Fuel load estimation is essential for assessing fire hazards, developing fire behaviour predictive models, evaluating the impacts of alternative fuels and treatments to protect lives and ecosystems, and implementing decision support systems for fire management. Numerous sampling methods, protocols, and designs have been developed to quantify fuel loading. Keane (2015) arranged a wide range of techniques from the easiest to the most difficult, considering the uncertainty level. Among these approaches, the visual technique is an indirect method encompassing fuel load quantification through the association of loads by comparing with existing data, visually comparing the fuel condition with other reference conditions. 

Surface fuel loading is visually estimated using a set of pictures representing average stand conditions for different vegetation types. When developing the digital photo series (DPS) (https://research.fs.usda.gov/pnw/projects/digitalphotoseries), fuel component loadings are measured, and the summary of the loadings is reported next to the picture (Fig. 1). For years, fire managers in the United States have used photographs of fuel complexes as decision-making and training aids.

Despite the clear advantages of using this technique, we must be conscious that fuel load estimation using photo series is often inaccurate and difficult to repeat across observers and vegetation types (Sikkink and Keane, 2008). Some fine fuel components, such as 1hr dead woody fuel, litter, or duff, can be hidden by the vegetation in the pictures; thus, underestimating these components is quite frequent.