Mostafa Rabah

Automatic concrete cracks detection and mapping of terrestrial laser scan data

Abstract Terrestrial laser scanning has become one of the standard technologies for object acquisition in surveying engineering. The high spatial resolution of imaging and the excellent capability of measuring the 3D space by laser scanning bear a great potential if combined for both data acquisition and data compilation. Automatic crack detection from concrete surface images is very effective for nondestructive testing. The crack information can be used to decide the appropriate rehabilitation method to fix the cracked structures and prevent any catastrophic failure. In practice, cracks on concrete surfaces are traced manually for diagnosis. On the other hand, automatic crack detection is highly desirable for efficient and objective crack assessment. The current paper submits a method for automatic concrete cracks detection and mapping from the data that was obtained during laser scanning survey. The method of cracks detection and mapping is achieved by three steps, namely the step of shading correction in the original image, step of crack detection and finally step of crack mapping and processing steps. The detected crack is defined in a pixel coordinate system. To remap the crack into the referred coordinate system, a reverse engineering is used. This is achieved by a hybrid concept of terrestrial laser-scanner point clouds and the corresponding camera image, i.e. a conversion from the pixel coordinate system to the terrestrial laser-scanner or global coordinate system. The results of the experiment show that the mean differences between terrestrial laser scan and the total station are about 30.5, 16.4 and 14.3 mms in x, y and z direction, respectively.

Sea Level Change Analysis and Models Identification Based on Short Tidal Gauge Measurements in Alexandria, Egypt

ABSTRACT Sea level change analysis and models identification are important factors used for coastal engineering applications. Moreover, sea level change modeling is used widely to evaluate and study shoreline and climate changes. This study intends to analyze and model Alexandria, Egypt sea level change by investigating yearly tide gauge data collected in a short duration (2008–2011). The time-frequency method was used to evaluate the meteorological noise frequencies. Two models were used to predict the time series data: Neural Network Autoregressive Moving Average (NNARMA) and Adaptive Neuro-Fuzzy Inference System (ANFIS). The time-frequency analysis and models identification results showed that no extreme events were detected for Alexandria point during the monitoring period. Therefore, the NNARMA and ANFIS models can be used to identify the sea level change. The estimates of the models were compared with the three different statistics, determination coefficient, root mean square errors, and auto-correlation function. Comparison of these results revealed that the NNARMA model performs better than the ANFIS model for the study area.

Seabed sub-bottom sediment classification using parametric sub-bottom profiler

Abstract Many studies have been published concerning classification techniques of seabed surfaces using single beam, multibeam, and side scan sonars, while few paid attentions to classify sub-bottom layers using a non-linear Sub-Bottom Profiler (SBP). Non-linear SBP is known for its high resolution images due to the very short pulse length and aperture angle for high and low frequencies. This research is devoted to develop an energy based model that automatically characterizes the layered sediment types as a contribution step toward “what lies where in 3D?”. Since the grain size is a function of the reflection coefficient, the main task is to compute the reflection coefficients where high impedance contrast is observed. The developed model extends the energy based surface model (Van Walree et al., 2006) to account for returns reflection of sub-layers where the reflection coefficients are computed sequentially after estimating the geo-acoustic parameters of the previous layer. The validation of the results depended on the model stability. However, physical core samples are still in favor to confirm the results. The model showed consistent stable results that agreed with the core samples knowledge of the studied area. The research concluded that the extended model approximates the reflection coefficient values and will be very promising if volume scatters and multiple reflections are included.

