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Abstract Crowdsourced data can provide spatially explicit data on the contribution of nature to people. Spatial information is essential for effectively managing the diverse relationships that people have with nature, but the potential and limits of using crowdsourcing data to generate maps for conservation purposes need further research. Passive crowdsourcing tools include social media platforms where photos and user‐generated tags are shared among users, whereas active crowdsourcing, such as public participatory geographic information system (PPGIS), provides an online platform for mapping place attributes such as values, experiences and preferences. In this study, we assess the spatial information gained through using Flickr (a photo sharing platform) and PPGIS (an online mapping platform) platforms for conservation planning to understand differences and similarities on the spatial distribution of values captured by the two platforms, and to identify what environmental and infrastructure variables correlate best with the distribution of values. We test these tools in Southern Norway including protected areas and the surrounding zones. We analysed non‐spatial (using chi‐square and Spearman rank correlation) and spatial (using clustering, Maxent and distribution overlap) data to identify differences between the two datasets and the values represented therein. We found large differences in spatial distribution using these two datasets, with Flickr data concentrated outside the protected areas and near roads, whereas PPGIS provided more fine‐scale data on diverse values in locations inaccessible by roads within the protected areas. Flickr can be used for generating regional scale data of scenic landscapes or routes, but PPGIS performs better for management of nature qualities appreciated by different user groups within protected areas. We discuss the pros and cons of using each data source and when each dataset is more suitable to be used in protected area management. A free Plain Language Summary can be found within the Supporting Information of this article.

Abstract Increased visitation to protected areas could have adverse impacts on the conservation values in the protected areas, and therefore effective visitor monitoring methods are needed to meet the complex management challenges that arise. Collecting data on human impacts is highly time consuming, thus requiring more effective tools that allow for high‐quality and long‐term measurements. In this study, we show how unmanned aerial vehicles (i.e. UAV or drones) could be used to monitor tourism impacts in protected areas. Tourism has boomed in national parks in Norway in recent years, such as in Jotunheimen National Park for which this study applies. We test the use of drones on a site where new tourist facilities will be established to set a baseline to identify future changes. We demonstrate how drones could help protected area management by monitoring visitor use patterns and commonly associated impacts such as trail condition (width and depth), vegetation structure and disturbances, informal trail proliferation, trampling, and trash and other impacts along the trails. We assessed accuracy and reliability compared with intensive field measurements of impacts and found low‐cost drones to be effective in mapping the study area with a resolution of 0.5 cm/pixel: drone derived trail measurements were comparable to traditional measurements with a negligible divergence on trail width measurements and a consistent 1.05 cm divergence on trail depth measurements that can be corrected with a few validation points. In addition, we created a high‐resolution vegetation classification map that could be used as a baseline for monitoring impacts. We conclude that drones can effectively contribute to visitor monitoring by reducing time spent in the field and by providing high‐resolution time series that could be used as baseline to measure tourism impacts on conservation values in protected areas.