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Review of the Applications of Satellite Remote Sensing in Organic Farming (Part I)

Chanev, Milen and Filchev, Lachezar (2023) Review of the Applications of Satellite Remote Sensing in Organic Farming (Part I). Aerospace Research in Bulgaria., 35, pp. 183-191.

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Document available online at: http://journal.space.bas.bg/arhiv/n%2035/Articles/18_Chanev.pdf


Summary in the original language of the document

Organic farming is a much more sustainable farming system than conventional farming. It is part of humanity's efforts to preserve biodiversity and provides healthy and safe food to humans. Remote sensing methods are widely used in agriculture. Their use will help the transition from conventional to organic farming. They can help farmers choose the most suitable place to build an organic farm. Remote sensing methods are a very powerful tool for weed control in organic farming. They can be used to determine the level of stress that crops experience. They provide a good opportunity to forecast yields on organic farms. Remote sensing methods can optimize fertilization on organic farms. They can be used to distinguish between organic and conventional agriculture, as well as to monitor biodiversity in agricultural areas. Remote sensing methods can help organic farmers make timely and adequate decisions in managing their farms.


EPrint Type:Journal paper
Keywords:Remote Sensing, Satellite data, Precision farming, Organic farming
Agrovoc keywords:
Language
Value
URI
English
remote sensing
http://aims.fao.org/aos/agrovoc/c_6498
English
satellite data
UNSPECIFIED
English
precision farming -> precision agriculture
http://aims.fao.org/aos/agrovoc/c_92363
English
organic farming -> organic agriculture
http://aims.fao.org/aos/agrovoc/c_15911
Subjects:"Organics" in general
Farming Systems
Animal husbandry
Crop husbandry
Values, standards and certification
Food systems
Environmental aspects
Knowledge management
Research affiliation: Bulgaria
Bulgaria > Other institutions Bulgaria
ISSN:1313 - 0927
DOI:10.3897/arb.v35.e18
Deposited By: Chanev, Milen Rusev
ID Code:46111
Deposited On:21 May 2023 15:28
Last Modified:21 May 2023 15:28
Document Language:English
Status:Published
Refereed:Peer-reviewed and accepted

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