Agricultural land displacement and undernourishment

Marselis, S.; Feng, Kuishuang; Liu, Yu; Teodoro, Jose Daniel; Hubacek, Klaus

doi:10.1016/j.jclepro.2017.05.125

Cited by 37 publications

(15 citation statements)

References 30 publications

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“…However, it has been widely appreciated that rapid urbanization has already induced various problems, such as air and water pollution Carrascal Incera et al, 2017;Sun et al, 2018), traffic congestion (Wang et al, 2017), depletion of cultivated land (Marselis et al, 2017), habitat destruction (Malico et al, 2016), the inadequate provision of urban shelter, the irrational rise of housing price (Ge, 2017), and various types of urban crimes (Alves et al, 2018). These problems present huge challenges to sustainable urban development.…”

Section: Introductionmentioning

confidence: 99%

A lessons mining system for searching references to support decision making towards sustainable urbanization

Wang

Shen

Ren

et al. 2019

Journal of Cleaner Production

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The recurrence of similar problems caused by human errors in urbanization process is common throughout the world. However, the knowledge learnt from these problems should become lessons as references for decision-making to avoid the recurrence of these problems, thus the results of urbanization are sustainable. It is considered of imperative importance to incorporate the lessons experienced into the decisionmaking process in a way that can help foresee the potential problems and take proper measures for addressing the problems. There is little existing study on how previous lessons are mined and incorporated in foreseeing the potential problems in future. The lack of this mining mechanism presents a significant barrier for decision makers to learn from the existing lessons thus to have references of how to make better decisions for future urbanization practices. This paper presents a Lessons Mining System (LMS) to assist in mining lessons experienced from previous practices. The system includes five components, namely, Lessonscase Representation , Lessons-case Store, Lessons-case Retrieval, Lessons-case Application, and Lessons-case Update. LMS can facilitate decision makers to understand what potential problems might occur from their current actions by referring to the lessons experienced previously in similar circumstances. This understanding can help decision makers take preventive measures to mitigate the potential problems. In other words, the use of LMS can send alarming messages to decision makers about what possible problematic consequence may occur thus they can modify their actions before too late. The establishment of LMS is based on Casebased Reasoning (CBR) theory and the similarity matching principles. A demonstration of Yangwu Town is presented to show the application of the system, and the result shows that the lessons mined can provide valuable references for the government of Yangwu Town to improve their decisionmaking quality.

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Section: Introductionmentioning

confidence: 99%

A lessons mining system for searching references to support decision making towards sustainable urbanization

Wang

Shen

Ren

et al. 2019

Journal of Cleaner Production

View full text Add to dashboard Cite

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“…While China, as of this writing, is experiencing the greatest negative effects, other nations and regions play similar roles. Bangladesh, Cambodia, and India are leading producers of textiles, and Laos, Myanmar, and several nations in Africa have many sites of "land grabs," the buying or leasing of land for export production on terms unfavorable to local people, with consequences for the environment and climate change, including deforestation (Marselis, Feng, Liu, Teodoro, & Hubacek, 2017).…”

Section: Power Social Stratification and Inequalitymentioning

confidence: 99%

Social science perspectives on drivers of and responses to global climate change

Jorgenson

Fiske

Hubacek

et al. 2018

WIREs Climate Change

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119

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This article provides a review of recent anthropological, archeological, geographical, and sociological research on anthropogenic drivers of climate change, with a particular focus on drivers of carbon emissions, mitigation and adaptation. The four disciplines emphasize cultural, economic, geographic, historical, political, and social‐structural factors to be important drivers of and responses to climate change. Each of these disciplines has unique perspectives and makes noteworthy contributions to our shared understanding of anthropogenic drivers, but they also complement one another and contribute to integrated, multidisciplinary frameworks. The article begins with discussions of research on temporal dimensions of human drivers of carbon emissions, highlighting interactions between long‐term and near‐term drivers. Next, descriptions of the disciplines' contributions to the understanding of mitigation and adaptation are provided. It concludes with a summary of key lessons offered by the four disciplines as well as suggestions for future research.This article is categorized under: Climate Economics > Economics and Climate Change

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Section: Power Social Stratification and Inequalitymentioning

confidence: 99%

Social Science Perspectives on Drivers of and Responses to Global Climate Change

Jorgenson¹,

Fiske²,

Hubacek³

et al. 2018

Preprint

Self Cite

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This article provides a review of recent anthropological, archaeological, geographical, and sociological research on anthropogenic drivers of climate change, with a particular focus on drivers of carbon emissions, mitigation and adaptation. The four disciplines emphasize cultural, economic, geographic, historical, political, and social-structural factors to be important drivers of and responses to climate change. Each of these disciplines has unique perspectives and makes noteworthy contributions to our shared understanding of anthropogenic drivers, but they also complement one another and contribute to integrated, multidisciplinary frameworks. The article begins with discussions of research on temporal dimensions of human drivers of carbon emissions, highlighting interactions between long-term and near-term drivers. Next, descriptions of the disciplines' contributions to the understanding of mitigation and adaptation are provided. It concludes with a summary of key lessons offered by the four disciplines as well as suggestions for future research.

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Agricultural land displacement and undernourishment

Cited by 37 publications

References 30 publications

A lessons mining system for searching references to support decision making towards sustainable urbanization

A lessons mining system for searching references to support decision making towards sustainable urbanization

Social science perspectives on drivers of and responses to global climate change

Social Science Perspectives on Drivers of and Responses to Global Climate Change

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