Optimal farm size reduces global poverty-induced soil antibiotic exposure risk.

Farming activities contribute to soil antibiotic pollution, posing health risks for rural farm workers, especially on small farms in impoverished regions. The effectiveness of large farms in reducing poverty-induced soil antibiotic exposure risk (SABER) remains uncertain. Here we integrate global datasets on concentration of soil antibiotics, rural farm-worker employments and on-farm working hours to quantify SABER.

Thirty years of 3-D urbanization in the Yangtze River Delta, China.

Accurately capturing the urbanization process is essential for planning sustainable cities and realizing the United Nations Sustainable Development Goal 11. However, until recently, most of the studies on urban expansion in the world have focused on area growth but have little knowledge of height dynamics. This study mapped the spatial distribution of urban built-up areas (UBA) in the Yangtze River Delta (YRD), one of the most urbanized regions in China, to investigate the spatio-temporal evolution in both the horizontal and vertical directions from 1990 to 2020.

[Grain yield estimation of wheat-maize rotation cultivated land based on Sentinel-2 multi-spectral image: A case study in Caoxian County, Shandong, China].

Establishing the remote sensing yield estimation model of wheat-maize rotation cultivated land can timely and accurately estimate the comprehensive grain yield. Taking the winter wheat-summer maize rotation cultivated land in Caoxian County, Shandong Province, as test object, using the Sentinel-2 images from 2018 to 2019, we compared the time-series feature classification based on QGIS platform and support vector machine algorithm to select the best method and extract sowing area of wheat-maize rotation cultivated land. Based on the correlation between wheat and maize vegetation index and the statistical yield, we screened the sensitive vegetation indices and their growth period, and obtained the vegetation index integral value of the sensitive spectral period by using the Newton-trapezoid integration method.

[Remote sensing inversion of cultivated land fertility at county scale based on SWCI-NDVI feature space].

It is objective needs during utilization and management of regional cultivated land resource to use remote sensing to accurately and efficiently retrieve the status of cultivated land fertility at county level and realize the gradation of cultivated land rapidly. In this study, with Dongping County as a case, using Landsat TM satellite imagery and cultivated land fertility evaluation data, the moisture vegetation fertility index (MVFI) was constructed based on surface water capacity index (SWCI) and normalized difference vegetation index (NDVI), and then the optimal inversion model was optimized to obtain the best inversion model, which was further applied and verified at the county scale. The results showed that the correlation coefficient between MVFI and integrated fertility index (IFI) was -0.