نشریه مهندسی نقشه برداری و اطلاعات مکانی
سال سوم شماره 4 (پیاپی 12، آذر 1391)

Digital Elevation Models (DEMs) are one of the most important kinds of geospatial data in Geospatial Information Systems (GIS). DEMs contain different types of errors caused by sampling, measurement, and reconstruction processes. So accuracy is considered as one of the important attributes of DEMs. The errors can be classified into three types including random, systematic, and gross. This paper presents a new algorithm for detecting gross errors of irregular DEM data using Artificial Intelligence (AI) algorithms. The proposed gross error detection method are characterized by a common localization procedure: entire dataset was examined by consideration iteratively only a small subset at a time; for each step the data belonging to a moving square window was taken into account and each dataset was separately handled. In each window a bilinear surface was fit to fully surrounded points and the residual for each point was estimated. By the use of Genetic algorithm, it was tried to minimize the sum of squared residuals in order to detect points with gross error. The results showed that the proposed gross errors detection method is more effective and feasible than existing algorithms such as data snooping.

As positioning systems have developed and become available to civilians, navigations systems have been produced and available to use for the public. However, navigation systems face a very important challenge of matching position data retrieved from a positioning system on the digital map of the navigation system. This problem is caused due to independence of positioning systems such as Global Positioning System and gyroscope from digital maps which are mostly produced by photogrammetric procedures. In addition to navigation, the problem also happens in traffic probes for measuring road speeds, producing statistical models of traffic delays, finding time-optimal driving routes, collision avoidance systems and etc. In this research, different methods of map matching since 1986 are taken into consideration. These methods are categorized from different aspects and a brief description of how each method works is also provided. Furthermore, the advantages and disadvantages of each method are studied.

The shocking consequences of disasters and natural hazards have already proven the urgency and necessity of disaster management and emergency response. Preparedness of Responsible Organizations Plays an Important role in mitigating impact of natural hazards. Timely and Updated environmental information is so helpful in effective response and efficient actions in disaster management systems. With the ongoing development of cheaper miniature and smart sensors; abundant fast and ubiquitous computing devices; wireless and mobile communication networks; and autonomous and intelligent software agents, the Sensor Web is rapidly emerging as a powerful technological framework for geospatial data collection, fusion and distribution. In this research we present a Standard framework based on sensor web concept to monitor and analyze Sensor data and notifying responders when alarming condition occurred. We design this frame work in an interoperable way to satisfy necessities of disaster management systems.

Unmanned vehicles, with names and terms, such as robots aircraft, airborne platforms without a pilot, RPVs, RPA, UAV and other terms are introduced, all of which suggest an agent-based platform that are controlled by a pilot out of it. As the name of the UAV, an unmanned aerial vehicle can be directed manually, semi-automatically or automatically. The important characters of UAV are less complexity and weight in comparison of other vehicles. The main applications of UAV are using them as a platform aerial photogrammetry in Geomatics. In this paper, the importance and potential benefits of using these platforms are studied and, research projects in this field have been investigated.

Star catalog containing thousands to hundreds of millions of stars in different sizes are used in different applications as an important database. Star catalogs’ data are collected by satellites or ground-based telescopes and typically include estimation of the stars’ positions (right ascension and declination) with positional accuracies, the magnitude of each star in the photometric bands, proper motion, photometry data, the stellar parallaxes, etc. In this study, a list of widely used or well-known catalogs for astronomical data is introduced and their properties such as the number of stars, positional accuracy, and range of stellar magnitudes have been compared. Moreover, some of the concepts and terms used in astronomy are presented in this study. Base on the results, Hipparcos catalog is a comprehensive database that includes all of stars’ information for most astronomical applications.

According to the increasing number of digital geospatial data, it is necessary to study the international standards for collection, processing, and quality control of geospatial data intended for entry into the National Digital Cartographic Data Bases. In this paper, after introducing the international standard organizations, such as USGS, FGDC, ISO and OGC, a complete review is performed on the standards for generation and processing of digital elevation models. These standards are intended to facilitate the interchange and use of DEM data. DEM collection and editing systems must produce data that are compatible with other production systems, not only in the Federal sector but also in other government and private sector organizations. Because of rapidly changing technologies in the mapping industries, these DEM standards cover a broad range of collection systems and related accuracy levels. It is the intent of this standard to set common standards that will ensure that data will be acceptable for entry into the national digital databases.

Nowadays, sustainable development theories emphasize that providing a good background for economic and welfare growth with spatial planning is necessary. The accessibility of people to welfare centers by proper utilization of sustainable development infrastructure networks, include transportation networks, has been facilitated. This research aims at assessing the functionalities of the GIS network models in creating best links between settlements for rural sustainable development. The main goal that was sketched for my thesis was to apply network model in GIS environment in order to model spatial hierarchy and spatial links of rural settlements. The hypothesis was that GIS network could effectively propose proper locations of establishing service centers. Therefore, such models can be applied in detection of rural settlements where are poor in receiving special services. Consequently, flow of facilities and people traveling time for receiving those services would become optimized. The outcome of the thesis has shown that using GIS network models in combination with rural planning theories and linear programming models; it is possible to detect areas with weak accessibility to facilities. Furthermore, we used. NET and ArcObjects programming in order to develop a new model in the ArcGIS environment. This model enables us to locate the services and facilities at the best place in a way that the settlement relationships would become most effective. Finally, the developed model is evaluated in a pilot project in South Khorasan one of the provinces in Iran. The results have proved the suitability of GIS network models in rural settlement planning.