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CropSAT – A decision support system for practical use of satellite images in precision agriculture

Alshihabi, Omran and Piikki, Kristin and Söderström, Mats (2020). CropSAT – A decision support system for practical use of satellite images in precision agriculture. I/In: First International Conference on Smart Information and Communication Technologies, SmartICT 2019.
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Abstract

CropSAT is an interactive decision support system (DSS) that provides vegetation index (VI) maps from Sentinel-2 data all across the globe and lets users delineate fields, design variable-rate application of user specified inputs (mainly nitrogen, but also e.g. fungicides or growth regulators) based on the VI maps. The CropSAT DSS was initially developed in a research project at the Swedish University of Agricultural Sciences (SLU), and has since its launch in 2015 been continuously developed in a private-public-partnership between SLU, private companies and the Swedish Board of Agriculture. Now it has global coverage, is continuously updated with new satellite images, and is provided free-of-charge in multiple languages (including Arabic and French). The present study aims at describing the CropSAT systems, summarizing research results from the ongoing developmental process and pointing to opportunities for applications in precision agriculture, e.g. in Morocco and other countries in North Africa.

Authors/Creators:Alshihabi, Omran and Piikki, Kristin and Söderström, Mats
Title:CropSAT – A decision support system for practical use of satellite images in precision agriculture
Series Name/Journal:Lecture Notes in Electrical Engineering
Year of publishing :2020
Volume:684
Page range:415-421
Number of Pages:7
Publisher:Springer International Publishing
ISBN for printed version:978-3-030-53186-7
ISBN for electronic version:978-3-030-53187-4
ISSN:1876-1100
Language:English
Publication Type:Conference Paper (UNSPECIFIED)
Article category:Scientific peer reviewed
Version:Published version
Full Text Status:Public
Subjects:(A) Swedish standard research categories 2011 > 4 Agricultural Sciences > 401 Agricultural, Forestry and Fisheries > Agricultural Science
(A) Swedish standard research categories 2011 > 1 Natural sciences > 102 Computer and Information Science > 10206 Computer Engineering
URN:NBN:urn:nbn:se:slu:epsilon-p-107059
Permanent URL:
http://urn.kb.se/resolve?urn=urn:nbn:se:slu:epsilon-p-107059
Additional ID:
Type of IDID
DOI10.1007/978-3-030-53187-4_45
ID Code:17482
Faculty:NJ - Fakulteten för naturresurser och jordbruksvetenskap
Department:(NL, NJ) > Dept. of Soil and Environment
(S) > Dept. of Soil and Environment
Deposited By: SLUpub Connector
Deposited On:27 Jan 2021 11:28
Metadata Last Modified:27 Jan 2021 11:28

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