2013/3/24 Conference: ASPRS 2013 Annual Conference. Baltimore, Maryland
Abstract
In many parts of the world, especially in mountainous regions, landslides are common, and they often
have hazardous consequences for almost all of the construction activities and human lives. Landslides
can be rapid or slow, and can occur in a wide variety of geologic environments. The movement of earth
material along slopes can take the form of rock falls, earth flows, mud flows, and subsidence. Some of
these movements are related to natural processes. In this paper, the potential use of terrestrial laser
scanning for landslide monitoring and geological parameter extraction is investigated. Also, we
investigate the possible use of terrestrial laser scanning to derive quantitative measurements associated
with discontinuity planes, which are crucial factors leading to a landslide. We provide a brief overview
of landslides, their impact, and current measurement and prediction techniques. The majority of the
work focuses on the use of terrestrial laser scanning data for deriving the strike and dip measurements of
the discontinuity planes using different data processing techniques. The validity of the derived quantities
is validated using field measurements.
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Crowd Volume Estimation Using Photogrammetric Techniques Authors: 14. Attya, H., Habib, A., Detchev, I., Al-Rawabdeh Publication date: 2012/3/23 Conference: ASPRS 2012 Annual Conference. Sacramento, California.
Abstract
Incidents caused by human crowds could occur in various venues and under different circumstances, the
most common being sport events, festivals, and religious events. Starting as early as the nineteenth
century, research efforts have been geared towards crowd behaviour monitoring strategies especially in
the fields of emergency and safety management. Attempts have been made also as recent as the mid and
late nineties of the last century to use computer graphics in crowd modeling and simulation. Although
crowd simulation is widely applied in several fields, research related to the derivation of quantitative
crowd information is quite limited and is mainly focused on crowd volume using image processing and
computer vision techniques. There were some attempts in the last two decades of the twentieth century
to employ real time close-range photogrammetry in pedestrian detection and counting. However, these
methods are hardly being used in high-density crowd monitoring because of the extreme difficulty in
individual detection and tracking under these conditions. This paper provides a conceptual framework
for the utilization of close-range photogrammetry to estimate crowd volume using a low-cost digital
camera. The framework starts by developing a three dimensional model of the site in question prior to its
observation in the presence of a crowd. This model will be used later to geo-reference the collected
images from a dynamic camera system. The 3D model together with the geo-referencing parameters of
the collected imagery will be finally used to derive crowd volume parameters. Preliminary results of the
developed system will be illustrated together with the plans for the implementation of the proposed
framework.
Planar Constraints for an Improved UAV-image-based Dense Point Cloud Generation
Authors: F. He, A. Habib, A. Al-Rawabdeh Publication date: 2015/8 Conference: ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Volume: XL-1/W4, 2015 Pages: pp.269-274
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences,
Volume XL-1/W4, 2015 International Conference on Unmanned Aerial Vehicles in Geomatics, 30 Aug–02
Sep 2015, Toronto, Canada.
Abstract
In this paper, we proposed a new refinement procedure for the semi-global dense image matching. In
order to remove outliers and improve the disparity image derived from the semi-global algorithm, both
the local smoothness constraint and point cloud segments are utilized. Compared with current
refinement technique, which usually assumes the correspondences between planar surfaces and 2D
image segments, our proposed approach can effectively deal with object with both planar and curved
surfaces. Meanwhile, since 3D point clouds contain more precise geometric information regarding to the
reconstructed objects, the planar surfaces identified in our approach can be more accurate. In order to
illustrate the feasibility of our approach, several experimental tests are conducted on both Middlebury
test and real UAV-image datasets. The results demonstrate that our approach has a good performance on
improving the quality of the derived dense image-based point cloud.
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Region-Based 3d Surface Reconstruction Using Images Acquired By Low-Cost Unmanned Aerial
Systems Authors: Z Lari, A Al-Rawabdeh, F He, A Habib, N El-Sheimy Publication date: 2015/8 Journal: ISPRS-International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Volume: 1 Pages: 167-173
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences,
Volume XL-1/W4, 2015 International Conference on Unmanned Aerial Vehicles in Geomatics, 30 Aug–02
Sep 2015, Toronto, Canada.
Abstract
Accurate 3D surface reconstruction of our environment has become essential for an unlimited number of
emerging applications. In the past few years, Unmanned Aerial Systems (UAS) are evolving as low-cost
and flexible platforms for geospatial data collection that could meet the needs of aforementioned
application and overcome limitations of traditional airborne and terrestrial mobile mapping systems.
