GEOGRAPHICAL DATA
Year:2016 | Volume:25 | Issue:99|Papers Count:12

The water salinity is the one of the important environmental marine factors and play important role in the Prediction of the surface ocean currents, spatial analysis of the fish aggregation, determination the density and studying its changes and also in ecological properties.This parameter change greatly with time and space and proper recognition is need to short time intervals measuring (monthly) for Multiple points of the study area.in the classic way, appraising one or more specific factors of water quality is expensive and spend great time and also is not good indicator for the whole area of a large region. But In recent years satellite technology and remote sensing are considered as appropriate tool for the assessment some of the water quality parameters, because due to the digital nature of this data, extensive availability, regular measurement, repeating data in the short time periods and spending less time and cost, can complete wide range of project.the purpose of this study is mapping sea surface salinity of Persian Gulf in iran and Gulf of st Lawrence in the Canada, using MODIS satellite data. in this regard a software produced in IRAN for the first time that can create salinity, temperature and density maps of sea surface In three different models with proper accuracy by entering the MODIS satellite data and field data.High ability and flexibility of artificial Neural Network in approximation of nonlinear and linear continuous functions in hybrid space, led this study to provide a new method based on using this network in which salinity map determines by a multilayer perceptron network.

Sustainable management of wildlife and natural habitats outcome of spatial, quantitative and qualitative studies of wildlife populations and habitats. Which highlights the importance of proper maintenance of existing data and organizing them to increase lifetime of such data to avoid duplication of resampling operations and to save budgets of wildlife conservation and management. So according to the advantages of using database management system for maintenance, usage and management of data, in this study we aim to design and implement spatial database of Khuzestan province wildlife. In order to design and implement the spatial database we used PostgreSQL/PostGIS object-relational database. According to results of our study, PostgreSQL/PostGIS (open source database management system) known as a viable option for the development of wildlife spatial data management capabilities. Also our study indicates that the designed management database system can support all possible queries related to wildlife spatial data, this system can also provide a solution to solve some problems related to management of large volumes of wildlife scattered data. According to the success of this research, we emphasized the necessity of attention to organize and manage the wildlife information and considered it issue in macro polices of Environmental Protection Organization of Iran. Finally, we pointed the necessity of creating and developing a universal database for the wildlife spatial data of Iran.

Shafts are one of the most important supplies of potable water, agriculture and industry.The quality of the water is the most important factor between these qualitative factors. Therefore the investigation and prediction of pollution is one of the managers and programmer’s purposes.In this research, Artificial neural network and geospatial information system were used to determine the pollution of these materials, magnesium in east villages of Golestan province during these years, 87, 88, 89, 90.In this model the artificial neural network by perspetron structure with hidden layers and several neurons were evaluated. In the present time, the underground water pollutions are increasing because of the chemical activities. Therefore it is require to investigate the vulherable regions of the area in order ro prevent underground water pollution.There are also different kinds of maps in this research such as: topography, geology, situation of shafts,… that were used in Arc GIS software to determine this underground water pollution and the suitable weight for the slightly parameter was specified in Matlab and the output achieved so that we finally could acquired the pollution maps by putting this output in Arc GIS.By observing these pollution maps and the available data during these mentiond years, we concluded that the rate of pollution was low and this could not be dangerous, because these polluted areas are vacant.

The main objective of this research was to determine Iran’s National Spatial Data Infrastructures (NSDI) readiness index, with the aim of identifying the basic restrictions that impede NSDI development. The framework of the research is constructed on the basis of survey and SDI readiness model. In this research, Iran’s NSDI according to a fuzzy-based model has been assessed using 16 decision criteria and five factors, including organizational, people, financial, information and technology factors. The data were collected through the questionnaire and interview with the experienced experts, who work in the government organizations, Universities, and private sector. The results of the implementation of the model demonstrated that Iran’s NSDI readiness composite index was 0.44. In addition, the assessment of the factors of Iran’s NSDI readiness showed that except technology factor, the rest of them were not developed well. Moreover, the status of the 75% of the assessment criteria was not satisfactory. Enterprise and private sector funding, individual leadership, telecommunication infrastructure, institutional leadership, umbrella legal agreement, politician’s vision regarding SDI, metadata availability, SDI culture/education, were identified as the main limiting criteria in the development of the NSDI. Despite the different types of the limiting factors of the NSDI development, Web connectivity, digital Geospatial data availability, human capital and Geospatial software criteria were evaluated at the suitable level of development. Besides, it seems that the non-technical factors (organizational, financial, human resources) were more important limiting factors than the technology factor in Iran’s NSDI development. At the end of the paper, some recommendations were presented to overcome the NSDI limiting factors.

