Title: Advanced visualisation of big data for agriculture as part of databio development
Authors: Charvát, Karel
Řezník, Tomáš
Lukas, Vojtěch
Charvát, Karel, jr.
Jedlička, Karel
Palma, Raul
Berzins, Raitis
Citation: CHARVÁT, K., ŘEZNÍK, T., LUKAS, V., CHARVÁT, K.j., JEDLIČKA, K., PALMA, R., BERZINS, R. Advanced visualisation of big data for agriculture as part of databio development. In IEEE International Symposium on Geoscience and Remote Sensing IGARSS. NEW YORK, NY 10017: IEEE, 2018. s. 415-418. ISBN 978-1-5386-7150-4 , ISSN 2153-6996.
Issue Date: 2018
Publisher: IEEE
Document type: konferenční příspěvek
conferenceObject
URI: http://hdl.handle.net/11025/33724
ISBN: 978-1-5386-7150-4
ISSN: 2153-6996
Keywords in different language: precision agriculture;big data;yield productivity zones;visualisation
Abstract: There is an increasing tension in agriculture between the requirements to assure full safety on the one hand and keep costs under control on the other hand, both with respect to (inter) national strategies. Farmers need to measure and understand the impact of huge amount and variety of data which drive overall quality and yield in their fields. Among others, those are local weather data, Global Navigation System of Systems data, orthophotos and satellite imagery, data on soil specifics etc. A strong need to secure Big Data arises due to various repositories and heterogeneous sources. Data storage and visualisation requirements are in some cases competing as they are a common interest as well as a threat that helps one part of a value chain to gain a higher profit. As demonstrated in this paper, handling (Big) data is therefore a sensitive topic, where trust of producers on data security is essential.
Abstract in different language: There is an increasing tension in agriculture between the requirements to assure full safety on the one hand and keep costs under control on the other hand, both with respect to (inter) national strategies. Farmers need to measure and understand the impact of huge amount and variety of data which drive overall quality and yield in their fields. Among others, those are local weather data, Global Navigation System of Systems data, orthophotos and satellite imagery, data on soil specifics etc. A strong need to secure Big Data arises due to various repositories and heterogeneous sources. Data storage and visualisation requirements are in some cases competing as they are a common interest as well as a threat that helps one part of a value chain to gain a higher profit. As demonstrated in this paper, handling (Big) data is therefore a sensitive topic, where trust of producers on data security is essential.
Rights: Plný text není přístupný.
© IEEE
Appears in Collections:Konferenční příspěvky / Conference Papers (KGM)
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