Due to their payload restrictions, these systems usually include consumer-grade imaging and positioning
sensor which will negatively impact the quality of the collected geospatial data and reconstructed
surfaces. Therefore, new surface reconstruction surfaces are needed to mitigate the impact of using low-
cost sensors on the final products. To date, different approaches have been proposed to for 3D surface
construction using overlapping images collected by imaging sensor mounted on moving platforms. In
these approaches, 3D surfaces are mainly reconstructed based on dense matching techniques. However,
generated 3D point clouds might not accurately represent the scanned surfaces due to point density
variations and edge preservation problems. In order to resolve these problems, a new region-based 3D
surface reconstruction technique is introduced in this paper. This approach aims to generate a 3D photo-
realistic model of individually scanned surfaces within the captured images. This approach is initiated
by a Semi-Global dense Matching procedure is carried out to generate a 3D point cloud from the
scanned area within the collected images. The generated point cloud is then segmented to extract
individual planar surfaces. Finally, a novel region-based texturing technique is implemented for
photorealistic reconstruction of the extracted planar surfaces. Experimental results using images
collected by a camera mounted on a low-cost UAS demonstrate the feasibility of the proposed approach
for photorealistic 3D surface reconstruction.
Proposed Algorithm for Automatic Cleaning of Terrestrial LiDAR Data Authors: A. Habib & A. Al-Rawabdeh. H. Attya Publication date: 2014/3/23 Conference: ASPRS 2014 Annual Conference. Louisville, Kentucky
Abstract
Terrestrial laser scanners have become one of the popular surveying equipment nowadays because of
their strong capabilities to collect huge amount of accurate data very quickly. Decreasing cost is one of
the other factors that help increasing the popularity of terrestrial laser scanners as surveying equipment.
Their use is spanning a wide spectrum of applications ranging from precise deformation measurements
to buildings three-dimensional modeling and heritage documentation. Usually urban LiDAR scenes
include plenty of unwanted features that occlude the objects of interest such as trees, parked cars,
pedestrian, banners to name a few. However dealing with laser scanning data (LiDAR) is not as trivial
as dealing with total stations data because of the vast number of points measured by laser scanners and
the irregularity of those points and the fact that urban LiDAR scenes include plenty of unwanted features
that occlude the objects of interest such as trees, parked cars, pedestrian, banners to name a few. These
three properties of LiDAR data cause dramatic increase of the computation cost which amplified by the
increase in the complexity of the scene. Knowing that the unwanted occluding features represent
considerable part of the collected data means that removing them could save considerable amount of the
computation cost as well as enhancing the reliability of the data processing. This task is usually carried
out manually by cropping the occluding objects using visualization software. However, this manual
approach increases the processing time of projects and labour cost. This paper suggests an algorithm to
remove the occluding objects automatically as a pre-processing step before segmenting the LiDAR data
and extracting the required information. The algorithm starts by assigning identification number to each
point in order to keep the sequence of the points. Then ground/non-ground filtering, using histogram
values of the Z-coordinate, is implemented to remove the ground. After removing the ground, the range
at each point is calculated and compared for successive points. The algorithm is based on the assumption
that the range difference between successive points is very small. Therefore when a sudden large
difference is detected, a possible occluding object could be exist. Deciding upon whether the detected
object is an occluding object or part of the object of interest is based on certain thresholds which could
be determined by prior information about the building complexity. Experimental results show that most
of the occluding objects is removed which led to considerable decrease in the computation time for
successive processing steps. The proposed algorithm could save plenty of time and labour cost for large
projects when huge amount of data is collected.
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Multi-Sensory Data Integration for Extracting Geotechnical Parameters for Landslides Hazard
Assessment Authors: Abdulla Al-Rawabdeh, Ayman Habib, Fangning He Publication date: 2014
Abstract
Geotechnical engineering is a relatively new discipline that has developed rapidly over the past 30 years.
