Volunteer classifications of images from the Cropland Capture game

Each entry represents a single classification of a single image by a volunteer rater. The dataset contains six columns: imgid: The unique identifier for each image used in the Cropland Capture campaign<br> userid: The unique identifier for each volunteer in the Cropland Capture campaign<br> rating: The answer provided; can be only one of the following:<br> 1: yes cropland<br> 2: no cropland<br> 0: maybe <br> date: Timestamp of the rating<br> ratingid: The unique identifier of the rating (this is different for each data row)<br> platform: What interface did the volunteer use to provide this rating?<br> 1: iPhone5<br> 2: iPhone, other models<br> 3: iPad<br> 4: Browser<br> &gt;100: Android; different numbers indicate the screen size in pixels For more information, please see the following publications: Salk, CF, T Sturn, L See, S Fritz (2017). Limitations of majority agreement in crowdsourced image interpretation. <em>Transactions in GIS</em>, 21: 207–223. Salk, CF, T Sturn, L See, S Fritz (2016). Local knowledge and professional background have a minimal impact on volunteer citizen science performance in a land-cover classification task. <em>Remote Sensing</em>, 8: 744. Salk, CF, T Sturn, L See, S Fritz and C Perger (2016). Assessing quality of volunteer crowdsourcing contributions: Lessons from the Cropland Capture game. <em>International Journal of Digital Earth</em>, 9(4): 410-426.