نشریه مهندسی نقشه برداری و اطلاعات مکانی
سال پنجم شماره 3 (پیاپی 19، شهریور 1393)

Volunteered geographic information is one the most significant advances in GIScience following the well-known elements of Web 2. 0. It has been mainly looked at as a source of information، and the focus has been on improving its usage، understanding، and quality. This paper opens a discussion on considering VGI as an implicit source of users’ experience، which provides general users with solutions to help them take actions like an expert. As a case study، the idea has been applied on estimating the optimum travel time path through information collected by experts. Having introduced the methodology، the results for some examples are presented and discussed.

In two recent decades، three main trends of the ubiquitous wireless communication networks technology development، the miniaturization of storage and computing platforms، and developments of new sensors and materials used in the sensors have significantly influenced the field of geospatial information sciences (GIS). These three trends have changed the monitoring methods of environmental phenomena and the ways their information are processed. Moreover، other technology developments have added new significant capabilities in modern geoscience field. This technology، so-called geosensor networks، is the special applications of wireless sensor network technology in geographic fields that detect، monitor، and track environmental phenomena and processes. Both real time aspects and improving spatiotemporal resolution has created new research challenges in environment modeling، monitoring، and processing of information. In this paper، firstly geosensor networks is introduced and the issues and challenges are expressed. Then، considering energy constraints in these networks، decentralized computation system is introduced. Using algorithms based on these computation systems improves energy consumption of network. Finally، the information processing in the network has been described، including in-network storage and processing and data abstraction.

In recent years، unmanned aerial platforms (UAV) equipped with autonomous navigation systems is used in various applications such as disaster management، remote sensing، search and rescue، surveillance، reconnaissance، and target tracking. Importance of using the autonomous unmanned aerial vehicles as sensor platforms and its role in disaster management shows that flexible، optimal، and automatic path planning of UAV flight trajectory is an essential task for automatic guidance and navigation due to various spatio-temporal constraints. Therefore، this problem requires a comprehensive spatial analysis of parameters that influence on platform''s trajectory، development of efficient algorithms، and robust approaches for planning and optimal autonomous navigation. In this paper، after reviewing pervious works، a comprative study of general path planning methods is presented. Then strengths and weaknesses of these approaches are discussed and after comparison، some suggestions are provided. Finally، routing strategies and planning for platforms in target search scenarios is studied.

Practical Applications of bathymetry from ancient times until now، has attracted the attention of scientists to methods that compute it. Bathymetry with ship، despite high accuracy is very costly and time confusing and in the deep regions is impractical even. Hence، the use of indirect methods to predict bathymetry is taken into consideration. Satellite altimetry measure sea level anomaly over 30 years. With retracking methods and new satellite missions such as Cryo_sat، density and accuracy of satellite altimetry data has increased. In geodesy can convert this data to gravity field components such as geoid undulations، free air gravity anomaly، deflection of vertical and etc. on the other hand the internal sources of earth has an important effect on the gravity field components. One of the main this sources in sea is seafloor topography. An inverse can be made by parker relationship between seafloor topography and gravity anomaly data in the frequency domain. On the other hand، iterative least square collocation can be used as an effectively mathematical model to solve inverse problem. In this paper we use the gravity data derived from satellite altimetry and estimate bathymetry in Oman sea area using iterative least square collocation. And compare our result with ETOPO1 bathymetry model and some ship borne depth data in the area of study. Standard deviation between difference of ETOPO1 and ship borne depth data is 121. 4m while this for our computed model is 117. 87m. this is show that our model has better precision in this area compared with ETOPO1.

Estimating accurate bathymetry has many applications in science and engineering. although ship borne sounding are precise method to create bathymetry chart but this method is time confusing and extensive، hence in many oceans region especially in the deeper region don’t exist sufficient data. For this reasons the use of methods that are cost-effective in terms of time and cost are taken into consideration. Satellite altimetry، for over three decades، measures sea level anomaly. For some time، scientists have used these data to measure the gravity field parameters such as gravity، geoid undulations and component of deflection of vertical. Subsurface structures in a region affect in the gravity anomaly. One of the main sources of gravity on sea is seafloor topography. Smith and Sandwell proved that in the wave domain gravity anomaly are most correlated with the seafloor topography in the wavelength range from 15 to 160 km. in this paper we will try to estimate seafloor topography in Oman sea first we filter gravity anomaly and then downward continue them to the mean depth and finally by using Weiner optimization method and ship track line gravity data estimate seafloor topography. It is shown that when we combine gravity data and ship borne track our result improve 7 m with comparisons to shipborne track only.

Tree detection using aerial sensors in early decades was focused by many researchers in different fields including Remote Sensing and Photogrammetry. This paper is intended to detect trees in complex city areas using aerial imagery and laser scanning data. The methodology used in this paper is a hierarchal unsupervised method consists of some primitive operations. This method could be divided into three sections، in which، first section uses areal imagery and both second and third sections use laser scanners data. In the first section a vegetation cover mask is created in both sunny and shadowed areas. In sunny areas Normalized Difference Vegetation Index (NDVI) and in shadowed areas a Shadow Index (SI) is employed to obtain vegetation cover mask. This mask contains grasses and bushes that should be eliminated in the other two sections. In the second section Rate of Slope Change (RSC) is used to eliminate grasses. Such areas that their RSC is below a threshold is eliminated. In the third section a Digital Terrain Model (DTM) is obtained from LIDAR data. By using DTM and Digital Surface Model (DSM) we would get to Normalized Digital Surface Model (nDSM). Then objects which are lower than a specific height are eliminated. Now there are three result layers from three sections. At the end multiplication operation is used to get final result layer. This layer will be smoothed by morphological operations. Our result has a good rank in comparing to other methods in ISPRS WG III/4، when assessed in terms of 5 indices including area base completeness، area base correctness، object base completeness، object base correctness and boundary RMS. With regarding of being unsupervised and automatic، this method is improvable and could be integrate with other methods to get best results.

In recent decades، SAR sensor for specific reliability and imagery at night and influence in cloud، is to be attention in remote sensing scientific centres. Because accessing to the SAR image and data in Iran is difficult، it is a challenge in Iranian space agency for SAR simulation and designing. In comparison of SAR with radar، A SAR sensor transmit thousand pulses in second and received them to making raw signals. The raw signals are processed in range and azimuth compression to making the SAR image with better resolution than radar. Many different parameters effect the Doppler centroid frequency. Earth rotation is one of these parameters that effect the azimuth processing. This paper uses a method based on the rotations of the sensor axes to reduce the earth rotation effect on SAR data. The advantages of the method is making process simple for final image with less distortion. This process lest the error due to range migration in line by line processing in azimuth direction.