The construction industry has predominantly relied on conventional building methods that prioritise elevated energy consumption over the entire life cycle of a structure. Most greenhouse gas emissions occur while operating the building. In Iraq, the use of insulation materials is optional, and most buildings are built using traditional materials. Therefore, retrofitting existing buildings using renewable materials can reduce global energy consumption and greenhouse gases emissions. For that reason, the utilisation of technology in the construction industry is imperative to attain enhanced productivity outcomes. Thus, one of the most valuable technologies is building information modelling (BIM). This study aims to analyse and optimise the energy efficiency of a building through the utilisation of Autodesk Revit and Insight 360°. The results indicated that the energy consumption in the building decreased from $6.28/m2/year to $3.56/m2/year. Applying parameters to energy analysis can lead to enhanced conceptual designs that are effective from an environmental standpoint.

Documentation of historic structures is widely recognized as an initial and crucial step in safeguarding tangible cultural heritage. Capturing and preserving detailed information (geometry and any architectural ornamental features) of these structures can ensure long-term conservation and provide valuable resources for research, education, and future conservation efforts. Selecting appropriate methods and techniques for documentation to create a comprehensive 3D representation of the historic structure is always a subject of research, and it is a challenging issue, specifically if the site is in an area with security concerns. This research aims to evaluate the Digital Surface Model of the Minaret of Amedy, a heritage site that is nationally registered. The data collection process was planned and executed, involving an e-survey GNSS receiver for measuring ground control points and a total station (TS, Leica TS06) for measuring control points on the four sides of the Minaret. Two hundred three images were taken by UAV, DJI Phantom 4 pro manually flown, and 196 images using Nikon D5300. The data was processed using the Agisoft Metashape photogrammetry software to create the final 3D Surface model and orthophotos. The RMS errors gained from UAV orthophotos are presented relative to the TS. Sub-centimeter accuracy for horizontal and vertical positions was obtained at low flight altitudes. The 3D digital models’ accuracy of the Minaret was assessed using conventional survey measurements, resulting in a maximum standard deviation in the coordinates of ±2.4 cm. The relative accuracy in distance measurement ranged from 0.00% to 0.20% and 0.00% to 0.30% in the horizontal and vertical directions, respectively. In addition, the maximum inclination of the Minaret in the East and West direction is about 18 cm and 13 cm, respectively, which were observed. These results reveal that the finding is valuable for future intervention and further research.

This research uses Unmanned Aerial vehicles (UAVs) as a platform to examine and monitor a building. It concentrates on inspecting building flaws, particularly cracks, utilizing UAV photogrammetry, which is the focus of this study. The reason for using a building as an object in this work is that the building maintenance team can evaluate, which can support providing trustworthy crack information on buildings. The building chosen for this work contains a reasonable amount of cracks, making it suitable. The methodology and procedures are used to take images of cracks in the building. The software can determine the size of the cracks based on 518 photos taken with a UAV. The 3D model of the building is created by using Agisoft Photoscan software to receive an overview of the building dimensions. The measurement of cracks is also being processed using Photomodeler software. The results showed that the capability of the UAV imagery can aid present surveying operations, particularly on building maintenance. It also indicates that cracks appeared on buildings from 0.72cm to 3.24cm in a certain altitude. The Root Mean Square (RMS) error obtained from comparing the actual and measured value of cracks was ±0.70 cm with the help of 114 GCPs distributed all over the building.

Digital image correlation(DIC) is a non-contact optical approach that employs tracking and image registration techniques to evaluate image alterations within two or three dimensions precisely. The DIC approach's primary focus revolves around identifyingsimilarities between images that have undergone deformation, commonly referred to as the "degraded image," and images that have remained unchanged, known as the "Reference image." This approach is utilized in diverse scientific and technical disciplines to measure full-field displacement and strains. DIC is widely recognized as a valuable and efficient technique for quantifying in-plane deformation. Moreover, DIC is currentlybeing utilized to monitorthe behaviorof concrete beforefractures, including the propagation and displacement of cracks. Additionally, new applications of DIC are continuously being discovered. This paper aims to review the various applications of DICandcompare its capabilities with conventional measurement techniques, such as gauges and transducers, in the context of material testing and deformation measurement.

