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Representing the Earth’s physical features onto a flat surface is a critical and challenging issue for geodesists to build topographic mappings at field scale in various applications. Artificial satellite positioning data are currently defined on a global geocentric frame, while terrestrial geodetic networks are determined on a local ellipsoid. Hence, coordinate transformations in three-dimensional space are required for data fusion involving different coordinate systems utilizing common points in two sets of coordinates. On the other hand, small companies in many developing countries have some data conversion difficulties due to the need for high-cost software and qualified persons. A low-cost automated tool is helpful in achieving this task and ensuring quality and positional accuracy. In this investigation, the problem was undertaken by establishing a software tool in the Microsoft Visual Studio environment for map-matching with global coordinates based on similarity transformations and a conformal polynomial approach. The tool’s performance was evaluated through a numerical example to assign transformation parameters and derive coordinates of checkpoints from the prediction surface.

Concrete is indeed one of the most consumed construction materials all over the world. In spite of that, its behavior towards absolute volume change is still faced with uncertainties in terms of chemical and physical reactions at different stages of its life span, starting from the early time of hydration process, which depends on various factors including water/cement ratio, concrete proportioning and surrounding environmental conditions. This interest in understanding and defining the different types of shrinkage and the factors impacting each one is driven by the importance of these volumetric variations in determining the concrete permeability, which ultimately controls its durability. Many studies have shown that the total prevention of concrete from undergoing shrinkage is impractical. However, different practices have been used to control various types of shrinkage in concrete and limit its magnitude. This paper provides a detailed review of the major and latest findings regarding concrete shrinkage types, influencing parameters, and their impacts on concrete properties. Also, it discusses the efficiency of the available chemical and mineral admixtures in controlling the shrinkage of concrete.

There is no doubt that the tremendous development of information technology was one of the driving factors behind the great growth of surveying and geodesy science. This has spawned modern geospatial techniques for data capturing, acquisition, and visualization tools. Digital elevation model (DEM) is the 3D depiction of continuous elevation data over the Earth’s surface that is produced through many procedures such as remote sensing, photogrammetry, and land surveying. DEMs are essential for various surveying and civil engineering applications to generate topographic maps for construction projects at a scale that varies from 1:500 to 1:2,000. GIS offers a powerful tool to create a DEM with high resolution from accurate land survey measurements using interpolation methods. The aim of this research is to investigate the impact of estimation techniques on generating a reliable and accurate DEM suitable for large-scale mapping. As a part of this study, the deterministic interpolation algorithms such as ANUDEM (Topo to Raster), inverse distance weighted (IDW), and triangulated irregular network (TIN) were tested using the ArcGIS desktop for elevation data obtained from real total station readings, with different landforms to show the effect of terrain roughness, data density, and interpolation process on DEM accuracy. Furthermore, comparison and validation of each interpolator were carried out through the cross-validation method and numerous graphical representations of the DEM. Finally, the results of the investigations showed that ANUDEM and TIN models are similar and significantly better than those attained from IDW.

Tensile strength of soil is indeed one of the important parameters to many civil engineering applications. It is related to wide range of cracks specially in places such as slops, embankment dams, retaining walls or landfills. Despite of the fact that tensile strength is usually presumed to be zero or negligible, its effect on the erosion and cracks development in soil is significant. Thus, to study the tensile strength and behavior of soil several techniques and devices were introduced. These testing methods are classified into direct and indirect ways depending on the loading conditions. The direct techniques including c-shaped mold and 8-shaped mold are in general complicated tests and require high accuracy as they are based on applying a uniaxial tension load directly to the specimen. On the other hand, the indirect tensile tests such as the Brazilian, flexure beam, double punch and hollow cylinder tests provide easy ways to assess the tensile strength of soil under controlled conditions. Although there are many studies in this topic the current state of the art lack of a detailed article that reviews these methodologies. Therefore, this paper is intended to summarize and compare available tests for investigating the tensile behavior of soils.

