جستجوی مقالات مرتبط با کلیدواژه « srtm » در نشریات گروه « علوم انسانی »

Components of verticaldeflection, i.e., North-South component  and East-West component ,are used for accurate determination of geoid or quasigeoid. Moreover, vertical deflection components area useful source for determination of variations in subsurface density and geophysical interpretations. Generally, there are two definitions for verticaldeflection. According to Helmert definition, vertical deflection at any given pointis the angle between the actualgravity vector (actual plumb line) and a line that is normal to the reference ellipsoid(a straight line perpendicular to the surface of reference ellipsoid). Another definition of vertical deflection is proposed by Molodensky. According this definition, vertical deflection at any given point is the angle between actualgravity vector and normal gravity vector (normal plumb line). Some relations have been introduced to convert Molodensky vertical deflection to Helmert vertical deflection. Helmert vertical deflection is estimated using astrogeodetic observations (combination of astronomical and geodetic observations). Presently, global geopotential models (GGMs) have been expanded to the degree of2190, which is equivalenttoabout 5-min spatial resolution. Vertical deflectionat any point on the Earth can be calculated using the GGM. The resulting vertical deflection is consistent with Molodensky definition.Unfortunately, accuracy of GGMs is not sufficient for estimation of verticaldeflection.In other words, since GGMs are expanded up to a limited degree due to their resolution, omission error(or truncation error) occurs in computation of the earth’s various gravity field functionals, such as the geoidal height and verticaldeflection. Combining GGM with a digital terrain model (DTM) is a method used to reduce omission error.It should be noted that DTM has a higher spatial resolution as compared to GGM.In this method, the omitted signals of GGM can be modeled using residual terrain model (RTM) derived from subtracting high resolution DTM from a reference smooth surface. The reference smooth surface is obtained from eitherapplying average operator to DTM or expanding global topography into spherical harmonics. Fortunately, DTMs with spatial resolution of 3seconds or more,and reference smooth surface based on 2190 degree spherical harmonics are publicly available. The present study seeks to assess vertical deflectionderived from a combination of GGM and DTM in Iran. Previously, Jekeli(1999) has studied EGM96 geopotential model with the aim of computingvertical deflection in the USA. Hirt(2010) and Hirt et al. (2010a) have assessed vertical deflection in Europe and the Alps using a combination of EGM2008 and RTM models.In Iran, GO_CONS_GCF_2_TIM_R4, a GOCE-only model, and EGM2008 geopotential model have been used toobtain vertical deflection and the results have been evaluated byKiamehr and Chavoshi-Nezhad(2014).

To implement the present study,a EGM2008 model with a spatial resolution of about 5-min is selected asGGM and a SRTM model with 3-sec spatial resolution is considered as DTM. To obtain RTM, DTM2006 model based on2190 degree spherical harmonicsis selected as the reference smooth surface.To compute the residual topography effect, prism method was used in an ellipsoidalmulti-cylindrical equal-area map projection system. First, we compute vertical deflectionusing EGM2008 model. It is also calculated using a combination of EGM2008 model and RTM(EGM2008/RTM method). In the next step, vertical deflection derived from the first method (EGM2008 model) and the second one (combination of EGM2008 model and RTM) are compared with vertical deflectionderived from astrogeodetic observations in 10 available Laplace stations in Iran.

Results indicate that there is a 1.2sec difference between North-South component of vertical deflection (i.e.) obtained from EGM2008 model and astrogeodetic observations.With RTM, this will reach 1 sec, which shows a 15% improvement. Moreover, there is a5.7secdifference between East-West component of vertical deflection () obtained from EGM2008 model and astrogeodetic observations, while this value will reach 5.6sec using RTM. Improvement in East-West component () is1.4%, which is smaller than the improvement of North-South component (). Based on the computations, we found that values of  and  in the Laplace stations canreach 17sec (RMS=7sec) and 15sec (RMS=8sec), respectively. Therefore, it is concluded that the relative error ofNorth-South component ()computation using EGM2008/RTM method is about 6% and the relative error ofEast-West component ()computation is about 37%.

The present research has studied the RTM effect on the improvement of GGM used for the determination of vertical deflectionin Iran. To performthe study, EGM2008 model with around 5-min spatial resolution was selected as GGM. RTM is also derived from subtracting the DTM2006 model (based on2190 degree spherical harmonics)from the 3-sec spatial resolutionSRTM model. Numerical findings indicate that a combination of RTM and GGM can improve the results of vertical deflectioncomputation, as compared to the results obtained from GGM-only approach. The improvement in North-South component of vertical deflection () is about15%and East-West component of the vertical deflection () undergoes about 1.4% improvement. In general, EGM2008 model and its combination with RTM have been more successful in the computation of  component as compared to computationin the geographical region of Iran. There is no clear explanation for this difference, but it can be due to errors in theastronomical or geodetic observations oflongitude in Laplace stations.