Building Information Modeling’s popularity has recently exploded in the public construction industry. In many countries, the critical success of any engineering project depends up on the integration of information. BIM is widely implemented in the construction industry in developed countries. In the architecture, engineering, and construction (AEC) industry, developing countries are attempting to follow up the newly established processes and technology. Thus, this study aims to investigate the BIM level in Iraqi construction and the main barriers and constraints to implementing such technology. A literature review, and a structured questionnaire was conducted to determine the current situation of BIM in Iraqis’ AEC. The questionnaire was circulated to the governmental and non-governmental sectors. The analyzed data, that were obtained using Microsoft Excel and Statistical Packaging for Social Science (SPSS), indicated that most participants were using traditional methods and 2D drawings in their designs. This leads to confirm that BIM in Iraq is at level (0). Furthermore, twelve barriers were selected, and the results showed that the highest three ranked barriers in adopting BIM according to the mean score were “Lack of BIM experts”, “Lack of BIM awareness” and “Traditional methods of contracting” with the mean value of 3.78, 3.65 and 3.64 respectively. The obtained results were compared and discussed with the previous researches. Therefore, authorities should put more effort into overcome these obstacles in order to enhance Iraq's AEC industry and use BIM methodologies in the Iraqi construction industry sector.

Providing housing units with livability and suitable facilities that can be an appropriate shelter for citizens is one of the main concerns of planners and officials. The problems of lack of access to standard and viable housing units in Iraq that faced major social and economic crises, war and terrorism, are more tangible. This paper tries to examine this problem by comparative, descriptive, field, questionnaire, and laboratory methods. For this purpose, 154 residential units, which are located in 17 residential sectors of south Malta neighborhood in Duhok city were evaluated, and some criteria considered in the present study includes 1-the quality of the buildings, 2-garbage and specks of dirt and stagnant waters, 3-lighting of the passages, 4-smoke and dust, 5-crowd and traffic and voice, 6-having yard or balcony or good landscape or green area, 7-animals and insects, bad odors, 8-access to transport networks. The main aim of this paper is to reveal the disproportion and uniformity of residential sectors and inappropriate residential sectors of Malta neighborhoods using TOPSIS. The Order Performance technique by Similarity to Ideal Solution (TOPSIS) model was ArcGIS were used for analysis and assessment. Shannon entropy was used for weighting criteria which showed that the Smoke and dust, animals and insects, and bad odors had the highest importance in analysis with a weight of 0.178, and 0.168 respectively. The residential unit with number 30 was the best and the most viable building with the highest Ci score (0.361). Residential unit 64 with a Ci of 0.150 was the least appropriate. In general, the west and northwest buildings of the Malta Neighborhood were more suitable for living in.

Remote sensing utilization has become a new and well-accepted trend in the use of multisource images at different processing levels for numerous applications such as the classification of the urban area. Throughout this study, in order to fully exploit information for the classification of the urban land cover, feature-level data fusion of a coarse resolution hyperspectral long-wave infrared (LWIR) image and a very high-resolution visible-light image are employed. However, optimum parameter determination for the support vector machine (SVM) classifier and the feature subset pick strongly affect the classification performance of these data. Taking into consideration the complex relationship between these two obstacles, the parameters of SVM and the feature subset by particle swarm optimization (PSO) are the simultaneous determinants proposed in this paper. For this purpose, on the one hand, vegetation index, spectral and textural features, and morphological building index (MBI) obtained from visible data are extracted. On the other hand, PCs are derived from hyperspectral LWIR. Experimental implementations of the 2014 Data Fusion Contest dataset showed that the suggested approach improved the classification efficiency by up to 7% compared to SVM without PSO. Furthermore, the obtained findings illustrate the superiority of the suggested technique compared to other data fusion experiments with the same data.

