بررسي قابليت داده هاي سنجش از دور در تهيه نقشه شوري و قليائيت خاك در جنوب شرق اصفهان

چكيده انگليسي :

Investigating the Potential of Remote Sensing Data in Producing Soil Salinity and Alkalinity Map in Southeastern Isfahan Farid Mahmoodi farid shabgir@gmail com Marth 14 2011 Department of Natural Resources Isfahan University of Technology Isfahan 84156 83111 IranDegree M Sc Language FarsiHamidreza Karimzadeh hr karimzadeh@yahoo comReza Jafari reza jafari@cc iut ac irAbstractSoil salinity is one of the major environmental problems that lead to crop yields failure and exacerbation ofdesertification in natural resources area More than 15 percent in Iran area are affected by salinity and evidences based on objective observations show these areas are developing every year Other limitations ofthe soils in arid and desert regions are calcite gypsum and alkalinity that considering the percentage ofminerals in the soils and natural ecosystems human interference cause to increasing of desert areas Forprincipled decision making on agricultural product management combating desertification and itsconsequences problems and use of production resources to achieve sustainable development understandingand knowledge of the origin amount and area of salinity the percentage of calcite gypsum and othermineral of soil in each region is essential One of the effective tools for investigating of surface soil salinityis remote sensing technology This study aimed to evaluate the ability of Landsat TM satellite data duringShahrivar 1388 over Varzaneh and Hasan abad regions located on southeastern of Isfahan province foridentification and separation of saline calcite and gypsum land by field studies and soil laboratory results In order to prepare satellite image geometric correction was performed this was done by image to imagemethod ground checkpoints and 1 25000 scale topographic map with UTM coordinates and accuracy ofabout 0 3 pixel Stratified random sampling techniques were used for field sampling Before sampling unsupervised classification was done on image for determine the individual groups and finally 53 soilsurface samples at 0 10 cm depth were taken from all identified groups of study area using GPS Differentmethods of image processing such as selecting the best band combination Principal Component Analysis PC1 PC2 and PC3 salinity indices modelling and classification was performed on the image To preparethe soil surface characteristics map multiple linear regression models with averaging of 9 pixels for eachsampling points in all bands and indices were calculated According to laboratory results the model run foreach soil surface characteristics such as Electrical Conductivity EC percent of gypsum sulfates ion etc and continuous map for each of these parameters were determined Also the supervised classificationmethod with maximum likelihood algorithm was carried out for prepare the soil surface characteristics map For both methods modeling and classification error matrix of maps were calculated and by comparing oferror matrix result and classification accuracy of different classes best method for prepare the soil surfacecharacteristics map was reported Suitable method for mapping the EC calcite and gypsum parameters wassupervised classification modelling and multiple linear regression respectivly Overall accuracy of EC calcite and gypsum maps are 89 90 and 88 percent respectively The results indicate high levels ofminerals in the soil surface of study area that is due to the natural ecosystem conditions inappropriate landuse and incorrect agricultural irrigation methods In conclusion final soil surface characteristics maps areimportant for field operations cambating desertification rehabilitation and estimation of wind erosion and compared to maps that are created by traditional methods our final maps have more economically and timesaving advantages Keyword Salinity Desertification Remote sensing Salinity index Multiple linear regression Supervised classification

محمودي، فريد

بررسي قابليت داده هاي سنجش از دور در تهيه نقشه شوري و قليائيت خاك در جنوب شرق اصفهان

بيابان زدايي , شاخص شوري , رگرسيون خطي چند متغيره , طبقه بندي نظارت شده