The goal of my research program is to improve our understanding about highly integrated natural and human processes. Within the context of Land-System Science, I seek to understand how natural and human systems interact through feedback mechanisms and affect land management choices among humans and ecosystem (e.g., carbon storage) and biophysical processes (e.g., erosion) in natural systems. One component of this program involves finding novel methods for data collection (e.g., unmanned aerial vehicles) that can be used to calibrate and validate models of natural systems at the resolution of decision makers. Another component of this program involves the design and construction of agent-based models to formalize our understanding of human decisions and their interaction with their environment in computer code. The most exciting, and remaining part, is coupling these two components together so that we may not only quantify the impact of representing their coupling, but more importantly to assess the impacts of changing climate, technology, and policy on human well-being, patterns of land use and land management, and ecological and biophysical aspects of our environment.

To achieve this overarching goal, my students and I conduct fieldwork that involves the use of state-of-the-art unmanned aerial vehicles (UAVs) in combination with ground-based light detection and ranging (LiDAR) equipment, RTK global positioning system (GPS) receivers, weather and soil sensors, and a host of different types of manual measurements. We bring these data together to make methodological advancements and benchmark novel equipment to justify its use in the calibration and validation of models of natural and human processes. By conducting fieldwork at high spatial resolutions (e.g., parcel level) we are able to couple our representation of natural system processes at the scale at which human actors make decisions and improve our understanding about how they react to changes and affect our environment.

Cristina Montañola Sales is an assistant professor at Institut Químic de Sarrià in Ramon Llull University, where she teaches subjects in ICT and statistics. She holds a PhD in Statistics and Operations Research and specializes in the investigation of novel quantitative methods for studying human behavior, such as agent-based models and spatio-temporal analysis. Her interdisciplinary research combines mathematics with social sciences, biomedicine and High-Performance Computing. She has studied various contexts, such as the dynamics of mobility of Gambian emigrants, demographic forecasting in South Korea, and ecological resilience of hunter-gatherers in India. Her research on tuberculosis transmissions and COVID-19 has advanced knowledge in epidemics, demographic dynamics and computational statistics. She has published articles and participated in international projects on simulation, parallel computing and global health.

Postdoctoral Research Associate at the CyberGIS Center for Advanced Digital and Spatial Studies, University of Illinois at Urbana-Champaign