Accurate and timely information on the global cropland extent is critical for food security monitoring, water management and earth system modeling. Principally, it allows for analyzing satellite image time-series to assess the crop conditions and permits isolation of the agricultural component to focus on food security and impacts of various climatic scenarios. However, despite its critical importance, accurate information on the spatial extent, cropland mapping with remote sensing imagery remains a major challenge. Following an exhaustive identification and collection of existing land cover maps, a multi-criteria analysis was designed at the country level to evaluate the fitness of a cropland map with regards to four dimensions: its timeliness, its legend, its resolution adequacy and its confidence level. As a result, a Unified Cropland Layer that combines the fittest products into a 250 m global cropland map was assembled. With an evaluated accuracy ranging from 82% to 95%, the Unified Cropland Layer successfully improved the accuracy compared to single global products.

Data sharing over the internet is increasingly efficient and increasingly anonymous. This growing anonymity makes it difficult for data users to exchange feedback: interesting ideas, innovations, ancillary data, concerns about data quality, etcetera. For data producers not knowing the end-users makes it more difficult to collect end-user feedback and tailor the production process to users needs. Feedback can be exchanged through social networks, in other words contacts with other users. Very little is known about such social networks in the case of data sharing. In this paper we present an analysis of the social networks associated with two land cover datasets. We found that most users have zero to two links to other users and virtually no links to users in other her organisations. Without these links, it seems almost impossible to identify users of a particular dataset. Internet technology can help but is currently not used to enhance exchange of feedback within the user community.