Publication details

Disaster Risk Reduction in Agriculture through Geospatial (Big) Data Processing

Authors

ŘEZNÍK Tomáš LUKAS Vojtěch CHARVÁT Karel CHARVÁT Karel, mladší KŘIVÁNEK Zbyněk KEPKA Michal HERMAN Lukáš ŘEZNÍKOVÁ Helena

Year of publication 2017
Type Article in Periodical
Magazine / Source ISPRS International Journal of Geo-Information
MU Faculty or unit

Faculty of Science

Citation
Web on-line verze článku
Doi http://dx.doi.org/10.3390/ijgi6080238
Field Earth magnetism, geography
Keywords precision farming; machinery telemetry; wireless sensor network; remote sensing
Description Intensive farming on land represents an increased burden on the environment due to, among other reasons, the usage of agrochemicals. Precision farming can reduce the environmental burden by employing site specific crop management practices which implement advanced geospatial technologies for respecting soil heterogeneity. The objectives of this paper are to present the frontier approaches of geospatial (Big) data processing based on satellite and sensor data which both aim at the prevention and mitigation phases of disaster risk reduction in agriculture. Three techniques are presented in order to demonstrate the possibilities of geospatial (Big) data collection in agriculture: (1) farm machinery telemetry for providing data about machinery operations on fields through the developed MapLogAgri application; (2) agrometeorological observation in the form of a wireless sensor network together with the SensLog solution for storing, analysing, and publishing sensor data; and (3) remote sensing for monitoring field spatial variability and crop status by means of freely-available high resolution satellite imagery. The benefits of re-using the techniques in disaster risk reduction processes are discussed. The conducted tests demonstrated the transferability of agricultural techniques to crisis/emergency management domains.
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