To explore the evolution process of soil salinization in Shouguang, the current study applied the Pan and Multi-spectra Sensor (PMS), Operational Land Imager (OLI) and Thematic Mapper (TM) data to establish a remote sensing monitoring model of soil salinization. Based on the vegetation and salinity indexes, we extracted the information of soil salinization in the flourishing period of plant growth in Shouguang in 2017. At the same time, we monitored the spatial and temporal patterns of soil salinization in Shouguang from 1998 to 2017. We compared the range of soil salinization reflected by remote sensing data and the regional groundwater level and revealed the formation and evolution mechanism of soil salinization in Shouguang. The results reflected that the distribution of soil salinization in Shouguang demonstrated obvious banding characteristics in distribution, and soil salinization gradually increased from the south to the north. Based on the imagery interpretation of Landsat images of three periods from 1998 to 2017, we found that the area of saline land in Shouguang severely decreased as a whole, but the coastal salinization intensified. Moreover, the inversion of surface soil salinity using the GF-1 satellite PMS image has a high precision, and the goodness of fit (R 2 ) is up to 0.871. Compared with the GF-1 image, the Landsat image is more suitable for grading and monitoring soil salinization in a wide range. We also confirmed that the change in ground water level is the main reason for the evolution of salinization. Excessive exploitation of groundwater by vegetable production caused the intensification of seawater intrusion and secondary salinization in coastal areas, while the water level dropped in areas far from the coastline. To prevent the deterioration from soil salinization in Shouguang, it is necessary for us to extract the local groundwater resources reasonably and optimally.
CITATION STYLE
Dong, F., Tang, Y., Xing, X., Liu, Z., & Xing, L. (2019). Formation and evolution of soil salinization in Shouguang city based on PMS and OLI/TM sensors. Water (Switzerland), 11(2). https://doi.org/10.3390/w11020345
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