نشریه مهندسی نقشه برداری و اطلاعات مکانی
سال سوم شماره 1 (پیاپی 9، اسفند ماه 1390)

Six conformal map projections, including UTM zones 38 to 41, LCC2SP and obsolete TM, are mostly used in Iran. Since some provinces extends to more than one zone, optimum selection of a map projection that lays minimum distortions is the most challenging problem in several mapping organizations of Iran. Choosing LCC2SP map projection is the usual approach adopted by mapping organizations to overcome the problem. Nevertheless, UTM map projection has lesser distortion in some provinces as our results illustrate. The aim of this paper is to recognize the optimal map projection with minimum distortion from mentioned map projections. Therefore, the amount of distortion is computed in different areas via the scale factor formula of each map projection. Finally, the map projection, with minimum distortion in the whole area of a province, is introduced as an optimal map projection for that province. For instance, if Fars province, which lies in UTM zones 39 and 40, is mapped by UTM 39, it will be represented with minimum distortion. Using optimal map projection for each province results in the reduction of the distortion and consequently, the produced map will be more accurate.

Transportation vehicles, especially taxis, which are equipped with GPS, are moving sensors, mining roads traffic. The transportation vehicle (taxi) drivers are skilled drivers who are usually experienced in finding the fastest route from a place to a destination. In this paper by mining the movement history of transportation vehicles, a user with the predefined source and destination points and the time of departure, is provided by practically the fastest route. The utilized approach is the use of a landmark graph that its nodes are road segments that are traversed by vehicles frequently and in that, the intelligence of drivers and dynamic properties of streets network are modeled. Based on the landmark graph, we take advantage of a two levels routing approach to compute the efficient path. The data being used are the trajectory of 140 vehicles moving in the city of Tehran in the period of 30 days. In comparison to other approaches such as, speed constraint, the employed method has higher performance in terms of processing time and the proposed route derived from the system has less travel time.

Safe driving along a road depends on two main contexts, the situation of vehicle against other vehicles and transportation infrastructure. In this paper firstly a method for recognition the spatial relations between two vehicles introduced by means of zone-of-influences, and XML based self-description documents serves for storing vehicles context. Second, a high level of detail GIS-T data model required for capturing context information of transportation network. For this part a lane based arc-node data model proposed in relational database. Reasoning with excessive parameters makes a system complex, two terms for preventing this problem introduced during this paper. Logical distance between two moving objects is the first one, and safe speed according to the current transportation infrastructure condition is second one. Finally a rule based engine for supporting reasoning based our offered contexts is described, that subsequently spatial services like caution alarms can be deliver to driver at risky situations.

Airborne gravimetry is the most efficient technique to provide accurate high-resolution gravity data in regions that lack good data coverage and that are difficult to access otherwise. With current airborne gravimetry systems, gravity can be obtained at a spatial resolution of 2 km with an accuracy of 1-2 mGal. It is therefore an ideal technique to complement ongoing satellite gravity missions and establish the basis for many applications of regional gravity field modeling. This paper presents the history, basic concept and applications of airborne gravimetry. Moreover some commercial airborne gravimeters with their specifications are described.

The use of digital imaging cameras for aerial photogrammetry mapping has recently been introduced in the world and has become a practical aspect. In recent years, the maps from aerial photographs using digital systems have expanded dramatically, so that a large volume of GIS maps are prepared by them. This study is a brief explanation about the digital aerial cameras and a difference between them and analog cameras is introduced. Available technologies in imaging systems such as frame size, data acquisition methods and number of imaging sensors, are also being studied. Then, the variety of digital cameras used in aerial photogrammetry based on their quality and design parameters, are compared with each other.

Among the various reasons of accidents, some of them are under the influence of the outside environment of vehicle. The accident site is an important parameter in determining and resolving these factors. The same effect of environmental factors on different vehicles, causing spatial systematic behavior in accidents. Spatial point of view, the systematic behavior of point events such as accidents tend to cluster formation is shown. The use of cluster detection methods and spatial statistics such as K-function will be provided a useful tool for identifying accident-prone areas with a peripheral origin. Since the road accidents occur on the network, instead of using the K-function statistics in Euclidean space, of statistics based network K-function is used. Based on Monte-Carlo simulation, distribution of accidents on the three traffic areas are obtained and compared with the actual sample. The results show a tendency to cluster and systematic behavior in the areas of environmental factors such as the geometric imperfection of road.

Spatial data infrastructure (SDI) plays a significant role in sustainable development. SDI tries to establish an effective communication between people and geospatial data through proper policy making, standardization and network access providing. SDI consists of two main parts namely geospatial data and sharing it. From national security point of view, SDI is part of essential infrastructures and resources of each country. Since data provided through SDI is of utmost importance, taking security consideration into account is crucial. However, systematic approach forces us to consider SDI as an inseparable whole. Therefore, we cannot consider security as a separate part that should be added in later phases. In other words, security considerations are inner parts of the system. Regarding the special importance of spatial data in national security, we have debated security considerations in planning and implementation phases in the research.