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Displaying 41 - 45 of 2258Collaborative Optimal Allocation of Urban Land Guide by Land Ecological Suitability: A Case Study of Guangdong–Hong Kong–Macao Greater Bay Area
Urban land optimization in urban agglomerations plays an important role in promoting territorial spatial planning to achieve high-quality development, land ecological suitability (LES) is one of the important variables influencing its urbanization and needs to be considered in urban growth simulation and modeling. This research proposed a multi-objective urban land optimization (MULO) model based on the non-dominated sorting genetic algorithm II (NSGA-II) which integrates the LES assessment.
Developing 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.
The Contribution of Land Registration and Certification Program to Implement SDGs: The Case of the Amhara Region, Ethiopia
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. Even though the government of Ethiopia launched the rural land registration and certification program (LRCP) to secure the land rights of rural households in 1998, currently, there are limited empirical studies to examine the contribution of LRCP in addressing sustainable development goals (SDGs).