Modern technology fusions are referred to as a significant source in remote sensing. It is one of the various sources that incorporate the use of active Light Detection and Ranging (LiDAR) as well as passive optical hyperspectral imaging spectrometers. Obtaining definite measurements correlated with the structural form and function of objects is the main advantage of this combination. It enables the discrimination of an object depending on its structural characteristics and spectral properties. The merging feature level is utilized in order to obtain benefits from both datasets. However, optimum parameter determination and feature subset selection have a profound result on the classification performance of the fusion combination of the data. The support vector machine (SVM) parameters, as well as the feature subset by particle swarm optimization (PSO), have a complex relationship when combined; thus, they are determined throughout this study to improve the final classification results. In addition to the original hyperspectral data, products of spectral reflectance, vegetation indicators and personal computer devices (PCs) are derived and separated out from hyperspectral data. However, LiDAR data-based digital surface model (DSM) is available. For further explanation of structural information, many textual forms, coarsenesses, slopes and morphological profiles, a derivative and statistical form of geographics are calculated. Tests demonstrated that the suggested technique for the accuracy of the classification could improve to approximately 6% with respect to the outcomes of the hyperspectral imagery classification. The findings achieved also demonstrate the improvement of classification for the group of residential, commercial and trees, which are approximately 30%, 40% and 18%, respectively.

The height obtained through the GNSS method is the ellipsoidal height and to have an efficient application in surveying it has to be converted into orthometric height. This paper aims to determine a local geoid model for a part of Duhok region based on the known orthometric height using GPS/levelling and assessing the precision performance of the two Earth gravitational models (EGM1996 and EGM2008) in the study area. The EGMs were adjusted based on root mean square errors, calculated from the differences between two geoid heights, GPS/levelling and EGMs. The Kriging interpolation method was used for creating a local geoid model based on GPS/levelling. The result from the adjusted geoid models to the survey data at 54 points revealed that the mean accuracy of geoidal heights at 0.08 m level is attainable. The precision performance of EGM96 is more precise than EGM08 by 14 mm in the area of interest.

The progress in modern technologies such as precise lightweight cameras mounted on unmanned aerial vehicles (UAV) and the more user-friendly software in the photogrammetric field allows for 3D model construction of any structure or shape. Software now achieves in sequence the processes of matching, generating tie points and block bundle adjustment and generating digital elevation models. The aim of this study is to make a virtual 3D model of the College of Engineering, University of Duhok, Kurdistan Region, Iraq. The data input is vertical and oblique imagery acquired by UAV, with the ground control points being distributed on the surrounded ground, facades, and roof. Ground control points were measured by the GPS RTK system in addition to the reflectorless total station instrument. The data is processed mainly using Agisoft PhotoScan software as well as the Global Mapper and the ReCap software. The output is a 3D model, digital elevation model, and orthomosaic. Geometric and visual inspections were carried out. Some imperfections appeared on the sharp edges and parapets of the building. In the geometric accuracy of selected points on the building, the maximum standard deviation in the coordinates was ±4cm. The relative accuracy in distance measurements was in the range from 0.72% to 4.92 %.

In the latest decades, Unmanned Aerial Vehicles (UAVs) have witnessed rapid growth and it plays a vital role in different fields of engineering and architecture. This technique can also be applied in land surveying as a device in order to measure the 3D ground coordinates and Earth work. The main aim of this paper is to evaluate the accuracy of volume that obtained by using Digital Elevation Model (DEM) derived from UAVs images. In this research, three different flights were performed with DJI phantom 4 pro (25m, 50m, and 100m) with 80% forward and side overlaps at Duhok Dam. Several Ground control points (GCPs) were installed and evenly distributed throughout the study area and their coordinates were determined using GPS-RTK technique for geo-referencing. The data images captured with UAV were processed using Agisoft photoscan Professional software. GPS survey was carried out using Leica viva GS10 base, and GS15 rover for the same place. The volumes acquired by the UAV images including all three flight heights were compared to the volume obtained with GPS survey techniques which considered as a base for comparison. The results showed that the volume calculated with UAV images encountered to the base were compatible with each other with (99. 86%,99. 76% and 99. 74%) for altitudes (25,50, and 100) respectively.

