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Paper Information

Journal:   IRANIAN JOURNAL OF SOIL AND WATER RESEARCH   2010 , Volume 41 , Number 1; Page(s) 27 To 37.
 
Paper: 

AN EVALUATION LISS_III DATA CAPABILITY FOR SALINE AND SODIC SOIL MAPPING

 
 
Author(s):  KHODADADI M.*, SARMADIAN F., ASKARI M.S., REFAHI H., NOROOZI A.A., HEYDARI A.
 
* FACULTY OF AGRICULTURE, UNIVERSITY OF TEHRAN
 
Abstract: 

Salinity and sodicity are the major factors of soil degradation in arid and semiarid areas. The main aim of this study was to evaluate the capability of LISS_III data for soil salinity and sodicity mapping in a selected part of the Qazvin plain, an area of arid environment. During the study, spectral classes were carried out of the remotely sensed data and then with the help of field observations and soil analysis regrouped to soil salinity and sodicity classes. Finally soil salinity and sodicity maps were prepared. Soil sampling was implemented using stratified random sampling method, depending on landscape complexity and homogeneity as well as on the representativity to LISS_III data. Also, in each soil map unit, at least one profile was studied for subsoil salinity variations. Field samples from augur and profiles were analyzed in laboratory for Na+, Ca2+, Mg2+ cations, as well as for soil texture, ECe and pH. The effectiveness of such additional data as digital elevation model and slope which may improve the accuracy of classification was analyzed. Also NDVI, SRVI, PVI, SAVI, SI, BI and NDSI indices as well as, PCA were taken into account in the analysis. Optimum index factor (OIF) was used for a detection of best band combination. Soil salinity map of each selected bands was produced and crossed with the ground truth map. The results indicated that maximum likelihood algorithm is of a higher accuracy than either Box Classifier or minimum distance algorithm. A combination of DEM with LISS_III bands benefits from a highest accuracy. The indices benefitted from an almost high degree of accuracy among the studied processing techniques. The SI and BI indices were in the most correlation with EC and could well distinguish the saline and no saline soils. PCA had a low accuracy in differentiating the saline soils. The optimum index factor had a low overall accuracy. Also results indicated that smooth crusts with no cracks caused increases in the reflections. The accuracy of sodicity map was less than that of the salinity map. The accuracy in moderate sodicity levels was less than in cases with either low or high sodicity levels.

 
Keyword(s): SALINE AND SODIC SOILS, LISS_III, INDICES, DEM, REMOTE SENSING, GIS
 
References: 
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