Most surveying works for mapping or GIS applications are performed with total station. Due to the remote nature of many of the sites surveyed, the surveys are often done in unprojected, local, assumed coordinate systems. However, without the survey data projected in real world coordinates, the range of possible analyses is limited and the value of existing imagery, elevation models, and hydrologic layers cannot be exploited. This requires a transformation from the local assumed to the real world coordinate systems. There are various built-in and add-in tools to perform transformations through GIS programs. This paper studies the effect of using Georeferencing tool, Spatial Adjustment tool (Affine and similarity) and CHaMP tool on the precision and relative accuracy of total station survey. This transformation requires real-world coordinates of at least two control points, which can be collected from different sources. This paper also studies the effect of using geodetic GPS, hand-held GPS, Google Earth (GE) and Bing Basemaps as sources for control points on the precision and relative accuracy of total station survey. These effects have been tested by using 111 points covered area of 60,000 m 2 and the results have shown that the CHaMP tool is the best for preserving the relative accuracy of the transformed points. The Georeferencing and spatial adjustment (similarity) tools give the same results and their accuracy are between 1/1000 and 1/300 depending on the source of control points. The results have also shown that the cornerstone to preserve the precision and relative accuracy of the transformed coordinates is the relative position of the control points despite their source.
Flash flood is a dangers natural disaster causes lots of structure damage, traffic collapse, economic defects and human life loss. An efficient way to reduce its effects is preparing flash flood mapping to identify zones at risk due to flood. Flash flood mapping is a powerful tool for urban planners, traffic and infrastructure engineers, emergency and rescue services. This article proposes an approach utilizes remote sensing (RS) and geographic information system (GIS) to prepare flood risk code (FRC) map for Jeddah city, Saudi Arabia. The proposed approach applied the Curve Number (CN) method of flood modelling and uses runoff depth, land use, soil hydrological parameters, surface slope, and longest flow path to generate FRC. SPOT satellite image of the study area was classified to generate land use map, Digital Elevation Model (DEM) was used for generating slope map and for hydrology analysis using HEC-GeoHMS tool, and soil properties were generated from scanned soil maps. All data were integrated in ArcGIS 10.4.1 to prepare the final flood risk map. The results show that a precipitation of 106.3 mm will generate 136.5 million m 3 of flood water. The results according to the developed flood risk code show that due to this amount of precipitation, about 1 million people live in Jeddah are prone to extreme flood risk and about 2 million of population are at major risk, the rest of population (about 0.5 million) are vulnerable to moderate to minor fold risk. The approach was verified using ground truth data and proofed precision.
Flash floods in arid environments are a major hazard feature to human and to the infrastructure. Shortage of accurate environmental data is main reason for inaccurate prediction of flash flooding characteristics. The curve number (CN) is a hydrologic number used to describe the storm water runoff potential for drainage area. This study introduces an approach to determine runoff coefficient in Jeddah, Saudi Arabia using remote sensing and GIS. Remote sensing and geographic information system techniques were used to obtain and prepare input data for hydrologic model. The land cover map was derived using maximum likelihood classification of a SPOT image. The soil properties (texture and permeability) were derived using the soil maps published my ministry of water and agriculture in Saudi Arabia. These soil parameters were used to classify the soil map into hydrological soil groups (HSG). Using the derived information within the hydrological modelling system, the runoff depth was predicted for an assumed severe storm scenario. The advantages of the proposed approach are simplicity, less input data, one software used for all steps, and its ability to be applied for any site. The results show that the runoff depth is directly proportional to runoff coefficient and the total volume of runoff is more than 136 million cubic meters for a rainfall of 103.6 mm.
Reflectorless total station (RLTS) has made it possible for only one person to carry out field measurements and inaccessible points can be measured with relative ease. There is no sufficient information about the accuracy of these instruments for the long range measurements. This paper attempts to evaluate the accuracy of reflectorless distance measurements ranging up to 1000 m and to determine the surface area needed for such measurements at different incidence angles. An experiment was carried out to examine what effect surface material, target size and incidence angle had on distance measurement. In this experiment 10 different distances were measured using targets of 6 different materials and 4 different sizes at 5 different incidence angles. To properly evaluate the results, a special supporting base was designed and manufactured for holding the reflecting targets to ensure accuracy in the evaluation. Based on the accuracy analysis of a lot of testing results, the conclusions that were drawn indicated that the target size had a great effect on the accuracy if the incidence angle was between 15˚ and 30˚.
Currently, Global Positioning System (GPS) techniques are becoming a much larger part of the surveying industry. Many companies are now using GPS in their everyday work activities. The Real Time Kinematic (RTK) positioning is an integral part of topographic surveys, road surveying, constructions and most civil engineering applications. Normally, RTK can be used to collect the positioning data successfully and quickly. The civil and construction projects are designed in ground distances while RTK measurements are done in grid coordinate system, in which the distances between points are different from ground. The RTK measurements should be converted to ground for compatibility with the designed. In this paper, the accuracy of three alternatives for converting RTK measurements to ground was studied. These alternatives are, using scale factor, using two ground reference points and using Low Distortion Projection (LDP) surface. For the accuracy investigation purpose, a traverse of 14 points elongated for a distance of about 1400 m was constructed. Its coordinates were measured using total station, then the misclosure error was computed and the coordinates were adjusted. The traverse points coordinates were measured again using RTK_GPS considering one of them as base point. The three studied alternatives were applied and the results were compared. The results show that the accuracy of the three alternatives is ranging from 2.1 to 2.9 cm in the relative position of points to the base point. For absolute position accuracy, the two ground reference points alternative is the most accurate alternative with an average error of 3.8 cm while the other two alternatives are almost the same with an average error of 12.3 cm.
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