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.

The heavy metal cadmium (Cd) is a major threat to food safety and human health. Phytoremediation is the most widely used remediation technology, and how to improve the remediation efficiency of phytoremediation has become a key issue. In this study, we constructed an intensive phytoremediation technology for remediation of Cd-contaminated soil with biodegradable chelating agent and plant growth regulator combined with maize and investigated the mechanism of this technology. The results showed that the best remediation effect was achieved in the treatment with 10 ⁻⁶ mol l ⁻¹ gibberellic acid (GA ₃ ) and 6 mmol kg ⁻¹ aspartate diethoxysuccinic acid (AES) combined with maize. In this treatment, the total biomass and extraction efficiency of maize were 3.6 and 8.67 times higher than those of the control, respectively, and the antioxidant enzyme activities of maize were also increased. The soil was enriched with dominant bacterial genera that promote plant growth and metabolism and tolerance to heavy metal stress, which in turn promoted maize growth and Cd accumulation. Structural equation modelling results indicated a large effect of plant Cd concentration and plant antioxidant enzyme activity on plant Cd extraction. The enhanced phytoremediation technology showed good potential for safe use of Cd-contaminated soil.

Timely cropland information is crucial for ensuring food security and promoting sustainable development. Traditional field survey methods are time-consuming and costly, making it difficult to support rapid monitoring of large-scale cropland changes. Furthermore, most existing studies focus on cropland evaluation from a single aspect such as quantity or quality, and thus cannot comprehensively reveal spatiotemporal characteristics of cropland. In this study, a method for evaluating the quantity and quality of cropland using multi-source remote sensing-derived data was proposed and effectively applied in the black soil region in Northeast China. Evaluation results showed that the area of cropland increased significantly in the study area between 2010 and 2018, and the proportion of cropland increased by 1.17%. Simultaneously, cropland patches became larger and landscape connectivity improved. Most of the gained cropland was concentrated in the northeast and west, resulting in a shift in the gravity center of cropland to the northeast direction. Among land converted into cropland, unused land, grassland, and forest were the main sources, accounting for 36.38%, 31.47%, and 16.94% respectively. The quality of cropland in the study area generally improved. The proportion of low-quality cropland decreased by 7.17%, while the proportions of high-quality and medium-quality cropland increased by 5.65% and 5.17%, respectively. Specifically, the quality of cropland improved strongly in the east, improved slightly in the southwest, and declined in the north. Production capacity and soil fertility were key factors impacting cropland quality with obstacle degrees of 36.22% and 15.64%, respectively. Overall, the obtained results were helpful for a comprehensive understanding of spatiotemporal changes in cropland and driving factors and can provide guidance for cropland protection and management. The proposed method demonstrated promising reliability and application potential, which can provide a reference for other cropland evaluation studies.

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.

In response to the current serious problem of soil cadmium (Cd) contamination in agricultural land, phytoremediation technology is a green and environmentally friendly application prospect; however, its remediation efficiency is currently limited. An enhanced phytoremediation technique was constructed using the biodegradable chelator aspartate diethoxysuccinic acid (AES) combined with the plant growth regulator gibberellic acid (GA₃) to enhance the formation of maize. This technique has been proven to have a superior remediation effect. However, the safety of the restoration technique is of particular importance. The remediation process not only removes the contaminants, but also ensures that the original structure and stability of the soil is not damaged. In this regard, the constructed enhanced phytoremediation technique was further investigated in this study using soil columns. In combination with microscopic tests, such as X-ray diffraction and scanning electron microscopy, this study investigated the effects of the remediation process on the distribution characteristics of Cd in soil aggregates, and the structure and stability of soil aggregates. This was conducted by analyzing, as follows: plant growth conditions; the morphology, structure and mineral composition of soil aggregates in different soil layers; and the changes in these characteristics. The results demonstrated that the enhanced phytoremediation technique constructed in this study has a negligible impact on the morphology and mineral composition of soil aggregates, while exerting a limited influence on soil structure stability. This indicates that the technique can facilitate the safe utilization of remediated contaminated soil.