Datum maintenance of the main Egyptian geodetic control networks by utilizing Precise Point Positioning “PPP” technique

Abstract A geodetic control network is the wire-frame or the skeleton on which continuous and consistent mapping, Geographic Information Systems (GIS), and surveys are based. Traditionally, geodetic control points are established as permanent physical monuments placed in the ground and precisely marked, located, and documented. With the development of satellite surveying methods and their availability and high degree of accuracy, a geodetic control network could be established by using GNSS and referred to an international terrestrial reference frame used as a three-dimensional geocentric reference system for a country. Based on this concept, in 1992, the Egypt Survey Authority (ESA) established two networks, namely High Accuracy Reference Network (HARN) and the National Agricultural Cadastral Network (NACN). To transfer the International Terrestrial Reference Frame to the HARN, the HARN was connected with four IGS stations. The processing results were 1:10,000,000 (Order A) for HARN and 1:1,000,000 (Order B) for NACN relative network accuracy standard between stations defined in ITRF1994 Epoch1996. Since 1996, ESA did not perform any updating or maintaining works for these networks. To see how non-performing maintenance degrading the values of the HARN and NACN, the available HARN and NACN stations in the Nile Delta were observed. The Processing of the tested part was done by CSRS-PPP Service based on utilizing Precise Point Positioning “PPP” and Trimble Business Center “TBC”. The study shows the feasibility of Precise Point Positioning in updating the absolute positioning of the HARN network and its role in updating the reference frame (ITRF). The study also confirmed the necessity of the absent role of datum maintenance of Egypt networks.

Comparison of Satellite Altimetric Gravity and Global Geopotential Models with Shipborne Gravity in the Red Sea

ABSTRACT The determination of high-resolution geoid for marine regions requires the integration of gravity data provided by different sources, e.g. global geopotential models, satellite altimetry, and shipborne gravimetric observations. Shipborne gravity data, acquired over a long time, comprises the short-wavelengths gravitation signal. This paper aims to produce a consistent gravity field over the Red Sea region to be used for geoid modelling. Both, the leave-one-out cross-validation and Kriging prediction techniques were chosen to ensure that the observed shipborne gravity data are consistent as well as free of gross-errors. A confidence level equivalent to 95.4% was decided to filter the observed shipborne data, while the cross-validation algorithm was repeatedly applied until the standard deviation of the residuals between the observed and estimated values are less than 1.5 mGal, which led to the elimination of about 17.7% of the shipborne gravity dataset. A comparison between the shipborne gravity data with DTU13 and SSv23.1 satellite altimetry-derived gravity models is done and reported. The corresponding results revealed that altimetry models almost have identical data content when compared one another, where the DTU13 gave better results with a mean and standard deviation of −2.40 and 8.71 mGal, respectively. A statistical comparison has been made between different global geopotential models (GGMs) and shipborne gravity data. The Spectral Enhancement Method was applied to overcome the existing spectral gap between the GGMs and shipborne gravity data. EGM2008 manifested the best results with differences characterised with a mean of 1.35 mGal and a standard deviation of 11.11 mGal. Finally, the least-squares collocation (LSC) was implemented to combine the shipborne gravity data with DTU13 in order to create a unique and consistent gravity field over the Red Sea with no data voids. The combined data were independently tested using a total number of 95 randomly chosen shipborne gravity stations. The comparison between the extracted shipborne gravity data and DTU13 altimetry anomalies before and after applying the LSC revealed that a significant improvement is procurable from the combined dataset, in which the mean and standard deviation of the differences dropped from −3.60 and 9.31 mGal to −0.39 and 2.04 mGal, respectively.

Determination of zero difference GPS differential code biases for satellites and prominent receiver types

The differential code bias (DCB) is the differential hardware (e.g., the satellite or receiver) delay that occurs between two different observations obtained at the same or two different frequencies. There are two approaches used to estimate DCBs for receivers and satellites: the relative and absolute methods. The relative method utilizes a GPS network, while the absolute method determines DCBs from a single station (zero difference). Three receiver types based on the pseudo-range observables were used here to collect the GPS data: Codeless Tracking, Cross Correlation, and Non-Cross Correlation styles. According to its types, GPS receivers have responded to restrictions on the GPS signal structure in different ways. The main goal of the current research is providing a method to determine the DCBs of GPS satellites and dual frequency receivers. The developed mathematical model was based on spherical harmonic function and geometry-free combination of pseudo-range observables (C/A or/and P-code) according to receiver type. A new elevation-dependent weighting function with respect to GPS satellites in our algorithm was applied. The applied weighting function was used to consider the quality variation of satellite DCBs, which is caused by pseudo-range measurement errors. The code of the proposed mathematical model was written using MATLAB and is called “zero difference differential code bias estimation (ZDDCBE)”. This code was tested and evaluated using data from IGS GNSS stations and different types of GPS stations out of IGS network installed in Egypt and Saudi Arabia. The estimated values from the ZDDCBE code show a good agreement with the IGS analysis centers with a mean error of estimation for the receiver DCB equal 5.94%. Therefore, the ZDDCBE code can be used to estimate the DCB for any type of receiver regardless if the receiver is from IGS network or not.