Digital elevation model (DEM) is the raster representation of the ground surface so that the information of each cell on the image has a value equal to the altitude from the sea level corresponding to the same spot on the ground. DEM is an appropriate tool for the generation of topographic maps and contour lines, access to the information of surface roughness, three dimensional vision, etc. (Jacobsen, 2004). The accuracy of the digital elevation model is effective on the accuracy of the information from which it is obtained. This is why researchers are always looking for a way to increase the accuracy of digital elevation models. Among the information resources that are used to generate this model are ground mapping, aerial photography, satellite images, radar data, and Lidar. Some of these data generate the digital elevation model with little accuracy due to the insufficiency of the elevation information. The aim of this paper is to investigate the accuracy of DEMs derived from ASTER satellite images and SRTM data with 30 and 90-meter pixel dimensions and the digital elevation model derived from the topographic 1:25000-scale maps with Differential Global Positioning System (DGPS) in different landforms including plains, hills and mountains.  

The study area is a part of the project of dam and water transfer system from the Azad dam to the plain of Ghorve-Dehgolan (with the goal of transferring water from the catchments of Sirvan River into the country) in the province of Kurdistan and the city of Sanandaj. In this study, the Real-Time kinematic method (RTK) was used to locate the points. In this method, assuming that the coordinates of the reference station are known and comparing it with the location obtained from the GPS receiver, a correction value is obtained that is applied to the coordinates obtained for the Rover Station, which is known as the relative or differential method. In this method, the corrections are calculated asreal-time during the observations and are considered in the determination of the Rover location.The Leica GS10 GNSS receivers were used in this study. First, two reference stations were determined using the Fast Static method and then, the Real-Time kinematic (RTK) method was used. In order to investigate the extent of the data compliance and relation, the Pearson linear correlation analysis was used and the accuracy assessment of the extracted digital elevation models was carried out using the RMSE, mean error and standard deviation. 

The statistical parameters such as root mean square error (RMSE), bias (µ) and standard deviation () were used to assess the accuracy of each one of the investigated digital models. By comparing different sources that create DEMs, it can be seen that the minimum error is first related to the digital elevation model extracted from the contour lines of the 1:25000-scale map (27/6 = RMSE) and then to the ASTER digital elevation model with the pixel size of 30 meters (RMSE=7.43). The 30-meter pixel size DEM has always led to better results than the 90- meter pixel size DEM. Based on the mean error standard, the minimum bias is related to ASTER30 m (bias of 2 m) and then to the 1: 25,000 DEM (2.17). The maximum bias was related to 30-and 90-meter models extracted from the SRTM data. The results of standard deviation error were in compliance with the RMSE results, which confirmed the superiority of 1:25000-scale map and ASTER30 m DEMs. The results showed that the determination coefficient of relationship between the ground data and digital elevation models is between 97 and 99. The maximum compliance is related to the digital elevation model extracted from the 1:25000-scale topographic data and the ASTER30 m DEM, while the minimum compliance is related to the SRTM90 m data. In general, the compliance of the digital elevation models with the ground data decreased as the field's conditions became more difficult, i.e. from plain to mountain.

The results of DEMs accuracy assessment showed that the minimum error was primarily related to 1:25000 contour lines DEM (RMSE=6.27) and then, to the ASTER30 m DEM (RMSE=7.43). The pixel size of 30 meters has always been better than the pixels size of 90 meters. Based on the mean error standard, the minimum bias is related to the ASTER 30 m (bias of 2 m) and then, to the 1: 25,000 DEM (2.17). The maximum bias was related to 30-and 90-meter models extracted from the SRTM data. The results of the standard deviation error were consistent with the RMSE results, which confirmed the superiority of the digital elevation models extracted from the topographic 1:25000-scale maps and the ASTER30 m DEM.