Over the last nine years, the ongoing armed conflict in Syria has had a devastating impact on properties and infrastructure, making it necessary to rebuild everything from scratch. As spatial data are a pillar to enhance sustainable socio-economic development, it should be georeferenced and reformed to keep up with the tremendous growth in information and communication technology. On the other hand, the low-distortion conformal mapping contributes significantly to changing the position of any feature on the earth's surface onto a plane to create accurate large-scale spatial data. The current research conducts an analytical study using spatial statistics tools to investigate an optimal conformal projection for representing the Syrian area in a single zone that preserves angles locally, reduces linear distortions, and fulfills modern geospatial technologies' requirements. The findings have shown the applicability of the proposed model as an alternative solution to minimize the scale error over the interest area. In addition, the isograms pattern is close to the shape of the area, and better fits the quality criteria of the chosen projection.

This paper reports the findings of an experimental programme to investigate the development of a structural lightweight concrete mixture using geopolymer binder and palm oil biowastes. Several conc...

This study aimed to analyzethe mediating impact of competence adequacy on organizational health and technology disruption. Leading construction firms in Jordan participated in this quantitative study and he results revealed significant positive effects of competence adequacy, on organisational health. These findingsprove to be an important contribution and implications to both practitioners and policy makers. Moreover, advantageous insights on how CA, TD can enhance the overall organizational health is also provided by this study. Findings and contributions of the study are as follows. Firstly, Jordanian construction firms will get more insight on the importance of institutionalizing competence building in their establishments by increasing awareness in managers. Additionally, anticipating environmental changes like technology disruption are also highlighted by the findings which guide organisations to achieve a sustainable edge over competitors at the marketplace and for future survival.

Map projection is required to convert geodetic position of features on the earth’s surface onto a flat sheet to produce a map. Conformality is necessary for many large-scale maps to maintain angles and scale at any point in all directions. However, over extended area there is distortion due to the change of scale from one point to another. This research conducts a comparative analytical study of the recent established conformal projection, Transverse Mercator, in Hashemite Kingdom of Jordan with another proposed one. In fact, the suggested projection will be chosen to represent the area in single zone, balance errors in linear scale to minimize them especially in the capital and other major population centers, and to meet the requirements of modern surveying techniques. The main objective of this study is to apply possibility of Stereographic projection to find out the most suitable system for mapping in Jordan depending on the previous criteria and double projection approach by using ArcGIS system to define its optimum parameters.

In recent years, many researchers in the construction industry had taken up the challenge to incorporate non-biodegradable wastes as partial replacement of cement and/or natural aggregates in the daily production of cement-based materials. Various efforts were intended to understand the influence of using marble dust in concrete due to its availability and a relatively high volume of the generation that causes serious environmental problems. Previous studies have utilized marble dust as a replacement of cement, fine aggregate, or total paste in the concrete and mortar mixtures. In general, several investigations have shown that up to a certain cement replacement ratio, marble dust can positively impact on the strength and microstructure properties of concrete. Furthermore, the results have indicated that the considerably high degree of fineness in the marble dust provides sufficient cohesiveness of mortar and concrete even in low w/c ratio conditions. Hence, this powder can be utilized as a filler to improve the flowability of cement-based materials. Consequently, this chapter aims to summarize recent investigations on the properties of concrete incorporating marble waste as cement replacement materials, highlight the potential gaps in the literature, and propose a prediction model for estimating the compressive and flexural strengths of concrete with marble dust using regression analysis.

Subdivision is a very important issue in land surveying and is characterized by the legal change of property boundaries in agreement with the local standards and regulations for maintaining...