It deals with a wide spectrum of natural geological materials ranging from low strength soils to high
strength rocks. Earth movements are common in many parts of the world and, as a result, present serious
safety and mortality risk to humans in addition to affecting construction activities. Earth movement can
be classified into different categories with landslides as being one of those categories. In order to assess
the stability of landslides, different geo-technical parameters are required such as the strike and dip of
the discontinuity planes in the potential area. Areas affected by landslides are often inaccessible which
makes manual compass and inclinometer measurements challenging because of the danger involved in
this operation. Preventing large natural landslides is difficult; however some mitigation is possible and
can help to minimize the hazards. Nowadays, 3D modeling of objects can be achieved through either
passive or active remote sensing systems. Active sensors, such as Terrestrial Laser Scanning systems
(TLS) have been used extensively for quick acquisition of highly accurate three-dimensional point cloud
data with high resolution. However, the TLS in some cases has limitations during the data collection due
to occlusions, orientation bias and truncation. This research addresses those issues by investigating the
possibility of augmenting TLS in the occluded regions through close-range photogrammetry to generate
high resolution and dense point cloud using the Semi-Global Matching (SGM) algorithm. By
augmenting the two data acquisition methods and registering to a common coordinate system to provide
a complete point cloud for the area of interest, any limitations and exposed gaps in the data are filled.
Planar segmentation is then carried out to extract the required geotechnical parameters automatically.
Four sets of geotechnical parameters have been compared in this research: 1) a set of manual
measurements, 2) a set extracted from the TLS data only, 3) a set extracted from the SGM algorithm
only, 4) and finally a set extracted from the fused TLS and SGM data. The results showed that the data
fusion method provided more accurate results when compared to the results coming from the TLS data
and those coming from SGM only. This reveals that the impact of the occluded regions on the
calculations of the geotechnical parameters must be considered to achieve the required quality of the
estimation process. The proposed method of this research provided high quality measurements for the
geotechnical parameters required to assess the landslide hazard, ensured safety, and saved cost and time.
A Robust Registration Algorithm for Time Series UAV-Image-Based Point Clouds for Change
Detection
Authors: Abdulla Al-Rawabdeh, Hussein Al-Gurrani, Kaleel Al-Durgham, Ivan Detchev, Naser El-Sheimy, and Ayman Habib Publication date: June 2016 Conference: ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Volume: ICWG I/Vb, 2016
ABSTRACT:
Landslides are among the major threats to urban landscape and manmade infrastructure. They often
cause economic losses, property damage, and loss of lives. Temporal monitoring data of landslides from
different epochs empowers the evaluation of landslide progression. Alignment of overlapping surfaces
from two or more epochs is crucial for the analysis of landslide dynamics. The traditional methods for
point-cloud-based landslide monitoring rely on using a variation of the Iterative Closest Point (ICP)
registration procedure to align any reconstructed surfaces from different epochs to a common reference
frame. However, sometimes the ICP-based registration can fail or may not provide sufficient accuracy.
For example, point clouds from different epochs might fit to local minima due to lack of geometrical
constraints. Also, manual interaction is required to exclude any non-stable areas from the registration
process. In this paper, a robust image-based registration method is introduced for the simultaneous
evaluation of all registration parameters. This includes the Interior Orientation Parameters (IOPs) of the
camera and the Exterior Orientation Parameters (EOPs) of the involved images from all available
observation epochs via a bundle block adjustment with self-calibration. Next, a semi-global dense
matching technique is implemented to generate dense 3D point clouds for each epoch using the images
captured in a particular epoch separately. The normal distances between any two consecutive point
clouds can then be readily computed, because the point clouds are already effectively co-registered. A
low-cost DJI Phantom II Unmanned Aerial Vehicle (UAV) was customised and used in this research for
temporal data collection over an active soil creep area in Lethbridge, Alberta, Canada. The
customisation included adding a GPS logger and an off-the-shelf Large-Field-Of-View (LFOV) digital
camera which facilitated capturing high-resolution geo-tagged images in two epochs over the period of
one year (i.e., May 2014 and May 2015). Note that due to the course accuracy of the on-board GPS
receiver (e.g., +/- 5-10 m) the geo-tagged positions of the images were only used as initial values in the
bundle block adjustment. Normal distances, signifying detected changes, varying from 20 cm to 4 m
were identified between the two epochs. The accuracy of the co-registered surfaces was estimated by
comparing non-active patches within the monitored area of interest. Since these non-active sub-areas are
stationary, the computed normal distances should theoretically be close to zero. The quality control of
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the registration results showed that the average normal distance was 3 cm, which is within the noise
level of the reconstructed surfaces. Further validation of the alignment of the 3D reconstruction surfaces
was carried out through a check point analysis using signalized targets, which were placed in the
monitored area. The root mean squared error (RMSE) was 4.6 cm and 5.7 cm in the horizontal and
vertical directions, respectively.
Earthquake Risk Assessment of Greater Amman Municipality Authors: R. Jaradat, M. Awawdeh, Y. Fahjan, A.Diabat, M Publication date: 2008 Pages: 489 Publisher: Technical Report submitted to the UNDP, Amman, under Atlas no. 51485.
