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MDPI AG, a publisher of open-access scientific journals, was spun off from the Molecular Diversity Preservation International organization. It was formally registered by Shu-Kun Lin and Dietrich Rordorf in May 2010 in Basel, Switzerland, and maintains editorial offices in China, Spain and Serbia. MDPI relies primarily on article processing charges to cover the costs of editorial quality control and production of articles. Over 280 universities and institutes have joined the MDPI Institutional Open Access Program; authors from these organizations pay reduced article processing charges. MDPI is a member of the Committee on Publication Ethics, the International Association of Scientific, Technical, and Medical Publishers, and the Open Access Scholarly Publishers Association (OASPA).
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Displaying 161 - 165 of 1524Developing an Agent-Based Model to Mitigate Famine Risk in North Korea: Insights from the “Artificial North Korean Collective Farm” Model
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. The model concept reflects the general information of collective farms in North Korea, which was set in 1960, and the abstract of the social–ecological system of North Korean agriculture. The model comprises the agent, environment, and external factors.
Large-Scale Land Acquisition and Household Farm Investment in Northern Ghana
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.
Unveiling the Potential of Machine Learning Applications in Urban Planning Challenges
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. As a fast-growing field of Artificial Intelligence, Machine Artificial Intelligence deals with smart designs, data mining and management for complex problem-solving based on experimental data on urban applications (land use and cover, configurations of the built environment and architectural design, etc.), but with few explorations and relevant studies.
Trade-Offs, Adaptation and Adaptive Governance of Urban Regeneration in Guangzhou, China (2009–2019)
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. As opposed to the “democratic” type of adaptive governance with its bottom-up policy initiations, community autonomy, polycentric power, participation in decision making, and self-organized policy actors, adaptive governance in Guangzhou is based on top-down decision making and implementation of public authorities’ solutions with the high role of political considerations.
Study on the Layout of Ecological Space and the Integrated Management Mechanism of the Yangtze River Delta Urban Agglomeration
The urban agglomeration at the Yangtze River Delta is one of the six most developed and populated urban agglomerations in the world. In recent years, with accelerating urbanization, the land use has changed significantly. Excessive construction aggravates ecological fragility. In this context, this paper first investigates the evolutionary processes and layout of the ecological space in the Yangtze River Delta. The root causes of various problems are then analyzed. Finally, suggestions for further improvement in both detailed tasks and governance aspects are proposed.