Elevation surface is a fundamental element of spatial data that can be employed to perform a variety of geostatistical and spatial analyses. On this basis, this paper presents the assessment of elevation surfaces interpolation methods such as Inverse Distance Weighting (IDW), Ordinary kriging, and Local Polynomial Interpolation (LPI). There are three scenarios for achieving this purpose by examining it in three different areas: mild slope area, steep slope area and combined case. The dimension of each tested area is decided to be 100*100 m with 121 survey points for each. The ellipsoidal height of survey points are measured by the Global Navigation Satellite System (GNSS) receiver exploiting the real-time kinematic (RTK) technique. All survey points are transferred to Arc GIS environment for generating elevation surfaces and conducting interpolations. Interpolated pixels of surfaces are then compared with the trusted data collected with GNSS receiver in RTK mode. The result revealed that the total Root Mean Square (RMS) error for kriging interpolation in the steep area is around 26 cm, whereas RMS for LPI interpolation in the flat area found to be approximately 8.0 cm. The evaluation outcomes can be utilized to understand the influence of the slope on interpolation methods as well as to select the most appropriate method according to the ground relief.

The Unmanned aerial vehicles (UAV) have become convenient for many applications such as the production of 3D ground models, orthophotos, road maintenance and dam monitoring, etc. The aim of this paper is to investigate the accuracy of the orthophoto obtained from UAV images compared to the existing orthophoto generated from aerial survey conducted by Vossing German Company in Duhok city, 2011 using GPS ground control point as a reference base. A digital elevation model (DEM) of the university campus was created with the UAV vertical images. Low flight height of 80m was used with the rate of 70% forward overlap and 40% side lap. An orthophoto is produced based on this DEM. To assess the accuracy of UAV orthophotos and the existing orthophotos produced from aerial survey, 7 ground control points (GCPs) were distributed and used for processing the orthophoto mosaic and DEM, 12 GCPs were used as check points. The 19 GCPs were accurately measured using GPS-RTK. Discrepancy in horizontal position of the GCPs measured on both orthophotos was obtained relative to the reference GPS base control points. The UAV data were processed and analyzed using two softwares pix4D and Agisoft Photoscan. The RMS errors obtained from both orthophotos is presented relative to the GPS base. Sub-centimetre accuracy for horizontal position was achieved from the UAV orthophoto at low flight altitude.

The Online Positioning User Service (OPUS) is a suite of Web-based tools used to process GPS data. It is a popular tool for surveyors, engineers, and the academic communities that offer precise positions from global positioning system (GPS) observations. OPUS offers point position processing via online services worldwide. For many developed countries, the extensive numbers of available Continuously Operating Reference Stations (CORS) is facilitated in obtaining accurate results. However, the accuracy of this tool has to be checked in remote areas or in areas where there are limited base stations available. This research focuses on checking the accuracy of the observation session from 2 to 15 hours in the area in which CORS is insufficient and comparing them with OPUS published accuracies and precision. 16-h-duration GPS data files collected on 13 passive stations in Duhok area using Leica viva GNSSN, GS10 in static mode. Then, these data files were windowed into sessions ranging from 2 to 14 hours in duration. The windowed files were processed in OPUS-static, and the resulting coordinates at each station were compared with the coordinates averaged and achieved 1 to 8 mm in precision which has been considered as a true value. The results showed that the obtained accuracies were not complied with OPUS published results. While for the windowed sessions, the achieved precision was in the range of 1 mm to 30 mm.