This final report is written in accordance with Atlas no. 51485 – Support to Building National Capacities for Earthquake Risk Reduction at Greater Amman Municipality in Jordan and the agreement signed between the United Nations Development Programme and Yarmouk University represented by Queen Rania Center for Jordanian Studies and Community Services in order to perform consulting services in respect of “The Earthquake Risk Assessment of Greater Amman Municipality".
Abstract
The main objective of the project is to support the Disaster Risk Management Master Plan (DRMMP)
Framework of the Greater Amman Municipality (GAM) with a comprehensive seismic risk assessment
with which will build a competent DRM practice and will improve the City’s resilience to earthquakes
and other hazards and protects its physical and socio-economic assets and investments. The project was
funded by the United Nations Development Programme-Amman (UNDP) for the General Directorate
for Civil Defense (GDCD). This study included the undertaking of both a probabilistic risk analysis as
well as deterministic risk analyses considering three separate plausible earthquake scenarios1. This
study is the first of its kind for the Greater Amman area. It provides a wealth of information of hazards,
vulnerability and risk that are extremely pertinent to the management of risk and the reduction of
physical vulnerability to GAM and the protection of its physical and human assets. Three different
earthquake scenarios were identified and used for seismic risk assessment in terms of physical building
damage, fatalitiesm and subsequent monetary losses.
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Quick look analysis of hazard and risk assessment associated with high density urban
communities: A Case Study from El-Hussein Refugee Camp, Amman-Jordan
Authors: Rasheed Jaradat, Muheeb Awawdeh, Abdulla Al-Rawabdeh Publication date: June 2009 Report Submitted to Swiss Agency for Development and Cooperation-SDC Amman-Jordan This report is written in accordance with the agreement signed between the Swiss Agency for Development and Cooperation (SDC) and Innovative Studies and Research (ISAR) in order to perform consulting services in respect of “Disaster Risk Reduction Programme”. The agreement signed by 17 March 2009 has been concluded based on the ISAR proposal for SDC.
Abstract
This report presents the results of a study implemented according to the project “Quick look analysis of
hazard and risk assessment associated with high density urban communities: a case study from El-
Hussein Refugee Camp, Amman-Jordan”. The Department of Palestinian Affairs (DPA) in Amman is
the beneficiary of this project as it oversees the Palestinian camps in Jordan. This report presents the
results of a study implemented according to the project “Quick look analysis of hazard and risk
assessment associated with high density urban communities: a case study from El-Hussein Refugee
Camp, Amman-Jordan”. The Department of Palestinian Affairs (DPA) in Amman is the beneficiary of
this project as it oversees the Palestinian camps in Jordan.
Characterizing Oil Shale Deposits at Attarat Um Ghudran, Central Jordan, Using Electrical
Resistivity Tomography (ERT)
Authors: Rasheed Jaradat, Abdulla Al-Rawabdeh Publication date: June 2011
Abstract
This study comes in support of current exploration activities of the Jordan Oil Shale Energy Co. at the
Attarat Umm Ghudran concession area. It aims at characterizing Oil Shale deposits between
drilled/planned boreholes, in an attempt to investigate possible continuities, and truncations of Oil Shale
and the overburden masses, using Electrical Resistivity Tomography method.
Accordingly, the basic objective of the present study is to characterize Oil Shale deposits within a
selected area of interest at the Attarat Umm Ghudran concession region using Electrical Resistivity
Tomography (ERT). It is aimed that, using appropriate electrode array, the ERT method, will provide a
clear picture about the characteristics of oil shale deposits in terms of continuity, possible truncations,
existing fault structures, and overlaying overburden material.
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CITATIONS:
https://scholar.google.ca/citations?user=JtfgfMYAAAAJ&hl=en
REFERENCES:
Prof Dr. Ayman Habib Professor at Civil Engineering Department, Purdue University, USA.
Mobile Number: + (765) 496-0173
E-mail Address: [email protected]
Prof Dr. Naser El-Sheimy Professor at Geomatics Engineering, Sweden, University of Calgary, Canada, AB.
Mobile Number: + (403) 220-7587
E-mail Address: [email protected]
Prof Dr. Nadhir Al Ansari Professor at Lulea Technical University, Sweden, Eglis Grand 3 3:5, Boden 96231, Sweden.
Mobile Number: +46725390767
E-mail Address: [email protected] or [email protected]
Additional references available upon request