Journal of Spatial Analysis

---

The best path to development is the primary focus on the potentials and threats of the environment and accordingly efficient use of the land. In this regard, it has a closely relation between agricultural and rural development and natural resources. The type of land use is a main factor in soil erosion and sediment production in the watersheds. In this research, it has been studied and evaluated the soil erosion in the Aleshtar plain catchment with aim of developing agricultural exploitation.

This study is based on PSIAC model. The PSIAC method has been designed based on the estimating of sediment potential with 9 important effective factors contains surface of the earth, soil type, weather conditions, runoff conditions,  topography,  land cover, Land use, current erosion condition, slope of river erosion and sediment transportation in the soil erosion. In the process of this research using geographical information system (GIS), the mentioned data analyzed, integrated, and finally layers of information were prepared. Followed by extraction of units, erosion zoning of the studied area has been implemented.

The total area of the studied area is 80305 hectares and is located in the northern parts of Lorestan province (southwest of Iran) and geomorphologic features are  almost mountainous and 39.65% of their area are mountains and hills. The maximum altitude is 3600 meters; the minimum is 1500 meters. and the average height of 2116 meters. Its climate type (based on De Marten method) is Mediterranean climatic pattern exists and  the average annual rainfall is 506 mm. The Aleshtar City is the only urban center in the area but there are 208 villages. The economy of the settlements is based on agriculture (farming, gardening and animal husbandry).

     Based on the findings of this research, 37.92% of the total land area of the basin is eroded (classes I, II, III). The land consists mainly of low slope and plain basin and is suitable for plantation (I). In this zone, 98 rural settlements (47.11%) are located. Relatively deep soils and flat are the features of these lands so the rate of erosion is low (II). 84 rural settlements (40.38%) are classified in this class. Shallow soils, these lands need to have conservation measures and can be managed under the operation of arable, rangeland, forest and resorts (III). 1 rural settlement (0.48%) is located in this class of erosion. 62.09% of the total basin land is located in the classes IV and V. A total of 25 rural settlements (12%) are located in this class. These lands under certain conditions can be planted; because erosion in the land is relatively high and the limitations in comparison with class III is more. Therefore they need more protection operations for exploitation. Also in these lands that are located in the high topography of the basin; erosion is extreme (Class V), which makes arable exploitation impossible.

    Generally the land use in Aleshtar basin is faced to erosion limitation, so the control of the soil erosion and soil conservation and water resources management are essential. However, the locations of the most rural settlements were based on low to moderate erosion zones which indicates that the ancient has had a traditional preparatory thinking.

    As a general recommendation, it can be said that in any location, including rural and urban settlements, along with the development of agricultural activities, attention to the erosion and zoning is essential.

---

Introduction
Changes, although low in temperature, change the occurrence of extreme phenomena such as droughts, heavy rainfall and storms (Varshavian et al., 2011: 169). Reducing the daily temperature variation has led to a reduction in the frequency of occurrence of temperature minima, especially in winter (Schiffinger et al., 2003, p. 51-41).
Material and method
The purpose of the present study was to investigate and predict the risk of monthly rainfed temperatures on horticultural and agricultural products in northern Iran. For this purpose, first, the data of the temperature of the whole station were obtained at a time interval of 30 years. Then, using Anfis's adaptive neural network model, data were collected for prediction and prediction for the next 6 years. Then, to measure the land suitability of the northern strip Iran was used for cultivating according to the predicted data using two models of Vikor and Topsis.
Conclusion:
In recent years, damage to agricultural and horticultural products has been increased due to temperature fluctuations. Accordingly, in this research, the prediction of the risk of monthly rainfed temperatures on horticultural and agricultural products in northern Iran has been investigated. Based on the predicted data, the minimum temperature of the Gorgan station was the lowest educational error with a value of 0.10 and at the maximum temperature, the lowest error was 0.015. Finally, in Golestan province, the maximum temperature And at least both are weak in the incremental state. Minimum and maximum temperature of Bandar Anzali station was the lowest educational error with the value (0.013, 0.10). In Gilan province, the maximum temperature peaks and at least both are in incremental conditions and the maximum temperature has a higher intensity. Be The minimum temperature of the Babolsar station was the lowest educational error with the value of 0.019 and at Ramsar maximum temperature, the lowest error was 0.016, and Mazandaran province exhibited maximum and minimum temperatures at both incremental and minimum levels Temperature showed greater intensity.
Results:
According to the findings of the study, with respect to the friction frain modeling, the maximum temperature showed the lowest defect compared to the minimum temperature. In Golestan province, the maximum temperature peaks and at least both are in weak increment, but in Gilan province, the maximum temperature peaks and at least both the maximum and maximum temperatures are higher. Mazandaran province showed maximum temperature and minimum temperature in both incremental and minimum temperature conditions.
 

---

Assessment of the Probable Impacts of Land Use Changes on Water Quality in Shadeghan
Wetland Using Remot Senseing Data
 
In this research, the evaluation of possible effects of land use change on water quality in Shadegan wetland has been provided with the help of remote sensing data. The purpose of this research was to evaluate and compare user variations in 2000 and 2015 using Landsat satellite imagery (with ETM and OLI sensors) from the study area and processing them in the ERDAS software environment using the unstructured classification method during a period of 15 years old has been investigated. To determine the cause of the changes occurring in the wetland, the water quality of the wetland was evaluated through the help of modeling. Vegetation in the wetland has been rising rapidly, indicating water pollution, an increase in the nutritional status and the early disappearance of this international wetland. With the help of this article, it can be admitted that the development of agricultural lands around the shadegan wetland from 2000 to 2015had caused an increase in pollution in the region, according to available agricultural wastement containing  quantities of herbicides and pesticides which has led to an increase in the growth of algae in the wetland, which has led to an increase in temperature and eventually the death of wetlands and aquatic animals so after selecting images and assign them in 5 classes, the change wetland  maps were obtained during a 15 year various sources were used to determine the best regression model for determining water quality changes in the following, the images were placed in the models and their mean and standard deviation were obtained. The result of the research showed that the Landsat sensor shows the water quality well and can be used to determine the changes. The development of agricultural lands leads to an increase in the eutrophication phenomenon in the wetland and, in the end, reduces the quality of water indicators. In the end, causes quality loss of water.
Key words: Assessment, Land Use Changes, Water Quality, Shadeghan Wetland, Remot Senseing.