نشریه مهندسی نقشه برداری و اطلاعات مکانی
سال پنجم شماره 4 (پیاپی 20، آذر 1393)

Seafloor mapping and classification are required in many underwater operations of which acoustic signals have been playing an important role. Multi-beam echo-sounders (MBES) are acoustic systems that provides full coverage high resolution bathymetry maps and backscatter information from the seabed or riverbed. They transmit a series of beams to the riverbed and receives the backscatter strengths (BS)، which depend on the angle of incidence. Angular dependence has already been applied to classify sediments using probability density function of the BS from MBES data. A complication occurs when the sediment types change along the swath، because it is difficult to separate from the beam angular dependence and the true backscatter strength variations. Therefore، the classification method is applied to the MBES data of specific angle. This paper employs an algorithm based on image processing principles، which the formation of the image from total massive data is the main step. After correcting for the angular dependence effects، they are gridded with an appropriate interpolation method. The image mosaics are then generated. The image processing techniques will then be applied to enhance the quality of images. Riverbed segmentation is performed by watershed transformation and morphological operations. Finally we assign a particular sediment type to each segment called ''labeling«by the mean grain size of the sediment grab sampling. The algorithm has been implemented on a MBES data set of the Waal river، the Netherlands. The correlation between the true data and image segmentation is about 63% using the specific segmentation. The results show that the proposed procedure improves the classification results compared to the traditional methods.

Semantic Web utilizes different data model rather than relational data model. Tables are well-known for relational data bases while RDF represents data in a model based on directed graph and formed of the triple composition. Although some RDBMS offer storage of graph data but with respect to time and consumed resources، their query efficiency is not appropriate enough. On the other hand، another encountering challenge can be addressed as the interoperable and flexible representation of geospatial data in the Semantic Web standards. A variety of standards from different companies has been designed as a solution for handling the interoperability challenges. One should determine which spatial semantic standard is most appropriate for data of interest، each of which has advantages and disadvantages. This paper reviews standards for spatial semantic data storage and retrieval، moreover by considering the extent of usage، available technologies will be surveyed. Every technology follow specific standard and rather than complete conformance، the technology may support some sections of the standard. In the following، this paper reviews the procedure of establishment and implementation of a semantic Web system that benefit from the approach of spatial semantic data known as “linked geospatial data”. Moreover in the last section of the paper، important points and necessities of each implementation step will be covered.

Watershed basin of Eivashan with an area of 12315 hectares is located in Khorramabad sub region of Lorestan province in Iran، between 48° 48´ to 48 50´ longitude and 33° 22´to 33° 29´ latitude. 5 different methods including Nilsen، Revised Nilsen، Bivariate statistical analysis (compaction of level)، expert judgment and mora varson''s initiative methods are used to derive landslide hazard zonation maps in this region sing GIS. The results shows that Nielsen modified and expert judgment wok better than other methods in evaluating landslide phenomena in the study area. Other methods can not accurately due to low land areas، sliding and damping factors is the failure of the geology and rainfall.

There are two major problems in presenting massive spatial data. First one is presenting whole data in a low scale range، and the second one is presenting part of data in a high scale range. For each of these two regions it is needed special solutions for each of raster and vector data types. Most of database management systems provides three good built-in function solutions for three kinds of above problems. «Image Tiling» for high scale raster data type، «Image Pyramid» for low scale raster data type، and «Spatial Indexing» for high scale vector data type. In fact none of them offers a particular function for optimizing whole vector data presentation at low scale range. In this study، by using generalization algorithms، we implemented a pyramid vector structure for some massive layers of 1/25000 National Topographic Database maps which were about one gigabyte، and needed 80 seconds to be presented at 1/11000 000 scale. After preparing vector pyramid architecture، it was possible to present them all، in just a four seconds.

SAR image matching is one of the most important processing steps for Digital Elevation Model (DEM) extraction using interferometry and radargrammetry methods. Because of radiometric distortion as speckle noise، layover، foreshortening and shadow، the matching processing is more complicated in SAR images than optical images. Limiting search area is one the methods to improve SAR images matching in the Area Based Matching (ABM) method. In this article we use epipolar line geometry for limiting search area of Terra-SAR-X image pairs during the matching. Epipolar line in the slave image is determined by Rang and Doppler (RD) equation and by orbital information، but solving direct and indirect RD equations for all pixels in master images is very time consuming processing. Therefore we employ some mathematical functions including linear، bilinear، and quadric functions for determining relationship between master image coordinate and epipolar line parameters in the slave image. The results show linear and bilinear equations can relate image coordinate in master and epipolar line parameter in slave image by accuracy better than 0. 5 pixels. Thus with only 4 points in master images that were matched with corresponding points in slave image، we can find epipolar line in the slave for all pixel in master image.

Based on 42 GPS velocity vectors existing in NW Iran، we estimated new velocity vectors for some arbitrary positions in study area by using two activation functions of Back Propagation Artificial Neural Networks (BPANN): “Sigmoid Function” and “Continuous Log-Sigmoid Function”. The results show sigmoid function’s RMSEs in E and N components are ±1 mm and ±1. 5 mm respectively which is less than Continuous Log-Sigmoid Function RMSE. So it seems BPANN method could be considered as a good alternative to estimate geodetic velocity field relative to other classical estimation methods.

Geodetic and photogrammetric mapping systems and methods can''t meet all the requirements of the displacement measurements. Hence، to collect information on local deformation، geotechnical and non-geodetic instruments are used within the deformable body. Geotechnical instruments such as extensometer، tiltmeter، inverted pendulum، and other similar devices can be used to gather continuous data. Definitely، by combination of geodetic and geotechnical measurements and by implementation of a comprehensive analysis of displacement، we can obtain better results in the monitoring of large structures such as dams. In this paper، the results of geodetic measurements (microgeodesy observations) of Maroon Dam have been compared with the results of geotechnical observations.