Digital Elevation Models (DEMs) is one of the main geographical data models which form the basis of the different spatial analysis. DEM is known as fundamental data in for many modeling tasks. Nowadays, the results validation of GIS spatial analyzes, has become a major challenge in the world of GIS .The quality of a DEMis dependent upon a number of interrelated factors, including the methods of data acquisition, the nature of the input data, and the methods employed in generating the DEMs.Analysis of uncertainty in different fields, due to data quality and related issues such as error, uncertainty models, errors propagation, errors elimination and uncertainties in the data, are felt more than any other times. Of all these factors, data acquisition is the most critical one. Previous studies on DEM data acquisition have focused either on examination of generation method(s), or on case studies of accuracy testing. These studies are not adequate, however, for the purpose of understanding uncertainty (an indicator used to approximate the discrepancy between geographic data and the geographic reality that these data intend to represent) associated with DEM data and the propagation of this uncertainty through GIS based analyses. The development of strategies for identifying, quantifying, tracking, reducing, visualizing, and reporting uncertainty in DEM data are called for by the GIS community.
In order to apply uncertainty analysis on DEMs this study aimed to evaluate the error rate and uncertainty of elevation data obtained from SRTM and ASTER satellites. The objectives of this study are: (1) to understand the sources and reasons for uncertainty in DEMs produced by cartographic digitizing; (2) to develop methods for quantifying the uncertainty of DEMs using distributional measures and (3) to measure the uncertainty associated with DEMs and minimize the chances of error by manse of optimizing models. Quantifying uncertainty in DEMs requires comparison of the original elevations (e.g. elevations read from topographic maps) with the elevations in a DEM surface. Such a comparison results in height differences (or residuals) at the tested points to analysis the pattern of deviation between two sets of elevation data, conventional ways are to yield statistical expressions of the accuracy, such as the root mean square error, standard deviation, and mean. In fact, all statistical measures that are effective for describing a frequency distribution, including central tendency and dispersion measures, may be used, as long as various assumptions for specific methods are satisfied. Our research methodology includes several steps. The first step causing the statistical indices ME, STD and RMSE, the error rate of DTMs ​​ for obtaining the chances of error in ach model. It has to be mentioned that the main attraction of the RMSE lies in its easy computation and straightforward concept. However, this index is essentially a single global measure of deviations, thus incapable of accounting for spatial variation of errors over the interpolated surface. In order to obtain more accurate results, then uncertainty of data errors was also simulated by Monte Carlo method and error propagation pattern was extracted by interpolation of results.
The results of this step show that, the DEM derived from pair stereo ASTER despite having better spatial resolution, included more errors and practically lacking the details of DTM 30 meters. Finally, removing the error propagation pattern from DEMs, the secondary DEM was produced. By recalculating indicators describing the error and comparing these values with the initial values, the results indicate that, both DEMs show more accuracy after eliminating the error propagation pattern. TPI Index was used to determine the location of basin topography and the basin is divided into 6 classes and error rate in each class was calculated before and after the simulation. The results showed that, the error rates in all classes before and after the simulation in both DEMs were reduced. In terms of uncertainty analysis methods for DEMs, results of our research indicated that the RMSE methods alone is not sufficient for quantifying DEM uncertainty, because this measure rarely addresses the issue of distributional accuracy. To fully understand and quantify the DEM uncertainty, spatial accuracy measures, such accuracy surfaces, indices for spatial autocorrelation, and variograms, should be used results also indicated that Monet Carlo simulation is indeed sufficient methods for simulation error in DEMs. Results of this research are great of important for uncertainty analysis in domain of Geosciences and can be used for improving the accuracy of modeling in variety of applications.

Digital Elevation Model (DEM) enables researchers to perform geographical researches in global and regional scales including global changes, natural disasters, environmental monitoring etc. Therefore, DEM data plays a key role in scientific researches. SRTM and ASTER GDEM are two elevation datasets that cover nearly the entire land surface of the earth and are globally available (for almost 80% of the earth). Thus, it is necessary to evaluate the vertical accuracy of such data prior their use and to select the appropriate data in term of the research target. ASTER based digital elevation model has spatial resolution of 30 meters, which seems to provide more precise elevation data than SRTM with 90 meters spatial resolution. Several studies have been performed for evaluating the accuracy of each of these two datasets in various countries of the world. The results of such studies indicate their advantages and limitations over each other. In this study, the vertical accuracy of these two DEMs are evaluated by ground control point in three zones of Iran with different topographic characteristics, which are Eastern Azerbaijan, Sistan and Baluchestan and Bushehr. Results show RMSE of SRTM for study area in Eastern Azerbaijan, Sistan and Baluchestan and Bushehr is 6.1, 7.4 and 2.9 meters and in ASTER GDEM is 8.7, 8.3 and 7.2 meters, respectively. So the STRM data has high vertical accuracy than ASTER GDEM in all three zones. The relation between vertical errors and land characteristics such as slope and aspect are studied and their results are presented in this study. Final results of the study indicates higher vertical accuracy of SRTM in comparison with ASTER GDEM in Iran and it is concluded that SRTM is a more appropriate choice for various applications.

Elevation models, a numerical expression of the continuous changes in ups anddowns, are capable of demonstrating roads at their actual positions, and facilitate thepossibility of mountain roads management. These models are also capable ofcomputing the potential of natural risks by means of satellite pictures, and can proveuseful in decreasing road accidents.For the present study, the author selected part of Chaloos Road, from Karaj toKandovan, where numerous accidents have occurred. As this part of the road issituated within the drainage basin of Karaj (Amir Kabir) Dam, the study drew on theelevation model (DEM) of this basin, which was extracted from satellite (SRTM)pictures. From this model, hillshade layers were extracted, and layers of adjustmentcurve, drainage system, gradient, gradient direction, and route of the largest gradientwere prepared. Moreover, this part of the road was extracted from a map at a scale of1:50000, and was placed in the above set of layers after being benchmarked. Followinganalyses, the potential of natural risks on this road was assessed.