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The Composite Burn Index (CBI) is commonly linked to remotely sensed data to understand spatial and temporal patterns of burn severity. However, a comprehensive understanding of the tradeoffs between different methods used to model CBI with remotely sensed data is lacking. To help understand the current state of the science, provide a blueprint towards conducting broad-scale meta-analyses, and identify key decision points and potential rationale, we conducted a review of studies that linked remotely sensed data to continuous estimates of burn severity measured with the CBI and related methods. We provide a roadmap of the different methodologies applied and examine potential rationales used to justify them. Our findings largely reflect methods applied in North America – particularly in the western USA – due to the high number of studies in that region. We find the use of different methods across studies introduces variations that make it difficult to compare outcomes. Additionally, the existing suite of comparative studies focuses on one or few of many possible sources of uncertainty. Thus, compounding error and propagation throughout the many decisions made during analysis is not well understood. Finally, we suggest a broad set of methodological information and key rationales for decision-making that could facilitate future reviews. This review paper summarises methodologies used to link field-based measures of severity, based on the Composite Burn Index (CBI), with remotely sensed data from optical sensors. It presents key analytical decisions and research gaps in the existing literature. [ABSTRACT FROM AUTHOR]