Agent-based models (ABMs) are particularly suited for simulating the behaviour of agricultural agents in response to land use (LU) policy. However, there is no evidence of their widespread use by policymakers. Here, we carry out a review of LU ABMs to understand how farmers’ decision-making has been modelled.

Many studies have investigated the effects of large-scale land acquisition (LSLA) on livelihood, while the effects of LSLA by different actors on investment decisions and levels of investment have largely gone without academic scrutiny. Consequently, information concerning the implications of LSLA by actors on investment is scarce in the literature pertaining to policy.

Spatial planning systems and institutions have a significant role in managing non-agricultural land growth in Europe and the assessment of how their implementation impacts on agricultural land consumption is of great significance for policy and institutional improvement.

As a proxy for human activity, per capita urban land has great significance for urban planning. We still lack a comprehensive understanding of per capita urban land from the perspective of urban–rural gradients.

Green development is necessary for building high-quality modern economic systems. Due to limited land resources, ensuring the ecological benefits will not be damaged while developing the economy is necessary, as is improving urban land green use efficiency (ULGUE). Lanzhou-Xining Urban Agglomeration is a crucial urban agglomeration in the upper reaches of the Yellow River Basin.

Improving urban land use efficiency is a feasible way to realize sustainable development and alleviate urban land pressure on the city.

In a digitalized era and with the rapid growth of computational skills and advancements, artificial intelligence and Machine Learning uses in various applications are gaining a rising interest from scholars and practitioners.

In the context of tax sharing reform and land reform during the 1990s, local governments in China relied heavily on land finance. Local governments have fierce competition in attracting investment, omitting the development of green economy.

With continuous rises in GDP, land cover in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) has undergone a drastic change over the period 1990–2018. In this study, land use in the GBA was divided into six types: farmland, forestland, grassland, wetland, construction land, and unused land.

Baseflow is an essential component of runoff, which is the dominant water resource for the dry season. To better manage water resources, it is vital to investigate the links between the multiple influencing factors and the baseflow for better prediction in light of global changes.

Global environmental changes are multifactorial and affected by multiple forms of land use. For this reason, and also in view of the current world climate scenario, they have become highly relevant and are subject to analysis and discussions on the best uses of land.

This paper explores the specific “authoritarian” type of adaptive governance of urban regeneration using the example of Guangzhou city as the frontier of China’s reforms.