USING OF RPAS IN PRECISION AGRICULTURE
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21110%2F17%3A00313011" target="_blank" >RIV/68407700:21110/17:00313011 - isvavai.cz</a>
Result on the web
<a href="https://sgemworld.at/sgemlib/spip.php?article9444" target="_blank" >https://sgemworld.at/sgemlib/spip.php?article9444</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.5593/sgem2017/23/S10.041" target="_blank" >10.5593/sgem2017/23/S10.041</a>
Alternative languages
Result language
angličtina
Original language name
USING OF RPAS IN PRECISION AGRICULTURE
Original language description
Remotely Piloted Aircraft Systems (RPAS), which have become more popular in recent years, can obtain data on demand in a short time with a resolution within centimeters. Data collection is environmentally friendly and low-cost from an economical point of view; of course it is best for small areas, such as square km’s only by using winged drones or in a few hectares by use of multicopters. Both types have their advantages and disadvantages. Our laboratory of photogrammetry has, since 2012, focused on using RPAS (drones, UAV) for the mapping or monitoring of agriculture. For this purpose it is better to use winged drones – we have EBee drones at our disposal with new equipment to include a thermal imager, multispectral imager, NIR, NIR red-edge and VIS camera. This is typically remote sensing equipment and is now usable on small areas for local case projects. Last year we started new projects in precise agriculture research, and we tested the equipment on an agricultural site near Plana city (western part of the Czech Republic), near the village of Vysoké Sedlište. On the test site we located fields of corn, rye and grassland. We collected data from the end of March till August in 2016 with a thermal and multispectral imager. A typical flight lasted 30 minutes, taking 200 multispectral images or 6000 thermal images (due to the order of magnitude, lower resolution images with 640x512 pixels were collected with 90% overlapping and were much faster by multispectral camera). Outputs from these instruments are thematic maps, NDVI progress, thermal index maps and unsupervised classification of five spectral channels using remote sensing software’s like Geomatica or Envi. An output shows unequal development of vegetation in different locations.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
17th International Multidisciplinary Scientific Geoconference, Conference Proceedings Volume 17, Informatics, Geoinformatics and Remote Sensing Issue 22, Geodesy and Mine Surveying
ISBN
978-619-7408-02-7
ISSN
1314-2704
e-ISSN
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Number of pages
8
Pages from-to
331-338
Publisher name
International Multidisciplinary Scientific GeoConference SGEM
Place of publication
Sofia
Event location
Albena
Event date
Jun 27, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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