نشریه مهندسی نقشه برداری و اطلاعات مکانی
سال ششم شماره 1 (پیاپی 21، اسفند 1393)

Estimating of the depth in coastal and shallow waters plays an important role in management and exploration of marine natural resources. Collection and production of this geospatial information is the initial step in any planning and development activities. Direct measurement of water’s depth and physical parameters، using field methods in coastal areas is normally costly and relatively time consuming. As an alternative، remote sensing technology can collect the observations in a short time and in a large geographic extent. This subject، in a country like Iran، with vast offshore، has a particular importance. In the past decades، using satellite earth observations for bathymetry in shallow waters is significantly increased. This has been mainly because of the potential of remote sensing data provided by satellite sensors، with proper spectral، spatial and temporal resolution، satellite The main purpose of this paper is to examine the capabilities of hyperspectral satellite imagery for bathymetry applications. To this end، one of the most well-known and frequently used empirical models،i. e. Stumpf is implemented and evaluated. Stumpf (2003) proposed an algorithm to estimate the water depth from multi-spectral images. This algorithm is based on the relative amount of reflection in the visible bands and leads better results in comparison to other methods. The problem is caused by the different type of substrates and is applicable in areas with low reflectivity. The proposed method is applied to a hyperspectral dataset acquired by Hyperion sensor on board of EO1 satellite. The image covers the shallow water in the north coast of Qeshm island. The results of experimental analysis show that the correlation between the image that are analyzed and the stumpf algorithm are applied on and the real depth values is 89. 3% and the standard deviation is 1. 38 meter for special applications which in coastal areas، according to the cost and processing time can be a suitable technique.

Nowadays، Mobile phones have different abilities like satellite positioning which allows calculating the users’ positions. These positions can be used for serving different location-based services for users. Therefore، these services should consider users’ interests and characteristics. This information is usually given manually by the users. If this information is extracted users’ behavior، these services can get interests information automatically. In addition، mobile devices can log calculated users’ locations. Then، each user’s trajectories can be achieved by connecting these locations considering temporal order. Information like interested locations، moving behavior and selected path by users can be extracted using these trajectories. This information can be used for applications like predicting users’ future location. Two methods for extracting interested locations for users are developed in this paper which can be a measure for the users’ behavior. These methods are evaluated using data for Beijing. First method extracts users’ interested locations without considering the time that the users were، but second method considers the presence time for the logged positions for extracting interested locations. Results show that second method has better functionality، because this method considers the trajectory data completely and number of extracted interested locations for second method was more than first method. These algorithms can be used for improving location-based services.

Hyper-spectral measurements obtained using a GER 3700 spectra-radiometer including 584 narrow bands in spectral region of 400–2400 nm were applied to estimate vegetation water content (VWC). Developments in hyper spectral remote sensing have led to developing the new groups of spectral indices and statistical models for estimating biophysical and biochemical properties of vegetation. In this study a back - propagation neural network with three groups of input data set including all spectral bands، the first ten principal components and the best narrow band indices were applied separately as input to estimate the VWC. The suitability of the network efficiency was analyzed applying cross validation technique. The best ANN was obtained using simple linear regression between measured VWC and network outputs in terms of RMSECV and R2cv. The results of this study showed that ANN has a high potential for estimating VWC by hyper-spectral data (Rcv=0. 88، RMSEcv=0. 31).

Due to the rapid transformation of the societies، and the consequent growth of the cities، it is necessary to study these changes in order to achieve better control and management of urban areas and assist the decision-makers. Accordingly it is essential to design a proper solution for image classification. For this purpose، there are numerous methods that can be divided into two general categories; pixel-based and object-based methods. Object-based classification and information extraction methods are usually known as being more effective for classification and interpreting purposes especially in urban areas. However supervised object-based classification، like other supervised methods، requires accurate and sufficient training data. Due to these facts it is highly motivated to design a efficient method to provide reliable training data from existing data sets. In this regard، the training samples was extracted from map and purified by using K nearest neighbor and k-means methods. The results of training data editition improved over 15 percents in the classification accuracy. And change map extraction accuracy in the best case was 98. 08 percent.

Path planning with the aim of finding an optimal path on a multi-modal transportation network، including public transport services and private services، is essential to assist people for using transport network infrastructures. Transportation networks are classified into two categories of time-independent and time-dependent models. The main difference between the two models is constant edge-weight in the first model and time-dependency of departures in the second. The goals of this study is modeling transport networks with different periods، proposing a new method for data storage and developing the Dijkstra’s algorithm for planning on multi-modal suburban transportation networks according to time and personal interests، implementing the proposed process on a dataset and evaluating the results. In this study، a framework is proposed that receives departure time، the source and destination cities as well as user’s priorities of transportation networks and proposes a path planning.

In recent years، location based social networks (LBSNs) have gained great popularity as social media. Their services are in relation with location and allow users to checking-in in different geographic locations and through this share their experiences and visited places. Indeed، these networks act as a bridge between the real world and online social networks. The high volume of check-ins recorded in the social networking sites، contain rich spatial and social information and provide good opportunity for scholars to study the social behavior of users from spatial and temporal view point. In this paper، a comprehensive survey has been done on the articles published in the field of location based social networks during the last few years. This paper aims to classify research issues to draw clearer and more favorable conditions for further studies on this type of social networking sites.

According to the report، the Global Positioning System GPS due to various errors، the absolute positioning accuracy in real terms will not satisfy many applications some corrections must therefore be applied to the observations of the position of the spot. That''s why the effects of various errors and how to deal with these errors has been expressed، the principle of DGPS system performance is discussed. Purpose of obtaining DGPS corrections system to eliminate or reduce errors affecting the accuracy. these corrections can be used to reach the desired accuracy of the navigation system and other matters related to the conduct of the instantaneous position can be used. The basic working principle based on the instantaneous position of the GNSS receiver is at least two. Consideration of the limitations of single-reference systems constraints on the communication system، reduces the accuracy and validity of the submitted corrections with increasing distance - is therefore a reference system are discussed. So the four permanent stations TKCE، KHJE، AHAR، SKOH method for determining the relative position is estimated. The results show that increasing the distance between the station elevation corrections increase the amount and accuracy of the method decreases. Thus it can be concluded that to reduce the adverse effects of these reference stations، the situation is more difference between the position of the unknown station to be deleted In this case، the proposed model is a linear combination of being able to review and remove stations that lowers accuracy DGPS system will be.