The Distribution networks are the most important part of the services that distribute electrical energy to the consumers. The Problems about the information of location reference are consist of inaccuracy, the lack of control and the lack of access to the information are some of the technical problems. The complexity of updating information and the complexities related to storing the information are also other examples of these problems. The technical problems and not using of advanced systems in the field of aid, causes the prolongation of black out time.The aim of this study is modeling and implementation of a context aware system for a few services in the field of urban electrical distribution events. The urban electrical distribution networks are made up of different parts and equipments. The rescuer according to the available and accessible information of the network determines the type of failure. The type of failure and spatial position of the aid automobile are considered as user environment context and position context, respectively. Therefore, in this study, the contexts are divided in two main categories of position and network context. Finally, the implementation and testing of context aware system which is designed in order to help aid management of urban electrical distribution networks, will be examined. The recognition of contexts has a proper and acceptable performance and according to surveys done, 80 percent of information is presented on time and with proper accuracy.

This article seeks to identify the spatial pattern viability of rural settlements bordering areas of Hermand is to identify risk areas The method applied in this study is descriptive and analytical approach of the research .To analyze the spatial distribution pattern of viable villages in three favorable, average and unfavorable spatial statistical tests GEO DATM spatial statistical analysis and GIS software environment will be used to spatially pattern viability villages to identify high-risk zones and eventually be identified. The results show the viability of the desired range of 16 villages, 16 villages and 12 villages in the whole poor were in the moderate range. The results of the algorithm used to analyze the spatial distribution of insulin Moran viability in the region shows that 7 Cold cluster (habitable Low (LL), and 11 clusters of hot (high viability (HH) in the region were identified. The largest hot spots in the south of the city, and the villages located in this spot has high livability and are located adjacent to each other and the cold spots and the city center located in the South East. The results show poorer villages near the border of viability and cold clusters are concentrated in these areas and cold clusters are concentrated in these areas and Dependence on the agricultural economy and lack of water resources is plain in the northern city of viability are weaker .High-risk spots in the area of security instability in rural settlement could be at risk and consequently the settlements that are more appropriate and livability and in the vicinity of the spots with low viability are also at risk in terms of security and to review their viability will be affected.

In sustainable tourism development approach is not only the needs but also the needs of the market (necessities) of society and the natural environment also stressed occurs. Accordingly, the GIS can be used for many activities related to tourism, planning and modeling used. The purpose of this study was to present a model for the accessibility into the tourism attractions for the sustainability of the tourism axes situated in Isfahan Province. Given the parameters under study, the research was applied in terms of type and descriptive-survey in terms of methodology. This study aimed to present a model for the sustainability of the regions with the highest number of attractions and the concentration of tourism in one area instead of a point. Isfahan and Kashan cities (historical-cultural) and Semirom and Fereydunshahr counties (natural tourism) have the greatest tourism capacity of the Province, respectively. As per the findings of the study, based on “the shortest access route”, five categories have been considered for the sustainability of the main four tourism axes with the first category covering the potential regions to a radius of 60 min far from the main tourism axes. As per the results of the study, a distance up to 60 min is regarded as a distance which a tourist wants to trip by a vehicle to reach his/her desired attraction). Among the main natural tourism axes situated on the West (Fereydunshahr) and Western South (Semirom) of Province, In the historical-cultural tourism axes of Isfahan and Kashanmust be taken into account by the authorities in the tourism management field, and must be given special consideration by the Province’s tourism planners.

Digital Elevation Model (DEM) enables researchers to perform geographical researches in global and regional scales including global changes, natural disasters, environmental monitoring etc. Therefore, DEM data plays a key role in scientific researches. SRTM and ASTER GDEM are two elevation datasets that cover nearly the entire land surface of the earth and are globally available (for almost 80% of the earth). Thus, it is necessary to evaluate the vertical accuracy of such data prior their use and to select the appropriate data in term of the research target. ASTER based digital elevation model has spatial resolution of 30 meters, which seems to provide more precise elevation data than SRTM with 90 meters spatial resolution. Several studies have been performed for evaluating the accuracy of each of these two datasets in various countries of the world. The results of such studies indicate their advantages and limitations over each other. In this study, the vertical accuracy of these two DEMs are evaluated by ground control point in three zones of Iran with different topographic characteristics, which are Eastern Azerbaijan, Sistan and Baluchestan and Bushehr. Results show RMSE of SRTM for study area in Eastern Azerbaijan, Sistan and Baluchestan and Bushehr is 6.1, 7.4 and 2.9 meters and in ASTER GDEM is 8.7, 8.3 and 7.2 meters, respectively. So the STRM data has high vertical accuracy than ASTER GDEM in all three zones. The relation between vertical errors and land characteristics such as slope and aspect are studied and their results are presented in this study. Final results of the study indicates higher vertical accuracy of SRTM in comparison with ASTER GDEM in Iran and it is concluded that SRTM is a more appropriate choice for various applications.

