چکیده:
Soil salinity phenomena are one of the main problems of arid and semi-arid lands. Saline soils constitute a huge part of Iran, and also threaten its neighboring lands. Therefore, in order to optimum exploitation of such soils, qualitative monitoring is necessary. Recently, remote sensing techniques have been increasingly applied in monitoring soil characteristics. The present study was carried out between 2014 and 2015, with the purpose of using remote sensing for mapping soil salinity in the saline rangelands of Chezan plain (Markazi province). In the first step, 50 soil samples were taken from the topsoil (30 cm depth) and their Electrical Conductivity (EC) was measured by EC- meter. To use the soil salinity map using remote sensing, we first used Indian Remote sensing Satellites (IRS) satellite imagery and the satellite’s LISS sensor (LISS III, 2008). After geometric and radiometric correction, this image was been classified using the Maximum Likelihood method. Then in the next step, Comparison of Spectrum indices were done by extracting maps of soil salinity. For this purpose, Four indices including: Brightness Index (BI), Salinity Index (SI1), SI2, and Normalized Difference Salinity Index (NDSI) were used. Among these indices, SI2 had the most correlation with ground control points (0.63 in 1% level) and is introduced as a more suitable index than others for zoning soil salinity. Regarding to the salinity map, the results showed that a sizeable portion of the study area was classified class 2 with a salinity of between 4-8 dS/m (55% of whole land).
خلاصه ماشینی:
The Jeffries-Matusita distance measures the separability of two classes on a more convenient scale [2-0] in terms of B: J=2(1-e^⁻B) Normality test for spectrum indices Regarding the different ability of each index in presenting a soil salinity map, first, data normality was tested using SPSS.
Cohen's kappa coefficient and total accuracy of the band combination of different bands of LISSIII {مراجعه شود به فایل جدول الحاقی} After assurance of correct classification, each soil salinity class area were calculated with Arc GIS.
, which were extracted from ETM+ (Landsat 7) to map soil salinity, and found, based on accuracy tests on studied indices that SIs had the most correlation with ground control points.
Evaluation of classification results for Chezan plain {مراجعه شود به فایل جدول الحاقی} Having and omitted errors related to the classes of the soil salinity map for the SI2 index were investigated.
Therefore, the present map of this index was used as the soil salinity map using remote sensing for the study area.
Correlation among values of brightness and soil salinity data in different indices {مراجعه شود به فایل جدول الحاقی} ** represents significance at the 0.
Areas of different soil salinity classes based on SI2 index for Chezan plain {مراجعه شود به فایل جدول الحاقی} Several studies have shown that image enhancement techniques consisting of spectral indices (e.
The results of the study revealed that in the mapping of soil salinity, the use of remote sensing techniques are better because of their high accuracy and low cost.