During the last 10 years, the Institute for Environmental Research and Sustainable Development of the National Observatory of Athens has developed and operates a network of automated weather stations across Greece. The motivation behind the network development is the monitoring of weather conditions in Greece with the aim to support not only the research needs (weather monitoring and analysis, weather forecast skill evaluation) but also the needs of various communities of the production sector (agriculture, constructions, leisure and tourism, etc.). By the end of 2016, 335 weather stations are in operation, providing real‐time data at 10‐min intervals. This paper provides information about the logistics of this network, including real‐time applications of the collected data as well as information on the quality control protocols, the construction of the station data and metadata repository and the means through which the data are made available to users.

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A key goal of contemporary agriculture is to dramatically increase production of food, feed, fiber, and biofuel products in a sustainable fashion, facing the pressure of diminishing farm labor supply. Agricultural robots can accelerate plant breeding and advance data-driven precision farming with significantly reduced labor inputs by providing task-appropriate sensing and actuation at fine spatiotemporal resolutions. This article highlights the distinctive challenges imposed on ground robots by agricultural environments, which are characterized by wide variations in environmental conditions, diversity and complexity of plant canopy structures, and intraspecies biological variation of physical and chemical characteristics and responses to the environment. Existing approaches to address these challenges are presented, along with their limitations; possible future directions are also discussed. Two key observations are that biology (breeding) and horticultural practices can reduce variabilities at the source and that publicly available benchmark data sets are needed to increase perception robustness and performance despite variability.