The palm oil industry generates a significant amount of wastes which their managing has been a major environmental concern in producing countries. The utilization of these wastes as an aggregate source for concrete production will help to sanitize the environment and provides a cheaper and renewable aggregates source for construction industries. This paper presents the results of the experimental program conducted on fly-ash based geopolymer concrete containing Palm Oil Clinker Aggregate (POCA). Several geopolymer concrete mixes were prepared in which POC was used as a replacement to both fine and coarse aggregates at different percentages starting from 25% to 100%. Mix proportioning was done in accordance with ACI 211.1-91. Geopolymer concrete specimens were cast, cured at ambient conditions and tested for the slump, density, water absorption and compressive, shear and flexural strengths. Overall, the use of fly ashbased geopolymer binder and POCA can enhance the sustainability aspects in concrete production as well as produce a high strength concrete. A concrete mixture containing 100% POCA can produce a structural lightweight concrete having a compressive strength of more than 30 MPa and a density of 1821 kg/m3. The use of a geopolymer binder promotes the workability and strength of POCA concrete and reduces its water absorbability. Incorporation of POCA up to 75% did not much change the structural efficiency of the produced concrete, while it was reduced by 32% when the POCA fully replaced the natural aggregate. Nevertheless, the benefits in terms of cost, energy, and environmental savings cannot be overlooked.

© 2019 The Author(s). In fact, Computer Aided Design (CAD) offers powerful design tools to produce digital large scale topographic mapping that is considered the backbone for construction projects, urban planning and landscape architecture. Nowadays local agencies in small communities and developing countries are facing some difficulties in map to map transformation and handling discrepancies between the physical reality and represented spatial data due to the need for implementing high cost systems such as GIS and the experienced staff required. Therefore, the require for providing a low-cost tool based on the most common CAD system is very important to guarantee a quality and positional accuracy of features. The main aim of this study is to describe a mathematical relationship to fulfil the coordinate conversion between two different grid references applying two-dimensional conformal polynomial models built on control points and a least squares fitting algorithm. In addition, the automation of this model was performed in the Microsoft Visual Studio environment to calculate polynomial coefficients and convert the positional property of entities in AutoCAD by developing spatial CAD tool. To evaluate the proposed approach the extracted coordinates of check points from the interpolation surface are compared with the known ones.

In this study, a multi-linear regression model for potential fishing zone (PFZ) mapping along the Saudi Arabian Red Sea coasts of Yanbu&rsquo, al Bahr and Jeddah was developed, using Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data derived parameters, such as sea surface salinity (SSS), sea surface temperature (SST), and chlorophyll-a (Chl-a). MODIS data was also used to validate the model. The model expanded on previous models by taking seasonal variances in PFZs into account, examining the impact of the summer, winter, monsoon, and inter-monsoon season on the selected oceanographic parameters in order to gain a deeper understanding of fish aggregation patterns. MODIS images were used to effectively extract SSS, SST, and Chl-a data for PFZ mapping. MODIS data were then used to perform multiple linear regression analysis in order to generate SSS, SST, and Chl-a estimates, with the estimates validated against in-situ data obtained from field visits completed at the time of the satellite passes. The proposed model demonstrates high potential for use in the Red Sea region, with a high level of congruence found between mapped PFZ areas and fish catch data (R2 = 0.91). Based on the results of this research, it is suggested that the proposed PFZ model is used to support fisheries in determining high potential fishing zones, allowing large areas of the Red Sea to be utilized over a short period. The proposed PFZ model can contribute significantly to the understanding of seasonal fishing activity and support the efficient, effective, and responsible use of resources within the fishing industry.

The emergence of modern geospatial techniques has brought a considerable change in data capturing, processing, and visualization tools. Digital elevation models (DEMs) are a 3D mathematical representation of the earth’s surface. Due to enormous advancement in geographic information system (GIS) tools and technologies, DEMs have a wide range of applications in natural resources management, environmental science, and engineering. In general, primary topographic variables extracted from DEMs are frequently less useful than secondary ones, e.g., surface roughness. Therefore, the precise values of secondary terrain features need to be derived from base DEMs. Generally, topographic roughness is an essential geomorphological variable that is a vital issue in geoscience. This research presents a comparison of deterministic interpolation methods, inverse distance weighted (IDW) and a natural neighbor (NN), with geostatistical technique, ordinary kriging (OK), to investigate the influence of generated DEM on quantifying terrain roughness relied on synthetic data and applying the zonal statistics tool. At the same time, a quantitative and qualitative approach is adopted to assessing the results through statistical methods and visual representations. The findings indicated that roughness values' behavior is broadly related to the quality of the built DEM. The NN approach yielded the greatest DEM accuracy, standard deviation, from a quantitative perspective (±0.930 m) than IDW (±3.748 m) and OK (SD = ±5.544 m) methods.

