Land-change simulation models such as the Land-use and Carbon Scenario Simulator (LUCAS), allow researchers to simulate land-use/land-change over multiple spatial and temporal domains, model iterations, and land-cover states and transitions. These models can also track the impacts of alternative management and disturbance scenarios on ecosystem carbon storage and flux (transfer of carbon), and other variables such as water-demand. As such, model outputs are often large and can contain a mixture of spatial and non-spatial data, leading to difficulties in managing, sharing and visualizing results. In collaboration with the UC Berkeley Geospatial Innovation Facility (GIF), researchers at the USGS developed a framework for managing and visualizing these datasets. An existing general framework, called Syncrosim built by ApexRMS, was used to manage land-change state and transition data, as well as carbon storage and flux datasets that vary over time, space, scenario and iteration, within a SQLite database. A Python-based API was developed to query data within the database and a web application was built to explore and visualize datasets managed within the framework. Together, these tools will allow researchers to more easily manage multiple land-use and carbon change datasets and quickly compare spatial and non-spatial data over multiple variables.
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