Iranian Journal of Remote Sensing & GIS
Year:2009 | Volume:1 | Issue:2|Papers Count:7

Barika area is located on south of Western Azerbaijan, Province, 27km. East in Sardasht .Gold-silver mineralization is located in a Cretaceous metavolcano-sedimentary sequence at northwestern Sanandaj-Sirjan zone. Major units in this area include Cretaceous Submarine volcano-sedimentary rocks. Host rock of mineralization is andesite to tracky andesite which is completely in Barika shear zone.The objective of this research, is finding hydrothermal alterations Zone by remote sensing technology and best processing technique of ASTER and ETM satellite image.In this research, different processing of satellite image such as Band Ratio method, principle component Analysis (PCA), Mineral Spectral Mapping have been used.In order to recognize alteration area, the authors used USGS laboratory spectral and Match Filtering algorithm and spectral of image for identification and delineation of the alteration minerals associated with gold mineralization. The obtained results of processing satellite images in this area showed different minerals such as sericitic, chloritic, calcitic, epidotic alterations, and Iron oxide minerals. Intense sericitic alteration is in the center of alteration system and chloritic, calcitic an epidotic alteration is in surrounding area. According to the field studies, Iron oxide minerals that observed with sericitic alteration are due to oxidation of sulfide minerals in mineralogy zones.The obtained results of processing satellite images in this area could be suitable guides for better discovery of this type of mineralogy in similar areas.

In order to enhance the available methods of feature extraction through non-parametric weighting procedure, an optimization method is introduced in this work. This method can be applied to the problems involving pattern recognition in high dimensional spaces. The method is based on the expansion of non-parametric scattering matrices where their average parameters are calculated for each sample separately using sum of the weighted samples of the other classes. The weight of each of the samples is calculated based on their Euclidean distance from the sample under the study. However, it is not possible to only express the scatteredness of the samples by this parameter alone haply the locations of these samples are important too. That is, it is possible sometimes to have two samples having equal Euclidean distance from the main sample while their degrees of dependences to this main sample are not the same. For instance, it is possible that one of these samples be completely dependent while the other is totally independent of the main sample. On the other hand, the degree of dependence is linearly related to the main sample and hence the linear combination of samples is important in determination of the scattering degree. Using these important parameters, the results of non-parametric weighted feature extraction shows some improvement. In the present work, using this important factor (Linear Combination), the method of non-parametric weighted feature extraction is enhanced and named Linear Combination Non-parametric Weighted Feature Extraction (LC-NWFE). The results show that the suggested method in most of the classes especially in the critical classes where their spectral similarities are high, works much better than NWFE method. The best result achieved was better than 82% for overall accuracy with a kappa accuracy of better than 80%.

Among all kinds of natural hazards in the world, flood is probably the most devastating, wide spread and frequent one that often results from excessive rainfall within a short period of time. Due to excessive rainfall during warm seasons, Golestan province has encountered with severe floods in recent years. Since rainfall intensity in this area is variable, the rain gauge cannot illustrate this variation, so that using remote sensing for rainfall estimation is inevitable. Satellite rainfall estimation algorithms frequently use infrared (IR) and Passive Micro Wave (PMW) data. IR data have high spatial and temporal resolution but cannot penetrate clouds; whereas PMW data can penetrate and estimate rainfall more accurately but have lower spatial and temporal resolution. Thus, by combining these two datasets, the advantage of reducing deficiencies can be achived. This paper describes the ability of combined METEOSAT and TRMM data for rainfall estimation of 10th of August 2005 and its application in flood monitoring in Golestan province. For flood monitoring the Geospatial Stream Flow Model (GeoSFM) was used. The correlation between predicted and rain gauge data was found to be 0.533; also calculated RMSE and MAD were 9.74 and 6.67 respectively. It was also distinguished that as the most sub-basin in the catchment had dried soil before raining in 10th of August, eastern and southeastern parts of the catchments (the place of exteme raining) were expreinced high flow of runoff. Hydrograph also showed that the maximum runoff occurred at 10th of August and after that time runoff decreased, but the decreasing slope is slight. The reason for this behavior seems to be the soil moisture and reduction in soil penetration due to extreme rainfall.

