Applications of ANN for Agriculture Using Remote Sensed Data

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Author(s): Geetha M. (Bapuji Institute of Engineering and Technology, India), Asha Gowda Karegowda (Siddaganga Institute of Technology, India), Nandeesha Rudrappa (Siddaganga Institute of Technology, India)and Devika G. (Government Engineering College, K. R. Pet, India)
Copyright: 2022
Pages: 23
Source title: Research Anthology on Artificial Neural Network Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-6684-2408-7.ch047

Keywords: Artificial Intelligence / Computer Science & IT / Engineering Science Reference / Neural Networks

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Abstract

Ever since the advent of modern geo information systems, tracking environmental changes due to natural and/or manmade causes with the aid of remote sensing applications has been an indispensable tool in numerous fields of geography, most of the earth science disciplines, defense, intelligence, commerce, economics, and administrative planning. Remote sensing is used in science and technology, and through it, an object can be identified, measured, and analyzed without physical presence for interpretation. In India remote sensing has been using since 1970s. One among these applications is the crop classification and yield estimation. Using remote sensing in agriculture for crop mapping, and yield estimation provides efficient information, which is mainly used in many government organizations and the private sector. The pivotal sector for ensuring food security is a major concern of interest in these days. In time, availability of information on agricultural crops is vital for making well-versed decisions on food security issues.

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Applications of ANN for Agriculture Using Remote Sensed Data

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