Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/30693
DC FieldValueLanguage
dc.contributor.authorKoumoulidis, Dimitrios-
dc.contributor.authorLeonidakis, Dimitrios-
dc.contributor.authorKatsenios, Nikolaos-
dc.contributor.authorEfthimiadou, Aspasia-
dc.date.accessioned2023-10-25T08:00:46Z-
dc.date.available2023-10-25T08:00:46Z-
dc.date.issued2020-06-14-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/30693-
dc.description.abstractAgriculture in relation to climate, is one of the key issues nowadays as climate change influences greatly agriculture and agriculture has an extended environmental impact. This paper presents the structure and key features of a decision support information system that will cover the major time and money-consuming problem related to cotton cultivation, which is the issue of irrigation. Water consumed by agriculture has a great environmental footprint. Dealing with this specific issue requires integrated management, both in terms of environmental protection and economic sustainability. The creation and usage of a decision support system for cotton cultivation, based on remote sensing and in-situ data is an urgent need for cotton cultivation, but also for modern agriculture in general, as it will save natural resources and at the same time will reduce costs. The proposed system is estimated to significantly reduce the use of irrigation water, thus reducing cotton cultivations aquatic footprint. The main objective of this information system is to provide a valuable consulting tool for the agronomist and the farmer, to support their daily activities, keeping in mind the minimization of the environmental footprint of cultivating cotton. The presented information system will combine innovative means of data recovery from IoT sensors, remote sensing data, and agricultural models predicting phenological stages and other parameters related to the quality and risks of cotton cultivations. Farmers will have access through a user-friendly web application from their personal computers and mobile devices.en_US
dc.language.isoenen_US
dc.rightsAttribution-NoDerivatives 4.0 Internationalen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nd/4.0/*
dc.subjectPrecision agricultureen_US
dc.subjectSatellite remote sensingen_US
dc.subjectDecision support systemsen_US
dc.subjectAgronomic modelsen_US
dc.subjectIrrigationen_US
dc.subjectCottonen_US
dc.titleReducing aquatic footprint of cotton cultivation, by developing a decision support system using satellites and sensorsen_US
dc.typeConference Papersen_US
dc.collaborationOpen University Cyprusen_US
dc.subject.categoryNATURAL SCIENCESen_US
dc.countryCyprusen_US
dc.countryGreeceen_US
dc.subject.fieldAgricultural Sciencesen_US
dc.relation.conferenceWater Efficiency & Climate Resilient Agriculture International Conferenceen_US
cut.common.academicyear2020-2021en_US
item.fulltextNo Fulltext-
item.cerifentitytypePublications-
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_c94f-
item.openairetypeconferenceObject-
item.languageiso639-1en-
crisitem.author.orcid0000-0003-4321-7181-
Appears in Collections:Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation
CORE Recommender
Show simple item record

Page view(s) 50

86
Last Week
0
Last month
10
checked on May 19, 2024

Google ScholarTM

Check


This item is licensed under a Creative Commons License Creative Commons