Visualizations of Uncertainties in Precision Agriculture: Lessons Learned from Farm Machinery

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Publikace nespadá pod Fakultu sportovních studií, ale pod Přírodovědeckou fakultu. Oficiální stránka publikace je na webu muni.cz.
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ŘEZNÍK Tomáš KUBÍČEK Petr HERMAN Lukáš PAVELKA Tomáš LEITGEB Šimon KLOCOVÁ Martina LEITNER Filip

Rok publikování 2020
Druh Článek v odborném periodiku
Časopis / Zdroj Applied Sciences
Fakulta / Pracoviště MU

Přírodovědecká fakulta

Citace
www on-line verze článku
Doi http://dx.doi.org/10.3390/app10176132
Klíčová slova yield measurements; point Big Data; uncertainty expression; interactive 3D visualization; ISO 19157
Popis Detailed measurements of yield values are becoming a common practice in precision agriculture. Field harvesters generate point Big Data as they provide yield measurements together with dozens of complex attributes in a frequency of up to one second. Such a flood of data brings uncertainties caused by several factors: accuracy of the positioning system used, trajectory overlaps, raising the cutting bar due to obstacles or unevenness, and so on. This paper deals with 2D and 3D cartographic visualizations of terrain, measured yield, and its uncertainties. Four graphic variables were identified as credible for visualizations of uncertainties in point Big Data. Data from two plots at a fully operational farm were used for this purpose. ISO 19157 was examined for its applicability and a proof-of-concept for selected uncertainty expression was defined. Special attention was paid to spatial pattern interpretations.
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