As known Close range photogrammetry represents one of the most techniques to create precise 3D model. Metric camera, digital camera, and Laser scanning can be exploited for the photogrammetry with variety level of cost that may be high. In this study, the cost level is taken in to consideration to achieve balance between the cost and the obtained accuracy. This study aims to detect potential of low cost tools for creating 3D model in terms of obtained accuracy and details and comparing it with corresponding studies. Smart phone camera is the most available for everyone; this gave the motivation for use in this study. In addition, Google Earth was used to integrate the 3D model produced from all sides including the roof. Then, two different types of the mobile camera were used in addition to the DSLR camera (Digital Single Lens Reflex) for comparison and analysis purposes. Thus, this research gave flexibility in work and low cost resulting from replacement the metric camera with the smart camera and the unmanned aerial vehicle (UAV) with Google Earth data. Mechanism of the work can be summarized in four steps. Firstly, photogrammetry planning to determine suitable baselines from object and location of targets that measured using GPS and Total station devices. Secondly, collect images using close range photogrammetry technique. Thirdly, processing step to create the 3D model and integrated with Google Earth images using the Agi Photoscan software. Finally, Comparative and evaluation stage to derive the accuracy and quality of the model obtained from this study using statistical analysis method. Regarding this Study, University of Baghdad, central library was selected as the case study. The results of this paper show that the low cost 3D model resulted from integrating phone and Google Earth images gave suitable result with mean accuracy level reached to about less than 5 meters compared with DSLR camera result, this may be used for several applications such as culture heritage and architecture documentation.
The article describes a simple and low cost methodology of four-dimensional map creation, based on the main elements of the urban world like such as green ground, buildings, soil, water area and others, which makes it possible to detect the urban progress during a certain period using an open source data of Google Earth and geographical information system. This implies that a study of changes in urban elementrequire an integration of spatial information and corresponding real time, which is referred to as the four-dimensional map. Accordingly, the fourth dimensional (time) was added to the three dimensional spatial information (3 dimensional) study area signifies by the University of Baghdad, Aljadrya Campus. Regarding the article, the study area’s urban progress was considered for Google Earth’s available period of the data set that started from 2002 to 2019 at each of 2002, 2005, 2010 in addition to 2019 before being updated from the field observation. The main goal of this article is to provide an important indicator that can be used to determine the nature of current growth and forecast it in the future. Furthermore, it can be used for solving the problems of negative urban progress, which is what most developing countries are experiencing. Findings show significant changes in the main objects of the study area are represented by increasing each of buildings, green grounds, play grounds by about 40.9%, 65.4% and 30.2% respectively, which are offset by decrease insoil grounds of nearly 20.8%.
This study aims to assess the accuracy of digital elevation model (DEM) created with utilization of handheld Global Positioning System (GPS) and comparing with Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM), version 2. It is known that the quality of the DEM is affected by both of accuracy of elevation at each pixel (absolute accuracy) and accuracy of presented morphology (relative accuracy). The University of Baghdad, Al Jadriya campus was selected as a study area to create and analysis the resulting DEM. Additionally, Geographic Information System (GIS) was used to visualize, analyses and interpolate GPS track points (elevation data) of the study area. In this research, three additional DEMs were created using 60%, 30% and 15% of the all GPS track points to deduce the effect of the number of the included points on the accuracy of the resulting DEM. The study findings show a high resolution for the resulting DEM less than 5m when taking into consideration all GPS tracking points that observed in this research. Moreover, the resulting DEM has relative accuracy better than absolute accuracy and reaches to around 2m. By comparing with ground control points (reference points), the quality of handheld GPS DEM shows considerable improvement better than ASTER GDEM. Thus, this study indicates to improve the accuracy level of handheld GPS DEM by about 40% with increasing the observed number of GPS track points to twice.
This study aims to improve the quality of satellites signals in addition to increase accuracy level delivered from handheld GPS data by building up a program to read and decode data of handheld GPS. Where, the NMEA protocol file, which stands for the National Marine Electronics Association, was generated from handheld GPS receivers in real time using in-house design program. The NMEA protocol file provides ability to choose points positions with best status level of satellites such as number of visible satellite, satellite geometry, and GPS mode, which are defined as accuracy factors. In addition to fix signal quality, least squares technique was adopted in this study to minimize the residuals of GPS observations and enhance its accuracy. Moreover, one hundred reference control points were established using geodetic GPS receiver (GR5 receiver), and fixing them in a specified sites of the University of Baghdad, Al Jadriya campus, which selected as a study area, to evaluate positioning accuracy of handheld GPS before and after adjustment. The study findings showed significant decrease in root mean square error (RMSE) in both horizontal and vertical directions from 9.4 m to 3.2 m and 6.8 m to 2.4 m respectively.
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