Spatial Distribution Analysis of Soil Properties in Varzaneh Region of Isfahan Using Image Processing Techniques

Introduction: Use of remote sensing for soil assessment and monitoring started with the launch of the first Landsat satellite. Since then many other polar orbiting Earth-observation satellites such as the Landsat series, have been launched and their imagery have been used for a wide range of soil mapping. The broad swaths and regular revisit frequencies of these multispectral satellites mean that they can be used to rapidly detect changes in soil properties. Arid and semi-arid lands cover more than 70 percent of Iran and are very prone to desertification. Due to the broadness, remoteness, and harsh condition of these lands, soil studies using ground-based techniques appear to be limited. Remote sensing imagery with its cost and time-effectiveness has been suggested and used as an alternative approach for more than four decades. Flood irrigation is one of the most common techniques in Isfahan province in which 70% of water is lost through evaporation. This system has increased soil salinization and desert-like conditions in the region. For principled decision making on agricultural product management, combating desertification and its consequences and better use of production resources to achieve sustainable development; understanding and knowledge of the origin, amount and area of salinity, the percentage of calcite, gypsum and other mineral of soil in each region is essential. Therefore, this study aimed to map the physical and chemical characteristics of soils in Vazaneh region of Isfahan province, Iran. Materials and Methods : Varzaneh region with 75000 ha located in central Iran and lies between latitudes 3550234 N and 3594309 N and longitudes 626530 E to 658338 E. The climate in the study area is characterized by hot summers and cold winters. The mean daily maximum temperature ranges from 35°C in summer to approximately 17°C in winter and mean daily minimum temperature ranges from 5°C in summer to about -24.5°C in winter. The mean annual evaporation rate is 3265 mm. In this study, image processing techniquess including band combinations, Principal Component Analysis (PC1, PC2 and PC3), and classification were applied to a TM image to map different soil properties. In order to prepare the satellite image, geometric correction was performed. A 1:25,000 map (UTM 39) was used as a base to georegister the Landsat image. 40 Ground Control Points (GCPs) were selected throughout the map and image. Road intersections or other man-made features were appropriate