Innovative Intelligent Methodology for the Classification of Soil Salinization Degree Using a Fractional-Order Master-Slave Chaotic System

Soil salinization has become a highly significant eco-system issue that is encountered all over the world. Serious soil salinization leads to soil deterioration and has a negative impact on sustainable development of the eco-system and agriculture. However, the spectral reflectance of soils with high overlap and indecipherability makes it difficult to classify the soil salinization degree quickly and accurately. In this paper, an innovative, intelligent methodology using a fractional-order chaotic system to classify the soil salinization degree is proposed. To select a suitable order for the fractional-order chaotic system, the integer-order and noninteger order master-slave Lorenz chaotic systems were used to observe variations in the phase plane distributions. Movement traces of the chaotic system show that severely saline soil will exhibit more active changes, and its distribution status of the Lorenz chaotic system will be more scattered. After analyzing the characteristics of phase plane distribution...