نشریه مهندسی نقشه برداری و اطلاعات مکانی
سال ششم شماره 2 (پیاپی 22، خرداد 1394)

Producing a complete large scale environment model which enables access to geometric as well as visual information is required by most organizations. In this regard، the use of stereo panoramas is an image based solution which has attracted the developers and users of city maps. This is due to the fact that stereo panoramas offering visual and complete view of surrounding simply. There exist a number of techniques which are used to develop stereo panoramas and each structure has its own advantages and disadvantages. This paper investigates the possibility of using off-the-shelf stereo cameras in production of stereo panoramic models from environment. In this regard، the possibility of using stereo cameras in developing a stereo panorama system is studied and different issues to produce an appropriate 3D model are investigated. Finally، the accuracy of using these types of cameras in geometric measurement through generated stereo panorama model is evaluated.

This study investigates the potential of MODIS data for estimating Vegetation Water Content (VWC) using Vegetation Indices (VI) that work in VIS/NIR and SWIR spectral region and improving their performances with appropriate band selection. In fact the aim of this study is raising the possibility of the practical use of MODIS imageries which are available easily، for free and with high temporal resolution for estimation VWC parameter. The ground truth data which were used for validation، were collected from 31 stations in an agricultural area in the State of Iowa، USA. Among them، 21 stations belonged to corn and 10 stations to the soybean fields. Two sets of indices that work in the VIS-NIR and NIR-SWIR spectral region were calculated. By using the cross-validation the corn data were divided to 4 clusters and the soybeans data were divided in 2 clusters. Each time one cluster considered as test data and the other clusters as training. And thus by using the training data، scatter plots between VWC reference values and calculated VWC values using vegetation indices were sketched and linear regression was established. Then by using test data and R2 statistic the results were validated. According to the results، indices which use NIR-SWIR bands show better performance than indices that use VIS-NIR spectral range. In this study bands 5، 6 and 7 of MODIS sensors were used to calculate NDWI index that bands 5، 6 produced better results than band 7. Therefore، band 6 was used for the rest of indices. The results also showed that the experiment on the soybean fields were less reliable than corn fields because of low density and accuracy in soybean field data. The high potential of MODIS data to assess VWC was confirmed by comparing the results of indices and field data.

Because there are differences of scale، rotation and intensity and deformation caused by the high of the satellite images، matching is one of the challenging problems in remote sensing. This activity intensively is used in remote sensing for many purposes such as multi source classification، environment monitoring، change detection، image mosaicking، etc. Among the variety of matching methods، one of them is global matching by Hopfield neural network. This method is mainly applied in object recognition and close range dominant and up to now it is not evaluated on aerial and remote sensing images. Implementing the matching method using Hopfield neural network on remote sensing images is the main goal of this study. In research conducted، fifth-order Hopfield neural network is used to perform the projective invariant matching. This network with increasing number of points loses its speed and efficiency in matching. Therefore، in this paper by reducing the order of Hopfield neural network from fifth-order to second-order improves the efficiency and speed of matching method. Practical results on two pairs remote sensing images shows the efficiency of this method.

The use of open source software has been increased rapidly due to its various benefits. These days many open source software exist that provide different capabilities for users to handle with spatial data. The selection of an open source software with needed capabilities for special project and lack of any responsibility about these software from corporations، forces the members to use their experiences. The forums give these opportunities to users to transfer their experiences in global level through Internet environment. In this paper، three top open source software، QGIS، GRASS and gvSIG have been investigated using questions and responds in the important GIS forums. Also these software via forums and forums capabilities have been compared. The results show that QGIS is used more than the others. Also stack exchange is the appropriate forum for ordinary GIS users and OSgeo is the suitable forum for expert GIS users.

The ultimate goal of geophysical observations is determining geological structures from the geophysical data which is very difficult due to the complex structure of the earth’s interior. Retrieving the parameters of a fault through a set of its deformation observations is called “geophysics’ inverse problem”. In this article، the Artificial Neural Network as an evolutionary method are applied to retrieve the Qeshm fault parameters. In this research، in order to estimate parameters of the fault causing the earthquake، Insar displacement observations of the earthquake occurred on The 2005 November 27 in Qeshm and also neural network have been used. Deploying this approach in co-seismic displacement field of Qeshm leaded to parameter estimation of the fault with a depth، length، widths، dip angle، strike، slip، of 6. 1 km، 7. 4 km، 4. 6 km، 42 degrees، 251 degrees and 88 cm، respectively. Maximum difference of the reconstructed displacement field based on the estimated parameters on displacement field obtained by Insar is demonstrated as large as 1 cm in vertical direction and 4 cm in north-south direction. The results indicate that the artificial neural networks are trusted approaches in parameter estimation of faults.

In recent years، the acquisition and processing techniques of high resolution Digital Surface Models (DSM) have been rapidly improved. This will allow us to have more access in details as well as high elevation accuracy. Besides، Airborne LiDAR production as a well-known and high quality DSM is still unbeatable in elevation accuracy and highly produced dense point clouds. In this paper، the objective is to update an old but high quality DSM produced by LiDAR data using a DSM generated from high resolution stereo satellite images. A stereo-based DSM produced from Worldview –2 imagery will be used as new elevation database to update older DSM. A classification-base algorithm is proposed to extract building changes between DSMs in two epochs. For image classification procedure، the DSM and Worldview-2 orthorectified images from 8 spectral bands have been used as input data for a fuzzy-based classification method. Then، extracted buildings are classified into unchanged، destroyed، new، and changed classes. In this study a dataset related to Munich city، has been utilized to test the experimental investigation. The implemented qualitative and quantitative assessments demonstrate high quality as well as high feasibility of the proposed approach.

In recent years development of electronics and computer sciences conduced to significant progresses to create smart environments and systems. Ambient intelligence is one of the most paradigms of electronic and telecommunication environments. Ambient intelligence refers to an environment in which the people are surrounded by intelligent and intuitive interfaces embedded in daily-life objects around which assist them in an invisible and smart way and improve their lives. The main goals of this paper to introduce ambient intelligence are to recognize the role of spatial analyses to improve such intelligent environments efficiency and also to consider ambient intelligence environments as one of the infrastructures to implement Geospatial Information Systems (GIS). Despite the efficiency of this type of smart computing environments، there are some challenges which make it difficult to achieve all of their goals completely. This paper addresses the main properties، applications and challenges of ambient intelligence based on the literatures.