By 2030, around 194,000 new dwellings will be built in Berlin, including almost 52,000 in 16 new urban districts. These and other interventions will impact the city’s nature and landscape. An important means of compensating for these losses is a land-use planning eco-account adapted to Berlin’s needs.

Landslides are one of the most significant natural hazards worldwide. They can have far-reaching negative impacts on societies in different socio-economic sectors as well as on the landscape. Among the different types and processes that can also affect infrastructure and land use planning, slow-moving landslides are often underestimated.

North Korea experienced a catastrophic famine in the mid-1990s that resulted in millions of deaths. This study aims to build an agent-based model to understand the risk of land degradation and famine in North Korea and explore potential solutions to mitigate this risk.

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.

Despite the significant and explicit focus on the United Nations Sustainable Development Goals (SDGs), much of the world’s land rights remain unrecorded and outside formal government systems. Blame is often placed on land administration processes that are considered slow, expensive, and expertise-dependent.

Land is the key asset in the agricultural sector and hence land policy is one of the key elements that determine whether SDGs are achieved in developing counties or not. In developing countries, land titling programs have been seen as a strategy for addressing SDGs.

With over 14 million hectares allocated, Vietnam’s forest and forestland allocation has been one of the largest natural resource decentralization programs in the developing world over the last three decades. Given this remarkable achievement, critics are concerned about the low rates of household tree planting investment and question the roles and effects of land institutions on investment.

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.

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.

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.

Carbon emissions increase the risk of climate change. As one of the primary sources of carbon emissions, road traffic faces a significant challenge in terms of reducing carbon emissions. Many studies have been conducted to examine the impacts of cities on carbon emissions from the perspectives of urbanization, population size, and economics.