There is no doubt that the armed conflict is development in reverse that brings about a severe wastage of human capital and infrastructures. The ongoing violence over the last half a decade in Syria has caused serious economic devastation and a massive loss of properties, landlessness, and lack of clarity relating to ownership or use rights. Post-conflict reconstruction is essential as it assigns the future shape of the country, and it is mostly determined by the commitment and capacities of local populations, including national government and civil society, to maintain the process. Therefore, it is necessary to identify the challenges, obstacles, and issues inhibiting the approach of restoring and sustainably developing the current system. Building a potential cadastral system for post-conflict Syria requires practical contributions from all stakeholders to explore possible ideas that may come up with other procedures for solving many legal, political, and technical issues. The design of a clear strategic framework for modernizing cadastral infrastructure will provide more excellent social stability and expand the prospects for economic growth within post-conflict communities. The main objective of this research is to describe a proposed approach for a reconstruction process oriented towards building an electronic multipurpose cadastre in support of sustainable development from an international perspective in line with modern technology. The addressed model ensures unified real estate registration and simplifies the information interchange between agencies.

Nowadays, renewable energy is commonly applied to ensure a sustainable development and minimize the reliance on fossil fuels. Wind is considered as one of the most significant inexhaustible sources of energy for power generation through turbines. However, choosing an appropriate site of wind farm and designing a turbine array to fit it are a key issue to success as expected. Geographic Information Systems (GIS) technology has been widely accepted in a number of areas as a decision support system based on analyzing geospatial data to facilitate reaching desired results in shorter time and less cost. The process of establishing the best-suited location of wind parks require analysis of spatial multi-criteria within a GIS environment using the Analytic Hierarchy Process (AHP). This research focuses on defining the main factors that influence wind energy development and presents GIS-based land suitability analysis model to determine the optimal allocation of wind farm in Syria. As a part of this study, the procedure of designing geodatabase for wind power plants is illustrated that includes conceptual, logical, and physical design phases. The results show efficiency of the integrated technique in site suitability evaluation of the presented case.

The conformal stereographic projection adopted by the Syrian survey authorities to represent the geodetic positions was designed for an age of paper maps according to geographical characteristics of Syria in the French mandate time (1920), which includes only the effective and cultural part of the country. Nowadays, this situation has changed since projects of land reclamation and of exploring petroleum in Al Gazira have been launched as well as modern surveying techniques such as Global Positioning System (GPS) and Geographic Information Systems (GIS) have been applied. This paper aims at overcoming the defects in the Syrian stereographic projection of the whole country by suggesting a new calculation approach and minimizing the errors in linear scale.

Groundwater resources are vitally important in arid and semi-arid areas meaning that spatial planning tools are required for their exploration and mapping. Accordingly, this research compared the predictive powers of five machine learning models for groundwater potential spatial mapping in Wadi az-Zarqa watershed in Jordan. The five models were random forest (RF), boosted regression tree (BRT), support vector machine (SVM), mixture discriminant analysis (MDA), and multivariate adaptive regression spline (MARS). These algorithms explored spatial distributions of 12 hydrological-geological-physiographical (HGP) conditioning factors (slope, altitude, profile curvature, plan curvature, slope aspect, slope length (SL), lithology, soil texture, average annual rainfall, topographic wetness index (TWI), distance to drainage network, and distance to faults) that determine where groundwater springs are located. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was employed to evaluate the prediction accuracies of the five individual models. Here the results were ranked in descending order as MDA (83.2%), RF (80.6%), SVM (80.2%), BRT (78.0%), and MARS (75.5%).The results show good potential for further use of machine learning techniques for mapping groundwater spring potential in other places where the use and management of groundwater resources is essential for sustaining rural or urban life.