SRI’s Center for the Study of Cultural Landscapes (CSCL) specializes in innovating approaches to data modeling, data integration, data synthesis, geospatial analysis, archaeological modeling, and landscape management. CSCL staff work with agencies, cultural resource management programs, and preservation organizations to identify solutions to preservation risks, such as those arising from climate change, land use, and technological obsolescence. CSCL places a strong emphasis on leveraging and integrating available cultural and environmental datasets to interpret and forecast patterns in site location, significance, condition, and vulnerability from a multi-scalar, landscape perspective. Our efforts include the analysis, assessment, and innovation of field, laboratory, and interpretive methods and the development of analytical and software tools for interpreting settlement and land use. In turn, we harness these insights to develop management plans, protocols, and recommendations.

Products and Services: CSCL provides analytical and interpretive products and services based in data science, geospatial analytics, and statistical modeling. These include the following:

• Archaeological research synthesis and management recommendations – the meta-analysis and synthesis of large bodies of cultural resource information and related research to develop comprehensive research designs, management recommendations, and archaeological syntheses for governmental bodies and other organizations.
• Contextual analysis – analysis of the relationship of heritage resources to their environment and each other, following approaches such as settlement analysis, viewshed and visibility analysis, cost surface analysis, suitability-capability analysis, and landscape ecology.
• Buried sites modeling – the development and validation of models of buried site potential that operationalize geoarchaeological knowledge and formation processes within a geospatial environment.
• Data collection and management – the development of data models, apps, and tools for collecting and managing archaeological and environmental data.
• Data quality modeling – modeling of the effects of discovery and recording methods and environmental conditions on the reliability and representativeness of archaeological data; evaluation of the adequacy and accuracy of CRM and environmental datasets for management purposes.
• Locational modelin – the development and validation of models of archaeological site location using advanced statistical techniques, using both inductive and deductive methods, as appropriate.
• Significance modeling – the development of algorithms, formal frameworks, and database capabilities for organizing archaeological sites into significance categories based on a core set of site attributes, including artifact and feature content, assemblage size, integrity, and environmental and depositional context.
• Vulnerability modeling – modeling of the location, timing, and severity of potential impacts on heritage resources, such as those arising from climate change and development.