In this study the geometric accuracy of four different maps for three sectors of Duhok city were assessed. The maps were produced in different periods and different techniques. One set of maps were paper plotted maps which had to be geo-referenced. The other three maps were digitally plotted with reference to the global coordinate system UTM/WGS-84/Zone 38 N projection. A total of 51 points were identified on one reference map which is the master plan of Duhok city prepared by the general directorate of urban planning/Kurdistan region/Iraq with the collaboration of the German company IngenieurburoVossing Company.The reference map, which is the master plan of Duhok governorate, is an official map that is certified and checked by the ministry of planning of the Kurdistan region to havea positional accuracy of 1.5 cm.These points were searched for and identified on the other three maps. Discrepancies in Easting and Northings of these points were calculated which resulted in the mean discrepancyof 2.29m with a maximum value of 8.5m in one event. The maximum standard deviation in dE and dN was 3.8m. These values are reasonably accepted considering that the maps were prepared using different techniques and a variable accuracy standard.

In this research, Digital level (DL), Total station (TS) and GPS were used to assess accuracy and precision of the height component. Field observations were implemented in two tested areas. A reference network which consisted of 34 points on area1 and 10 control points on area2 which had been observed five times using Digital level, RTK-GPS and Total station (TS) where Digital level was considered as a base for comparison. Several known control points were used as check points to evaluate the accuracy of measurements. According to the obtained results, TS and GPS-RTK measurements were compared with the adjusted reference points measured by precise Digital level (DNA 03). Around ±15 mm standard deviation for TS and ±13.5 mm for GPS were achieved. Linear accuracy of TS, GPS, and orthophotos measurements from Vossing German Company were also investigated in regular features within the same tested areas. The actual lengths were measured with steel tape up to a millimeter accuracy and were considered as being a base for comparing. The maximum deviation 22mm accuracy has been obtained in area2 and 12 mm in area1. The study shows that the extracted features from orthophotos had less accuracy in hilly regions due to relief displacement whereas they were more accurate in gentle slopes.

The accumulation of sediment in the bottom of the dam is one of the major causes contributed to dam failure. This in turn creates risks of flooding for villages and cities below it. The aim of this research is to investigate the output of the bathymetric contour map of the bed of small Earth dams in Duhok at three different locations (Kashkan, Zawita and Skreen) as well as to determine the volume of accumulated sediment for each one at different periods of establishment. In addition, a comparison between the current statuses and the design life of each one was achieved. Both vertical depth and horizontal position measurements are implemented using two methods. The first one is the manual and direct method using lead line rope, weight, total station and DGPS for data collection in Zawita and Kashkan reservoir. While, the second method used the Acoustic Doppler Current Profiler (ADCP) integrated with the Global Positioning System (GPS) to record both vertical depth and horizontal position measurements automatically in Skreen dam. The ADCP was calibrated for adjusting the axes (heading, roll and pitch) before collecting data. The data of ADCP were processed and analyzed using River Surveyor Line software and the bathymetric contour map of the selected reservoir's bed was created using AutoCAD civil 3D software. Also, the volume of sedimentations of each selected Earth dam was calculated from the difference between the created topographic surface of the reservoir bed and its original one. The results show that the volume of the sedimentation in kashkan reservoir is about 13810 m3 for the period of 2009 to 2018, Zawita reservoir is about 4449 m 3 for the period 2010 to 2018, Skreen reservoir is about 4608 m 3 for the period 2009 to 2018, and the design life of each one estimated by state was approximately similar to the finding of this research.

Google Earth imagery is frequently used in science, engineering, and other mapping applications. However, the company owning the tool announced that the data available in its geographical products is only approximate, so its accuracy is not officially documented. The Google Earth imagery in many areas around the world has been independently checked by scholars and third body parties. The estimated accuracies are found to largely vary depending on various factors but mainly due to, the imagery source or the image resolution. Positional accuracy testing methodology may also affect the assessment results. In processing, there should be many points around the tested area in order for the comparison to be more reliable. In this paper, the horizontal accuracy assessment was carried on the Google Earth imagery in Duhok city using the traces collected via GPS in Real Time Kinematic (RTK) technique. About 38 km of trajectory was collected for the two main roads in the selected area. Via semi-automated method, the points from RTK trajectory were compared to the corresponding extracted points from the centerline of the road network of Google Earth imagery. The nearest neighboring method through buildup algorithm was considered for comparison between both sets of data. Root Mean Square Error (RMSE) and maximum error were computed for horizontal positional coordinates and found to be 1.53m and 7.76m, respectively.

