Abstract
The role of remote sensing and human–environment interactions (HEI) research in social and environmental decision-making has steadily increased along with numerous technological and methodological advances in the global environmental change field. Given the growing inter- and trans-disciplinary nature of studies focused on understanding the human dimensions of global change (HDGC), the need for a synchronization of agendas is evident. We conduct a bibliometric assessment and review of the last two decades of peer-reviewed literature to ascertain what the trends and current directions of integrating remote sensing into HEI research have been and discuss emerging themes, challenges, and opportunities. Despite advances in applying remote sensing to understanding ever more complex HEI fields such as land use/land cover change and landscape degradation, agricultural dynamics, urban geography and ecology, natural hazards, water resources, epidemiology, or paleo HEIs, challenges remain in acquiring and leveraging accurately georeferenced social data and establishing transferable protocols for data integration. However, recent advances in micro-satellite, unmanned aerial systems (UASs), and sensor technology are opening new avenues of integration of remotely sensed data into HEI research at scales relevant for decision-making purposes that simultaneously catalyze developments in HDGC research. Emerging or underutilized methodologies and technologies such as thermal sensing, digital soil mapping, citizen science, UASs, cloud computing, mobile mapping, or the use of “humans as sensors” will continue to enhance the relevance of HEI research in achieving sustainable development goals and driving the science of HDGC further.
Highlights
Combined, the 1999 National Research Council (NRC) publication “Global Environmental Change: Understanding the Human Dimensions” [1] that followed closely on the heels of the 1998 NRC “People and Pixels: Linking Remote Sensing and Social Science” [2] publication, effectively launched a golden era in the integration of remote sensing technologies into the study of human–environment interactions under the broader umbrella of human dimensions of global change (HDGC) research
With the heightened understanding of the coupled nature of human and natural systems and of the significant contributions humans have made to changes in the hydrologic, ecologic, geomorphologic, biologic, biogeochemical, and climatic cycles [3], increased effort has subsequently been given to integrating human–environment interactions (HEI) studies and rapidly evolving remote sensing technologies predicated on this critical link between humans and the Earth systems they depend on for their livelihoods and well-bring
Along with an increased focus on citizen and participatory science and leveraging the incessant stream of georeferenced voluntary geographic information (VGI) produced from mobile and social media sources, analysis-ready remote sensing datasets can virtually revolutionize the field of human–environment interactions research at unprecedented rates over the ensuing decade
Summary
The 1999 National Research Council (NRC) publication “Global Environmental Change: Understanding the Human Dimensions” [1] that followed closely on the heels of the 1998 NRC “People and Pixels: Linking Remote Sensing and Social Science” [2] publication, effectively launched a golden era in the integration of remote sensing technologies into the study of human–environment interactions under the broader umbrella of human dimensions of global change (HDGC) research. A study undertaken by social scientists may use a LUCC remote sensing analysis to validate an in-depth analysis of in-situ land use data and local perceptions of environmental change obtained from community interviews [13,18,19,20] Integrated models, such as agent-based models (ABM), more accurately represents complex socio-environmental systems because they begin with the smallest component of the system (i.e., humans) and allow agents to make autonomous decisions and interact with each other within a set of simple rules informed by observed social data (such as surveys or focus groups). We assess the degree to which human systems and social data have been integrated into these studies and identify opportunities for further, much needed integration
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