Using RTK and VRS in direct geo-referencing of the UAV imagery

Abstract Direct Geo-Referencing is a new technique in photogrammetry, especially in the aerial photogrammetry. Unlike the Aerial Triangulation “AT”, this method does not require Ground Control Points “GCPs”, to process aerial photographs into desired ground coordinates systems. Compared with the old method, this method has four main advantages: faster field work, faster data processing, simple workflow and less cost. Generally, direct geo-referencing using two systems, Global Navigational Satellite Systems “GNSS” and Inertial Navigational System “INS”. GNSS recording the camera coordinates “X, Y, Z”, and INS recording the camera orientation angles “w, φ, k” at the time of exposure. These parameters merged and are provided to each photograph in the processing stage. The current paper investigates the using GNSS system for providing the linear exterior orientation “EO” parameters “X, Y, Z” by two techniques, real time kinematic “RTK” and virtual reference system “VRS”. The accuracy of the applied method is tested on topographic survey project in Switzerland. The surveyed data of the specified project were collected by amateur digital camera Canon 18.2 MP, 182 captured images from approximately 85m flight height, 18 Ground Check Point “GCP” determined by static GNSS. Horizontal accuracy is 0.029m for VRS case, 0.034m for RTK case and vertical accuracy is 0.026m for VRS case, 0.029 for RTK case.

Assessment of the most recent satellite based digital elevation models of Egypt

Abstract Digital Elevation Model (DEM) is crucial to a wide range of surveying and civil engineering applications worldwide. Some of the DEMs such as ASTER, SRTM1 and SRTM3 are freely available open source products. In order to evaluate the three DEMs, the contribution of EGM96 are removed and all DEMs heights are becoming ellipsoidal height. This step was done to avoid the errors occurred due to EGM96. 601 points of observed ellipsoidal heights compared with the three DEMs, the results show that the SRTM1 is the most accurate one, that produces mean height difference and standard deviations equal 2.89 and ±8.65 m respectively. In order to increase the accuracy of SRTM1 in EGYPT, a precise Global Geopotential Model (GGM) is needed to convert the SRTM1 ellipsoidal height to orthometric height, so that, we quantify the precision of most-recent released GGM (five models). The results show that, the GECO model is the best fit global models over Egypt, which produces a standard deviation of geoid undulation differences equals ±0.42 m over observed 17 HARN GPS/leveling stations. To confirm an enhanced DEM in EGYPT, the two orthometric height models (SRTM1 ellipsoidal height + EGM96) and (SRTM1 ellipsoidal height + GECO) are assessment with 17 GPS/leveling stations and 112 orthometric height stations, the results show that the estimated height differences between the SRTM1 before improvements and the enhanced model are at rate of 0.44 m and 0.06 m respectively.

Using advanced soft computing techniques for regional shoreline geoid model estimation and evaluation

ABSTRACT This study aims at evaluating the global geoid model for a regional shoreline fitting using advanced soft computing techniques and global navigation satellite system/leveling measurements. Artificial neural networks, fuzzy logic, and least square support vector machine models are developed and used to fit the global geoid model for the north coastal Egyptian line. In addition, a novel estimation geoid model is designed and evaluated based on the latest global geoid models. The results of the three estimation models show that they can be used to correct the shoreline geoid model, in terms of root mean square error that ranges from 1.7 to 8.5 cm. Moreover, it is found that the least square vector machine model is a competitive approach with certain advantage in solving complex problems represented by missing data.