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Desert
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Rahmati, M., Hamzehpour, N. (2018). Effectiveness of spectral data reduction in detection of salt-affected soils in a small study area. Desert, 23(1), 97-106. doi: 10.22059/jdesert.2018.66357
M. Rahmati; N. Hamzehpour. "Effectiveness of spectral data reduction in detection of salt-affected soils in a small study area". Desert, 23, 1, 2018, 97-106. doi: 10.22059/jdesert.2018.66357
Rahmati, M., Hamzehpour, N. (2018). 'Effectiveness of spectral data reduction in detection of salt-affected soils in a small study area', Desert, 23(1), pp. 97-106. doi: 10.22059/jdesert.2018.66357
Rahmati, M., Hamzehpour, N. Effectiveness of spectral data reduction in detection of salt-affected soils in a small study area. Desert, 2018; 23(1): 97-106. doi: 10.22059/jdesert.2018.66357

Effectiveness of spectral data reduction in detection of salt-affected soils in a small study area

Article 10, Volume 23, Issue 1, Winter and Spring 2018, Page 97-106  XML PDF (1.33 MB)
DOI: 10.22059/jdesert.2018.66357
Authors
M. Rahmati; N. Hamzehpour
Department of Soil Science, Faculty of Agriculture, University of Maragheh, Maragheh, East Azarbayjan, Iran
Abstract
     Data reduction is used to aggregate or amalgamate the large data sets into smaller and manageable information pieces in order to fast and accurate classification of different attributes. However, excessive spatial or spectral data reduction may result in losing or masking important radiometric information. Therefore, we conducted this research to evaluate the effectiveness of the different spectral data reduction algorithms including Principle Component Analysis (PCA) and Minimum Noise Fraction (MNF) transformation, Pixel Purity Index (PPI), and n Dimensional Visualizer (n-DV) algorithms on accuracy of the supervised classification of the salt-affected soils applying ETM+ data beside 188 ground control points. Results revealed that data reduction caused around 20 to 30 % decreases in classification results compared to none reduced data. It seems that applying spectral data reduction algorithm in small study areas is not only supportive, but also has negative effects on classification results. Therefore, it may better to not to use the algorithms in small areas.   
Keywords
modeling; Regression modeling; Salt-affected soils; salinity; Satellite images
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