Understanding the interactions between global climate change and human activity at the neighborhood level is crucial to the development of next-generation earth system models that can produce actionable results with minimum uncertainties. Changing human activity within urban, suburban, and exurban areas can have specific and significant influence on the global climate. However, current global climate models do not include humans as actors within the modeling framework, so such high-resolution influences have not yet been conclusively determined. Demonstrating that highly resolved temporal and spatial decisions by humans within the earth-system modeling framework influences the global climate could inform local and regional policies regarding mitigation of and adaptation to climate change. We address this need by proposing an integrated methodology using data analytics, agent-based modeling and earth system modeling.