Soil hydrological processes (SHP) support ecosystems, modulate the impact of climate
change on terrestrial systems and control feedback mechanisms between water, energy and …

Digitalization has impacted agricultural and food production systems, and makes application
of technologies and advanced data processing techniques in agricultural field possible …

Highlights•We present a framework to clarify learning processes in transdisciplinary
research.•We propose three distinctive conceptions of transdisciplinary learning.•We include …

Digitalisation has enjoyed rapid acceleration during the COVID-19 pandemic on top of the
already fast-paced expansion impacting almost every aspect of daily life. Digital twin …

There is growing global interest in the potential for soil reflectance spectroscopy to fill an
urgent need for more data on soil properties for improved decision-making on soil security at …

Abstract Machine learning approaches have been widely used for crop yield modelling and
yield forecasting but there has been limited application to understanding site-specific yield …

In this concluding paper, we summarize the main advances coming forward from the joint
conference of the International Union of Soil Sciences (IUSS) Working Groups (WG)“Digital …

Land use evaluation and capacity assessment for sustainable urban development in Ahvaz
city has become crucial due to rapid urban expansion negatively impacting current and …

The acquisition of soil information using infrared spectroscopy is now widely practised in soil
sciences. In conjunction with machine learning models, spectral data are used to predict soil …

Synthesizing bare soil pictures in regions with complex vegetation is challenging, which
hinders the accuracy of predicting soil organic carbon (SOC) in specific areas. An SOC …