No abstract

Soil salinization is a critical and global environmental problem. Effectively mapping and monitoring the spatial distribution of soil salinity is essential. The main aim of this work was to map soil salinity in Shandong Province located on the Yellow River Delta of China using Sentinel-1/2 remote sensing data and digital elevation model (DEM) data, coupled with soil sampling data, and combined with four regression models: support vector regression (SVR), stepwise multi-regression (SMR), partial least squares regression (PLSR) and random forest regression (RFR). For these purposes, 60 soil samples were collected during the field survey conducted from 9 to 14 October 2019, corresponding to the Sentinel-1/2 and DEM data. Then we established a soil salinity and feature dataset based on the sampled data and the features extracted from Sentinel-1/2 and DEM data. This study adopted the feature importance of the RF model to screen all features. The results showed that the CRSI index made the greatest contribution in retrieving soil salinity in this region. In this paper, 18 sampling points were used to validate and compare the performance of the four models. The results reveal that, compared with the other regression models, the PLSR model has the best performance (R2 = 0.66, and RMSE = 1.30). Finally, the PLSR method was used to predict the spatial distribution of soil salinity in the Yellow River Delta. We concluded that the model can be used effectively for the quantitative estimation of soil salinity and provides a useful tool for ecological construction.

As a vital part of sustainable development, food security is challenged by prolonged and concurrent pressures. Efforts have long been devoted to balance grain production across China as a whole, and thereby the uncertainties and underlying crisis in the regional grain-producing systems are hidden. In this study, we characterize the dynamic evolution of 357 cities and explore the dominant supply and demand effects to signal early warnings of grain insecurity. Our results show that 220 cities are in unsustainable grain supply–demand conditions in comparison with 10 years ago. Additionally, the south and southwest of China have experienced enlarged disparities and more severe grain insecurity. The dual effects from both increased population and decreased grain output are substantially responsible for the unsustainable grain-producing system on the city scale. Moreover, cities identified as having grain insecurity occupy high-quality cultivated land, including 55.4% of top-grade land, 49.8% of high-grade land, and only 28.9% of low-grade land. We consequently inform the incongruity between grain productivity and regional grain conditions. It is suggested that current intensive management of cultivation and the strategy of differentiated responsibilities in grain production should be based on environmental sustainability and a degree of self-sufficiency across the region.

No abstract

No abstract