The Change Pattern and Its Dominant Driving Factors of Wetlands in the Yellow River Delta Based on Sentinel-2 Images

Abstract

There were significant differences in the dominant driving factors of the change process of different types of wetlands in the Yellow River delta. In addition, to our knowledge, the optimal classification feature sets with the Random Forest algorithm for wetlands in the Yellow River delta were least explored. In this paper, the wetland information in the study area was extracted based on a Random Forest algorithm with de-feature variable redundancy, and then the change process of wetland and its dominant factors from 2015 to 2021 was monitored and analyzed using the Geodetector and gravity center model. The results showed that (1) the optimal variable sets composed of red edge indexes based on the Random Forest algorithm had the highest classification accuracy, with the overall accuracy and Kappa coefficient of 95.75% and 0.93. (2) During 2015–2021, a large area of natural wetland in the Yellow River delta was transformed into an artificial wetland. The wetlands showed an overall development direction of “northwest–southeast” along the Yellow River. (3) The interaction between vegetation coverage and accumulated temperature had the largest explanatory power of the change in the natural wetland area. The interaction between solar radiation and DEM had the largest explanatory power for the change in the artificial wetland area. The research results could better provide decisions for wetland protection and restoration in the Yellow River delta.

Keywords

• wetlands
• change pattern
• Random Forest algorithm
• feature selection
• Geodetector