| ŘEZNÍK, Tomáš, Vojtěch LUKAS, Karel CHARVÁT, Karel, mladší CHARVÁT, Zbyněk KŘIVÁNEK, Michal KEPKA, Lukáš HERMAN and Helena ŘEZNÍKOVÁ. Disaster Risk Reduction in Agriculture through Geospatial (Big) Data Processing. ISPRS International Journal of Geo-Information. Basel, SWITZERLAND: MDPI, 2017, vol. 6, No 8, p. 1-11. ISSN 2220-9964. Available from: https://dx.doi.org/10.3390/ijgi6080238. |
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@article{1386575,
author = {Řezník, Tomáš and Lukas, Vojtěch and Charvát, Karel and Charvát, Karel, mladší and Křivánek, Zbyněk and Kepka, Michal and Herman, Lukáš and Řezníková, Helena},
article_location = {Basel, SWITZERLAND},
article_number = {8},
doi = {http://dx.doi.org/10.3390/ijgi6080238},
keywords = {precision farming; machinery telemetry; wireless sensor network; remote sensing},
language = {eng},
issn = {2220-9964},
journal = {ISPRS International Journal of Geo-Information},
title = {Disaster Risk Reduction in Agriculture through Geospatial (Big) Data Processing},
url = {http://www.mdpi.com/2220-9964/6/8/238},
volume = {6},
year = {2017}
}
TY - JOUR
ID - 1386575
AU - Řezník, Tomáš - Lukas, Vojtěch - Charvát, Karel - Charvát, Karel, mladší - Křivánek, Zbyněk - Kepka, Michal - Herman, Lukáš - Řezníková, Helena
PY - 2017
TI - Disaster Risk Reduction in Agriculture through Geospatial (Big) Data Processing
JF - ISPRS International Journal of Geo-Information
VL - 6
IS - 8
SP - 1-11
EP - 1-11
PB - MDPI
SN - 22209964
KW - precision farming
KW - machinery telemetry
KW - wireless sensor network
KW - remote sensing
UR - http://www.mdpi.com/2220-9964/6/8/238
L2 - http://www.mdpi.com/2220-9964/6/8/238
N2 - 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.
ER -
ŘEZNÍK, Tomáš, Vojtěch LUKAS, Karel CHARVÁT, Karel, mladší CHARVÁT, Zbyněk KŘIVÁNEK, Michal KEPKA, Lukáš HERMAN and Helena ŘEZNÍKOVÁ. Disaster Risk Reduction in Agriculture through Geospatial (Big) Data Processing. \textit{ISPRS International Journal of Geo-Information}. Basel, SWITZERLAND: MDPI, 2017, vol.~6, No~8, p.~1-11. ISSN~2220-9964. Available from: https://dx.doi.org/10.3390/ijgi6080238.
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