Spatial dimension of the most urban planning models are based on the zonal systems. This kind of models assumes that all attributes are uniformly distributed all over a zone and spatial interaction between zones is established via linked only to the centroids of the zones. Zone-based spatial models pay no attention to special characteristic and distribution of different land uses and transportation facilities inside each zone. Therefore, this kind of models can not satisfy current planning issues and are too disaggregate to counter new challenges in urban planning activities. In this research, a micro-simulation model is proposed for accessibility evaluation with focusing on integration of two major urban planning sub-systems: land use and transportation. The characteristics of various land uses and transportation policies are studied to be included in the accessibility evaluation model. Specific characteristics of various land uses are considered during the development of the model. In this research, various land uses are categorized in two classes: multi-facility and single-facility and different accessibility evaluation models are developed for each land use class. Parcel is considered as the smallest planning unit in the model and geographical information system and its analysis tools are used to test the result of the model in a case study area in Shiraz city. The results show that the model is robust to clarify different aspects of accessibility. The results present useful information to urban planners and show them various shortcomings regarding both land use and transportation systems in the case study. Micro evaluation of accessibility, as one of the most important parameter in a land use-transportation integrated model, supports urban planners to get proper decision to tackle with the problems related to both urban land use and transportation systems.

Management of some facilities such as transportation is one of the most important applications of geographic information systems. In this field, the network capabilities of GIS such as computation of shortest path could be very useful. There are a variety of studies and researches on developing algorithms for shortest path finding. However, less attention has been paid on modeling the uncertainty of determined optimum path. The uncertainty of a determined optimum path is relevant to the accuracy of the input data. For example, when distance is considered as a criterion for determination of optimum path, the positional accuracy of the road network affect the reliability of the determined optimum path. This paper intends to model the uncertainty of optimum paths, where the optimality is determined based on distance and travel time criteria. Error propagation rules and fuzzy set theory were used respectively to model the uncertainty for distance criteria and travel time criteria. The developed model was implemented and tested for a case study in Iran. The results showed that by including uncertainty in a path finding problem, users can determine optimum paths, which may be a little bit longer (from length or travel time perspectives), but more reliable than the shortest or the fastest path. Using a reliable optimum path is preferred by many citizens (and especially emergency services) in comparison with uncertain shortest/fastest path.

Interpolated data are usually used in many engineering and planning activities such as geology, climatology, natural resources and hazard management. Root Mean Squared Errors (RMSE) is the most frequently used indicator for error assessment and statement. Unfortunately, this indicator is mainly non-spatial and it does not provide the required spatial details about the local reliability of the interpolated layers. Therefore, development of more efficient and practically useful methods for spatial evaluation and visualization of interpolation errors are of prime importance.In this research, after reviewing some of the important limitations of RMSE and interpolation methods, a practical approach based upon the triangulation, for modeling and mapping of the reliability of interpolation has been proposed. Triangles formed by application of the delauney triangulation to sample points have been used as the main spatial entities. Three characteristics of triangles including the area, shape (modeled by the ratio of perimeter to area), and variance of the values of their 3 corners have been used to model the interpolation errors in triangle levels. The reason for choosing these parameters is their important role in creation of errors, as well as simplicity of their calculation in GIS environment. Point data of elevation from part of Tehran metropolis has been used as the case study for examination and demonstration the usefulness of the proposed approach. Modeling has been based on the least squares fitting in a multiple regression framework. The fitted model has been used for prediction of interpolation errors. Where its validity has been evaluated by the independent, well distributed test sample points with a known elevation.Results of the proposed approach have been encouraging, and close relationship between the actual and predicted (by model) errors have been observed. Production of the map of interpolation errors, as in the proposed approach, can be useful for efficient use of the interpolated data. Also, these maps can be used as useful guides for collection of additional samples where the improvement of the interpolated data quality is required. More close examination of the proposed approach in a wider and diverse environmental condition has been recommended.

Maps are the most important medium for presenting navigational information to drivers. Quality of maps, presented to their users, has a direct impact on the usability and performance of a car navigation system. In this regard, displaying maps adapted to user's environment and their condition is critical. Users in different context need maps with various scales -zoom level and level of details- to fulfill their information requirements. Since, using a car navigation system is not elementary task for drivers, selecting and presenting maps with proper zoom levels and level of details must be performed by the system intelligently and automatically. In this paper, we offer a method to select the two mentioned factors automatically to present legible maps in different context. Values of these two factors are depending on user's context, so context aware computing has been used in the proposed method. Context aware computing is a computing that enables systems to acquire current user’s context and adapt its behavior accordingly. In this research, various contexts that may have an impact on map scale are studied and then an approach to select proper scale in such contexts is proposed. In addition, based on context aware computing concept an adaptation model is offered that enables system to determine proper map scale in different context. As a proof of the idea, a prototype car navigation system- with the ability of displaying maps in appropriate scales with different context- is implemented and tested in parts of Tehran.