The large amount of available sedimentation in the reservoirs at different locations of reservoir bed implies the need for accurate hydrographic survey approaches. This approach is normally plotted to create bathymetric contour map. The aim of current study is to investigate the bathymetric contour map of the reservoir bed for Duhok dam and determine the volume of accumulated sediment within the local catchment conditions of Duhok reservoir for the period of 1988 to 2016 which has not been explored yet. Also, the life of the reservoir can be calculated. The study used the Acoustic Doppler Current Profiler (ADCP) integrated with the Global Positioning System (GPS) to record both vertical depth and horizontal position measurements, respectively. The data were processed and analyzed using RiverSurveyor Live software, and the topographic surface of the entire reservoir bed was created using AutoCAD civil 3D software. The results showed that the volume of sedimentation in the reservoir was about 8.0 million m3 for the period of 1988 to 2016, and the life of reservoir is 180 years since the commencement of the operation.

The Google Earth application is a free source of information and data for the general public. The application provides in addition to its valuable ground imagery, point coordinates in local UTM system and ground profiles can be obtained easily. To assess the positional accuracy provided by the system in local Duhok city topographic conditions, point coordinates obtained from Google Earth images are compared with the high accuracy coordinates obtained by GPS system. For this purpose two sites were selected. The first site was within the university of Duhok campus where height differences does not exceeds 18m. The standard deviation obtained in E, N, and Z were± 0.98, 1.14, 1.05m respectively with range of -2m to 2m in all 14 measured points. The second site was located on the northern Duhok city outskirts, (Zuzan housing city). Difference in elevation points on this ground is 80m. The standard deviation obtained in E,N, and Z were ±2.32,3.01, and 10.68m respectively for 15 well defined points with a range of -7 to 7m in E , N and -18 to 23m in elevation. A surface was established using AutoCAD civil 3Dprogram by inserting Google Earth image and surface. 81 GPS coordinates were used to create another surface. Elevation of points on the two surfaces is compared. A standard deviation=±11.74m, in points elevation was obtained with a range of (-26.43 and 23.06). Obviously in an undulating grounds, Google Earth cannot provide high degree of accuracy. The system is not so sensitive to sudden changes in ground topography in short distances.

