Indoor map is a fundamental element of indoor location-based services (ILBS). However, traditional indoor mapping techniques are labor-intensive and time-consuming. The advancement of smartphones offers great opportunities for crowdsourcing-based indoor mapping, which is one of the most promising applications due to its low cost and flexibility. Over the last decade, many crowdsourcing-based indoor mapping solutions using smartphones have been proposed. This article provides a systematic review of these works. Different from former surveys, we classify the indoor mapping process by the stage of map construction. In particular, we highlight the two key steps, geospatial-element acquisition, and indoor-map construction, and provide state-of-the-art techniques on these topics. Then, we systematically review the crowdsourcing-based indoor mapping solutions under grid-based, landmark-based, and semantic maps. In addition to covering the principles, benefits, and challenges, these systems are compared in terms of sensors, participation, output, experimental environment, and reported accuracy. Besides these existing performance criteria, we extract quantitative performance criteria that are suitable to evaluate crowdsourcing-based indoor mapping solutions. Finally, we present open issues and future research directions.