Across all societies, humans depend on goods received from nature, termed ecosystem services. However, cultural ecosystem services (CES), the non-material benefits people obtain from ecosystems, are often overlooked in land-use decision making due to their intangible nature. This study aimed to evaluate three possible survey methods for site-based CES data collection; language-based supervised surveys (in which interviewers conduct surveys in real-time, recording verbal responses), language-based unsupervised surveys (respondents complete written surveys without an interviewer), and image-based unsupervised surveys (respondents complete surveys via image selection without an interviewer). Language-based supervised surveys were found to be more efficient in collecting CES data than language-/image-based unsupervised surveys, with a mean completion rate over 1.5-fold greater than either unsupervised survey; furthermore, survey completion was over twice as fast, and less than a sixth of the monetary cost per respondent compared to unsupervised surveys. The site-based assessment developed in this study provides robust data, and is shown to provide rapid and useful feedback to land-use decision makers. We recommend that rapid, site-based assessment methods are utilised to collect the information required to support CES-related decision making.