
Proceedings Paper
Applications of Sentinel-2 data for agriculture and forest monitoring using the absolute difference (ZABUD) index derived from the AgroEye software (ESA)Format | Member Price | Non-Member Price |
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Paper Abstract
To convince new users of the advantages of the Sentinel_2 sensor, a simplification of classic remote sensing tools allows
to create a platform of communication among domain specialists of agricultural analysis, visual image interpreters and
remote sensing programmers.
An index value, known in the remote sensing user domain as “Zabud” was selected to represent, in color, the essentials
of a time series analysis. The color index used in a color atlas offers a working platform for an agricultural field control.
This creates a database of test and training areas that enables rapid anomaly detection in the agricultural domain. The use
cases and simplifications now function as an introduction to Sentinel_2 based remote sensing, in an area that before
relies on VHR imagery and aerial data, to serve mainly the visual interpretation. The database extension with detected
anomalies allows developers of open source software to design solutions for further agricultural control with remote
sensing.
Paper Details
Date Published: 2 November 2017
PDF: 13 pages
Proc. SPIE 10421, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIX, 104211A (2 November 2017); doi: 10.1117/12.2277828
Published in SPIE Proceedings Vol. 10421:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XIX
Christopher M. U. Neale; Antonino Maltese, Editor(s)
PDF: 13 pages
Proc. SPIE 10421, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIX, 104211A (2 November 2017); doi: 10.1117/12.2277828
Show Author Affiliations
R. de Kok, ProGea Consulting (Poland)
P. Wężyk, Univ. of Agriculture in Krakow (Poland)
P. Wężyk, Univ. of Agriculture in Krakow (Poland)
M. Papież, AGH Univ. of Science and Technology (Poland)
L. Migo, ProGea Consulting (Poland)
L. Migo, ProGea Consulting (Poland)
Published in SPIE Proceedings Vol. 10421:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XIX
Christopher M. U. Neale; Antonino Maltese, Editor(s)
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