Topics for these sessions include, but are not limited to, the following:
• State-of-the-art technologies and applications in human-environmental interactions.
• Interaction effects of socio-environmental dynamics on food, water, energy securities, disease spread, and public health.
• Impacts of human activities on environmental changes, such as coastal land loss, flooding, deforestation, wildfires, and decreasing biodiversity and natural resources.
• Short-term and long-term community resilience assessment and modeling.
• Scale effects on coupled natural-human system modeling.
• Applications of geospatial big data (e.g., social media, volunteered geographic information, remote sensing, distributed sensors, portable sensing, sensor networks, etc.) on human dynamics modeling.
• Applications of Artificial Intelligence algorithms on socio-environmental dynamics modeling and simulation.
• Geospatial data fusion challenges and considerations in human and natural interactions research.
Human communities are vulnerable to threats from global environmental changes, including global warming, sea-level rise, and increasingly frequent natural hazards. Meanwhile, human development, such as urbanization and exploration, changes the landscape and biodiversity of the natural environment. The rapidly growing body of geospatial data sets and technologies leads to new opportunities and challenges in modeling the complex human-environment interactions and developing sustainable communities.
This virtual session aims to promote a discussion on modeling human dynamics in integrated social-environmental systems. This session welcomes presentations using remote sensing, social surveys, social media, crowdsourcing, spatial modeling, geostatistics, and machine learning to answer how human systems respond to a dynamic environment through mitigation and planning.
Topics for these sessions include, but are not limited to, the following:
• State-of-the-art technologies and applications in human-environmental interactions.
• Interaction effects of socio-environmental dynamics on food, water, energy securities, disease spread, and public health.
• Impacts of human activities on environmental changes, such as coastal land loss, flooding, deforestation, wildfires, and decreasing biodiversity and natural resources.
• Short-term and long-term community resilience assessment and modeling.
• Scale effects on coupled natural-human system modeling.
• Applications of geospatial big data (e.g., social media, volunteered geographic information, remote sensing, distributed sensors, portable sensing, sensor networks, etc.) on human dynamics modeling.
• Applications of Artificial Intelligence algorithms on socio-environmental dynamics modeling and simulation.
• Geospatial data fusion challenges and considerations in human and natural interactions research.
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