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Conference paper - Peer-reviewed, 2020

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

Alshihabi, Omran; Piikki, Kristin; Söderström, Mats;

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.

Published in

Lecture Notes in Electrical Engineering

2020, volume: 684, pages: 415-421
Book title: Advances in Smart Technologies Applications and Case Studies : Selected Papers from the First International Conference on Smart Information and Communication Technologies, SmartICT 2019, September 26–28, 2019, Saidia, Morocco
ISBN: 978-3-030-53186-7, eISBN: 978-3-030-53187-4
Publisher: Springer

Conference


International conference on smart Information & communication Technologies, 190926-190928, Saidia, Morocco

Authors' information

Swedish University of Agricultural Sciences, Department of Soil and Environment
Piikki, Kristin (Persson, Kristin)
Swedish University of Agricultural Sciences, Department of Soil and Environment
Swedish University of Agricultural Sciences, Department of Soil and Environment

UKÄ Subject classification

Computer Engineering
Agricultural Science

Publication Identifiers

DOI: https://doi.org/10.1007/978-3-030-53187-4_45

URI (permanent link to this page)

https://res.slu.se/id/publ/107059