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   Integrated Application of Remote Sensing and Spatial Statistical Models To the Identification of Soil Salinity: A Case Study From Garmsar Plain, Iran  
   
نویسنده Noroozi Ali Akbar ,Homaaee Mehdi ,Farshad Abbas
منبع علوم محيطي - 1390 - دوره : 9 - شماره : 1 - صفحه:59 -74
چکیده    Soil salinity expansion is an environmental challenge particularly in arid and semi arid regions. in order to evaluate the progressing extent of soil salinity in relation with natural and human-induced conditions, a study was conducted using the laiidsat tm imagery. the present study was conducted in the garmsar area to the east of tehran. a total of 288 soil samples were analyzed to determine the relationship between the spectral refleetance and eleetrical conductivity (ec), as salinity indicator. multiple regression analysis and ordiuary least square regression (ols) were used to examine the relationships between ec and derived speetral to generate several models. in the case of derived spectral, mid-infrared band (tm band-7), visible band (band-1), tasseled cap3 (wetness index) and pca2 (principal component analysis) were found to be most coitelated with the observed ec values of the surface layer of the soil, at 99% coufidenee level. the aecuracy of the predietion model was tested using a validation set of 52 soil samples in eyvanekey plain, close to stndy area where the environmental eircumstanee consist of similar properties. rmse and mae were used to evaluate the performance of the map prediction quality. results showed that the appropriate model could predict the soil salinity with precision of 4.1 and 0.49 ds m1, respectively. the predicted salinity ranged from ods/in to 11 ods/in. therefore, the ec estimations were suitable to generate soil salinity map. sensitivity analysis was tested on applied parameters that showed band-1 and band-7 were 3 and 2 times more than sensitive rather than other parameters respectively. the results are promising and certainly useful for soil salinity prediction.
کلیدواژه Electrical Conductivity (Ec) ,Tm ,Ordinary Least Square Regression ,Garmsar (Iran) ,Soil Salinity
آدرس Tarbiat Modares University, Faculty Of Agriculture, Department Of Soil Science, ایران, Tarbiat Modares University, Faculty Of Agriculture, Department Of Soil Science, ایران, Twente University Netherlands, Faculty Of Etc, Depcn'Tment Of Earth Science, Netherlands
پست الکترونیکی mhomaee@modares.ac.ir
 
     
   
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