Publication details
Visualizations of Uncertainties in Precision Agriculture: Lessons Learned from Farm Machinery
| Authors | |
|---|---|
| Year of publication | 2020 |
| Type | Article in Periodical |
| Magazine / Source | Applied Sciences |
| MU Faculty or unit | |
| Citation | |
| Web | on-line verze článku |
| Doi | http://dx.doi.org/10.3390/app10176132 |
| Keywords | yield measurements; point Big Data; uncertainty expression; interactive 3D visualization; ISO 19157 |
| Description | 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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