Use-Specific Considerations for Optimising Data Quality Trade-Offs in Citizen Science: Recommendations from a Targeted Literature Review to Improve the Usability and Utility for the Calibration and Validation of Remotely Sensed Products

Abstract

The growth of citizen science presents a valuable potential source of calibration and validation data for environmental remote sensing at greater spatial and temporal scales, and with greater cost efficiency than is achievable by professional in situ reference-data collection alone. However, the frequent mismatch between in situ data-quality requirements for remote-sensing-product development and current data quality assurance in citizen science presents a significant challenge if widespread use of these complementary data sources is to be achieved. To evaluate the scope of this challenge, we conducted a targeted literature review into the nature of data-quality issues faced by citizen-science projects for routine incorporation into terrestrial environmental-monitoring systems. From the literature, we identify the challenges and trade-offs to inform best-practice implementation of data quality assurance in citizen-science projects. To assist practitioners in implementing our findings, we grouped these themes by stage of citizen-science project: (1) program planning and design; (2) participant engagement; (3) data collection; and (4) data processing. As a final step, we used our findings as the basis to formulate guiding questions that can be used to inform decision making when choosing optimal data-quality-improvement and assurance strategies for use of citizen science in remote-sensing calibration and/or validation. Our aim is to enhance future development of citizen-science projects for use with remote sensing in environmental monitoring.