A Mobile Laser scanning system (MLSS) is a kinematic platform combining different senses, namely: GPS, IMU, and Laser scanner. These senses are integrated and synchronized to a common time base providing 3D geo-referenced data. MLSS is used in several areas; such as 3D urban and landscape modelling for visualization in planning and road design, simulation for environmental management, and to support land use decision- making. The accuracy of 3D georeferenced points, achieved via Mobile Laser Scanning (MLS) under normal conditions, can reach the level of 3 cm. However, this accuracy tends to be degraded in urban areas, because of trajectory errors of the laser scanner (IMU drift due to the limited availability of GPS signal). This, also, can be attributed to the difficulty of matching natural features in the point cloud. Previous researches have tried to overcome the problem in urban laser scanning by focusing on enhancing the performance of the Navigation System (NGS). This can be costly and may not achieve the high accuracy level required for some Engineering applications. When the Navigation Solution is degraded, the accuracy of the point cloud results will be degraded. Using different data sources is another way to improve accuracy in urban areas. For example using airborne LIDAR, terrestrial imagery, and unmanned aerial vehicle (UAV) but these are very time consuming as well as costly compared to MLS systems. Targets are used in a number of way in MLS and are often chosen from natural details points. These can be difficult to define, particularly when high accuracy requirements need to be met, for example, when matching scans together or fitting scans to existing surveys as used in this project, and calibrating the system. The accuracy of MLS in the urban area was tested using three methods, namely Ground Control points (GCPs), surface to surface comparing, and additional source of data. Also, the effect of range, incidence angle (IA), resolution and brightness on different types of targets (sphere, cone, pyramid and flat target) was studied to explore the optimal target design. Moreover an algorithm for automatic target detection was developed to detect the optimal target. Then, for each target in the point cloud, the center/apex was calculated using least square surface fitting. Test show that the accuracy of 3D coordinates, obtained from MLS in an urban area is about 2-5 cm. Test also show that using targets with MLS can improve the quality of result reaching 5mm levels of accuracy even in the urban area, based in the use of checkpoints to assess the quality and reliability of the outputs. Almost all work on this project was carried out using the software packages available at the Nottingham Geospatial Institute (NGI) and MLS data provided by 3D Laser Mapping Ltd. (3DLM). Two terrestrial laser scanners, namely: HDS 3000 and Faro Focus3D have been used for testing the designed targets. The finding of this research will contribute easy, cost effective, and improved accuresies in MLS data. This enhances usefulness in application, such as change detection, deformation monitoring, cultural heritage and the process of 3D modelling, particularly in urban areas.

A satellite and terrestrial oblique images were used to measure the coordinates of ground points. The study area is located on the outskirts of Dohuk city. This location allows for acquiring a terrestrial oblique image from the surrounding mountain. The direct linear transformation solution was used to transfer from photo coordinates into ground coordinates. The obtained accuracy matches the GPS accuracy of ground control points.

The continuous developments in the survey technique gave rise to discovering of many ways and new procedures for map compilation, as well as improving the efficiency of the conventional ways, which is referred to as "The field surveying". These ways differ from each other by cost of production, and the purposes for which the map is produced. Also these ways are differ from each other in the accuracy of the produced maps. These discrepancies lead to the need of determining a suitable production way for limited purposes, with the required accuracy. On these bases the subject of this study was based in order to complete the accuracy analysis obtained from different procedures of map compilation and these are: The field survey, aerial survey, satellite surveying and space imagery. Through studying each method and then comparing the results of all methods with the result of the field survey because we considered it the most accurate way of map compilation. The study area was selected to include many ground control points, which was used later for the purpose of accuracy analysis of the results. These points consist of a central control point in addition to five surrounding points distributed around it. The procedures used in this work for calculating the ground coordinates of the control points are: The field survey, the direct measurement on maps with scales of (1: 10 000 & 1:100 000), analogue aerial surveying methods and analytical digital method, for aerial photos with scale (1:10 000). We also used space imagery from (Landsat TM) satellite imagery, which have resolution up to (30m). Then, the study included one of the Global Positioning System receivers which is (Magellan GPS NAV 1000™ differential accuracy ±30 m) for determining the ground coordinates of control points and then analyzing the results. The final accuracy analysis is performed depending on the root mean square errors of the computed results (RMSE), which was calculated through the comparison of the differences of the control points which is calculated in every method with the calculated coordinates by (field survey). We also made a graphical comparisons by using Geographic information system (GIS), which is making these comparison easily and quickly understandable by displaying it on the computer screen. The process of results comparison and accuracy analysis shows that the concluded coordinates from the aerial photography using the mechanical method (analogue) is most accurate result compared with the field survey which gave as a (RMSE) value of (1.25m) which is suitable accuracy for map productions of scale from (1 :5000-1: 10 000). The final results also showed that the Rectification of satellite images using Polynomial Equations of first & second degree gave (RMSE) value of (0.72) pixel, which is equivalent to (21.54m) on the ground. These can be used for producing and revising basic topographic maps of scale from (1:100 000 or less). The final results also showed that each method has its own logical accuracy which is suitable to produce maps related to this method, while it is limited in other scales.