Today, tourism as one of the main sources of income, has a major role in the economy in the countries with high potential in terms of tourist attractions (natural, social and cultural) have been more interesting. Iran is one of the top ten countries in the world is enjoying the attractions and Khorasan is one of the most attractive regions of the country. Khorasan Razavi province with about 456 points of historical tourism, natural and religious tourism is one of the attractive areas of the country. In addition, the number 30 has been detected in the area of tourism. This appeal requires consideration and planning. So is it with the right capacities to plan accordingly to enjoy the features and attractions of each region to best use And can be used to develop the province. Cartographical paper tourism development model in Khorasan Razavi province With Gunn model )1979) and is presented using GIS. At the beginning of the tourist attractions of the province was prepared to identify and map its spatial distribution. After a variety of attractions in 9 categories based on valuation models, participants in the AHP model of Khorasan Razavi province in tourism zoning. Top rated on the basis of political divisions in order to benefit from the attractive city of Sabzevar, Mashhad and Nyshabour was dedicated. Finally, based on the classification of each city's large cities were normalized and actual positions. It also displays the rank of a zoning areas also see the value of the various attractions that the results can be based on the amount and level of planning policies in the area of each action, though it can be but different interpretations of the zoning presented as a suitable and efficient model in the Spatial planning of tourism and the macro level, the tourism sector, especially tourism will be useful for policy makers.

Automatic identification and localization of Cartographic objects in aerial and satellite images have gained increasing attention in recent years in digital photogrammetry and remote sensing. Although the automatic extraction of man made objects in essence is still an unresolved issue, but also the man made objects can be extracted from aerial photos and satellite images. Recently, the high-resolution satellite images, typically at most 3 meters in panchromatic band ground sample distance (GSD) and up to four multispectral bands in the visible and near infrared spectrum, are suitable for detection and identification of objects. This paper represents a new algorithm for identification of Cartographic objects based on Artificial Neural Network (ANN). The algorithm is divided in two modules: image simplification by the Wavelet transform, Mathematical Morphology (MM) operators, and identification of object by the Kohonen Self Organizing Map (KSOM) and split and merge method. The study area included two parts of an orthoimage from Kish, IRAN.

Self-Organizing Feature Maps (SOFM) are a category of artificial neural networks with a special ability in pattern recognition and data clustering using attributes of data points. In this study, ability of Kohonen self-organizing feature maps has been assessed in Regionalization of Aras watershed in order to perform regional flood frequency analysis. Results showed SOFM can be used as an efficient tool for data clustering and Regionalization of watersheds. Furthermore the results showed that the cluster validity measure is equal to optimum value for Regionalization of Aras watershed, when the number of regions is equal to 4. Also heterogeneity measures are equal to optimum values, when number of regions is equal to 2 or 4. However, when number of regions is equal to 2, largest regions can be formed.

The Sistan & Balouchestan province is extensive, this factor has caused it variety climate. The climatical Regionalization of Sistan & Balouchestan conducts with new methods of Regionalization such as factor analysis, clustering and autocorrelation. For this purpose selected 20 variables of 10 stations. To investigation on climate province with factor analysis method shows that 5 factors make climate of Sistan and Balouchestan. These factors to arranged atmospheric humidity, precipitation, temperature, sunlight, wind and thunder import respectively. In the south of province such as Oman coastal humidity and cloud are important factors to determination climate. In the southern Balouchestan temperature, sunlight and thunder determined characteristic of climate of this region.  Windy dusty factors are characteristic of the north - east corner. In the northern of Balouchestan precipitation and thunder are important factors to determination climate. The sunlight plays a basic role to making climate in the east part of province (Saravan). One of cluster analysis on 5 climate factors determined that exit five region climates. At the end, the province divided into three regions with autocorrelation methods.

According to mean monthly temperature data of 338 synoptic and climatologic stations of Iran eight different temperature region have been recognized in Iran. These regions in reference to mean annual temperature of Iran (18°C) have been named as:-South western warm region-Cold region (sloppy areas) -Peneplain cold region-Coast of Persian golf warm region-Temperature glossies-Temperature region (Khazar)-Warm plains-Cold mountainsA cluster analysis applied to theses regions showed that there are three temperature season: Cold season, Warm season and Transient season.

The study of the groundwater resources and their properties are very important due to the vast desert areas and arid conditions. Given the current situation in Iran, the water supply is one of the most important territorial and environmental problems. In this study, groundwater resources were surveyed and mapped in Yazd Province and their properties were modeled to determine their effectiveness for grazing and agricultural activities. The main objective of this study was to develop and establish groundwater geoinformatics and Cartographic monitoring of the meteorological data and groundwater formation. Also, the climatic characteristics were evaluated as determinants parameters of groundwater flow to measure its parameters variations. The thematic charts and geoinformatics maps were provided. Profile software was used for modeling microclimate and groundwater flow’s parameters, like groundwater level and moisture transfer for several decades. Priznak model was used for comparison and multi-parameter analysis of specified profiles and their classification. Finally, different regions of Yazd Province were mapped and classified with different degrees of possibility for grazing and agricultural activities. Results showed that groundwater levels in the study territory are at depths ranging from 40 to 145 m. According to the results, it was observed that the changes in groundwater level and microclimate can be used to evaluate the land capability for grazing and agricultural activities.

Most heavy storms result in destructive floods. One of the basic elements in analyzing floods in watersheds without data is hourly storms. The Determination of the storm of the watershed needs regional analysis of storms and transferring them to the gravity center of the watershed. Maximum daily precipitation ( 24 P ), is the most accessible storm in any region, which can be converted to hourly precipitation. The analysis of the point and regional 24 P is one of climate studies requirement. Regionalization of 24 P , can be an influential step toward analyzing storms and floods. In order to accomplish such a task, two approaches are possible, one is using the old methods of geographical Regionalization and the other one is using the new methods like "Cluster Analysis" and "L-Moments Homogenous Tests". In this paper second approach was employed. All existing rain-gauge stations (N= 396) were considered and their available data were collected in this study. Basic tests were applied and 266 stations were removed due to the lack of the required conditions and only 130 stations were used in analysis. "Principal Components" method was used to omit the uninfluential variables (only 6 variables out of 21 were proved as basic and important). "Hierarchical Clustering" was used in the process of Regionalization of the stations indicated of seven different regions. These regions were distributed in different locations throughout the country and the Regionalization map is presented. The "L- Moments Homogenous Tests" were also employed for further indication. According to the final results, the Regionalization of 24 P of Iran's rain-gauge stations can be defined as 7 homogenous regions.

Rainfall temporal pattern has a marked influence on design of dams, urban water harvesting, culverts, drainage design, flood potential and soil erosion. In this research we used data of 146 autographic rainfall stations of Iran to implement the rainfall temporal pattern. Rainfall depth were calculated for each time interval from rainfall charts and were categorized to four quarters. The ranking method was used to arrive at rainfall temporal patterns corresponding to time intervals of 1, 3, 9 and 12 hours. After normalizing the rainfall mass curves, every quarter of rainfall was ranked, number 1 for the highest. The final pattern was derived by averaging the quarter ranks and percentage of rainfalls corresponding to each duration. Adopting Ward method, 5, 9, 9, and 8 homogeneous regions were detected for short (<3 hr), medium (3-6 hr), and long (6-12, and>12 hr) rainfall time period, respectively. Design rainfall temporal pattern was . derived for every homogenous zone. There is a danger for mis-used temporal pattern by type patterns.