Drought is a natural phenomenon that befalls nearly on all climatic zones worldwide. Because of especially susceptible to drought conditions and their low annual precipitation, the effects of this creeper and gentle phenomenon in arid and semi-arid regions are higher than other regions. For spatial analysis of drought in the present research, Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra satellite has been used Normalized Difference Vegetation Index (NDVI) and land surface temperature (LST) to calculate the Vegetation Condition Index (VCI), Temperature Condition Index (TCI) and finally vegetation health index (VHI) over Markazi Province, for the growth months from 2000 to 2014.Then drought severity classes extracted based on VHI maps into five classes:1-very high 2-High 3-moderate 4-slight and 5-no drought, and their variations surveyed with VHI time series. The survey of VCI and VHI time series showed that there are meaningful correlation between NDVI and LST. In certain years, they were corresponded to each other, while in other years they were one counter the other and their resultant determined the occurrence and severity of drought, which is reflected in the VHI. Based on results of this research, years of 2000 and 2001 had highest drought severity and years of 2004 and 2007 lowest. For growth months, May and August had highest and lowest respectively. With regard to drought classes, results consisted of: no drought (56%), slight (19%), moderate (15%), high (8%) and very high (2%).Comparison of this research results and National Meteorology Organization report demonstrated accuracy of remotely sensed index of VHI in monitoring of agricultural drought. Our study proves drought indices such as VCI, TCI and VHI can help to decision makers and planners by eliminate of point method weakness.

Soil salinity and salinization of lands, as one of the main problems of agriculture, has paramount importance and can be avoided with proper understanding of its progress. This is the first step in identifying areas of salt and salt mapping in these soils. With the development of remote sensing technology and efficient use of satellite imaging, this study compared the salinity maps produced by a variety of classification image algorithms (Maximum likelihood, Minimum distance and Parallelepiped) by Landsat5 TM satellite data in the East of Khoy. In this study, 269 soil samples were analyzed and the results obtained were implemented on TM image. For initial identification, topography maps, ENVI 4.8 software and satellite image processing were used and geometric correction was performed with specific locations using GPS. Selected train samples with good distribution in the image and salinity classes were prepared from 1 to 9 determined. Examples of each class of salinity were placed carefully with single pixel size in each image on the corresponding pixel and stored with ROI format, because they had the coordinates. The results indicate the existence of a correlation between bands 1, 4 and 5 TMimage with salinity data and classification algorithms using the Pixel-based method, the highest accuracy of the map is the maximum likelihood. For this purpose, indicators such as error matrix, Producer’s Accuracy, User’s Accuracy, overall accuracy and kappa Coefficient were extracted. This map is also consistent with field observations of different classes of soil salinity measurement and shows high accuracy of the algorithm among soil salinity maps. The aim of this study was to compare salinity maps prepared by these methods in the area with results of other researchers.

Accurate and timely estimates of potential evapotranspiration have Vital for water resource planning and agriculture. In this study, to estimate evapotranspiration of sugarcane in the warm season in Khuzestan province is concentrated. The data used includes air temperature, relative humidity, wind speed and sunshine since the establishment of the station until 2014. At first, reference crop evapotranspiration values using the standard FAO Penman Monteith calculated and then use the available crop coefficient, evapotranspiration of sugarcane is estimated at different growth stages. The results show that the average evapotranspiration of sugarcane in Khuzestan province in the early stages of 3.35 mm per day in June and In the middle stages of growth and in the final stages of 10.46 mm and 6.28 mm per day. The value of this parameter in July in the early stages of 3.59 mm and 11.23 mm in the middle stages and in the final stages of growth at a rate of 6.74 mm per day, respectively. Finally evapotranspiration of sugarcane in August in the early stages of growth 3.56 mm per day and 11.12 mm in the middle stages of growth and development in the final stages of 6.67 mm per day, respectively. The maximum daily and monthly evapotranspiration in July and minimize it happened in June. The highest daily fluctuations and monthly evapotranspiration of sugarcane in the middle stages of growth and lowest its growth occurs in the early stages.

Nowadays, integrating different kinds of data and images, achieved by the different remote sensing sensors are known as a suitable solution for extracting more useful information. This because of large range of aqucition images, digital format, and high temporal resoulation enable scinentits to extract information form land surface. The passive optical sensors have been used extensively in mapping horizontal structures. However, radar data could be used as a complementary data, since these data would be gathered in different climatic conditions in 24 hours of a day, as well as some geo and manmade structures have a specific response in the radar frequency. Furthermore, LiDAR data could gather precise measurements from vertical structures. On the other hand incorporating these variety of information and data for extracting specific urban features is curucial and challenging task. Hence, by integrating optical, radar, and LiDAR data more features and information would be prepared for different kinds of applications. For example some object may easily find in optic imagery but it is difficult to extract that object form LiDAR or RADAR images. Therefore utilizing procdure for fusing and extracting these object is inevitable. In this research, we used these datasets to detect buildings, roads, and trees in a complex city sense, i.e., San Francisco, by generating 57 features, and also by using the PCA and ICA feature extraction methods, as well as the well-known intrinsic dimension methods, including SML and NWHFC. Finally, the K-NN classifier was utilized in order to detect buildings, roads, and trees and grouping features according to the earned accuracies. Results show the high performance of the proposed approach and support our analyses.