Abstract
In order to get RS method to extract soil salinity of the Yellow River Delta, we set Kenli County as typical Yellow River Delta to be research area and get data of soil salinity through field investigation. By using RS image of Landsat-8 of March 14, 2014 and analyzing information features of each band and surface spectral features of research areas, we select out sensitive bands and build Soil Salinity Information Extraction (SSIE) model and vegetation index NDVI model for comparison. And then, we accordingly classify grades of soil salinity and get soil salinity information by decision tree approach based on expert knowledge. The results show that overall accuracy of SSIE model is 93.04% and coefficient of Kappa is 0.7869, while overall accuracy of NDVI model is 83.67% and coefficient of Kappa is 0.7017 respectively. By comparing with measured proportions of each class, we see that results from SSIE model is more accurate, which indicates significant advantage for soil salinity information extraction. This research provides scientific basis to get and monitoring soil salinity of the Yellow River Delta region quickly and accurately.
Highlights
Soil salinization and alkalization is a globally ecological and environmental issue [1]-[4]
It is seen that the overall accuracy and coefficient of Kappa of soil salinity information extraction (SSIE) model built in this essay are obviously higher than those of vegetation index model
Considering the relations of each band of Landsat-8, in order to decrease the redundancy between bands, we chose sensitive bands of OLI 5 and OLI 6, which provides an effective method for sensitive band choosing and soil salinity information extraction
Summary
Soil salinization and alkalization is a globally ecological and environmental issue [1]-[4]. RS technology, which has features of macrography, comprehensiveness, dynamic and speediness, can get information on same area repeatedly and extensively. It has become a new detection means for earth resources survey and environmental monitoring and has been widely applied for research of soil degradation, especially for monitoring and mapping of saline soil [9]-[11]
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