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Hyperspectral Remote Sensing For Agricultural Management: A Survey

by B. D. Jadhav, P. M. Patil
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 106 - Number 7
Year of Publication: 2014
Authors: B. D. Jadhav, P. M. Patil
10.5120/18536-9750

B. D. Jadhav, P. M. Patil . Hyperspectral Remote Sensing For Agricultural Management: A Survey. International Journal of Computer Applications. 106, 7 ( November 2014), 38-43. DOI=10.5120/18536-9750

@article{ 10.5120/18536-9750,
author = { B. D. Jadhav, P. M. Patil },
title = { Hyperspectral Remote Sensing For Agricultural Management: A Survey },
journal = { International Journal of Computer Applications },
issue_date = { November 2014 },
volume = { 106 },
number = { 7 },
month = { November },
year = { 2014 },
issn = { 0975-8887 },
pages = { 38-43 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume106/number7/18536-9750/ },
doi = { 10.5120/18536-9750 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:38:48.848545+05:30
%A B. D. Jadhav
%A P. M. Patil
%T Hyperspectral Remote Sensing For Agricultural Management: A Survey
%J International Journal of Computer Applications
%@ 0975-8887
%V 106
%N 7
%P 38-43
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Hyperspectral sensors are devices that acquire images with narrow bands (less than 20nm) with continuous measurement. It extracts spectral signatures of objects or materials to be observed. Hyperspectral have more than 200 bands. Hyperspectral remote sensing has been used over a wide range of applications, such as agriculture, forestry, geology, ecological monitoring, atmospheric compositions and disaster monitoring. This review details concept of hyperspectral remote sensing; processing of hyperspectral data. It also focuses on the application of hyperspectral imagery in agricultural development. For example, hyperspectral image processing is used in the monitoring of plant diseases, insect pests and invasive plant species; the estimation of crop yield; and the fine classification of crop distributions.

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Index Terms

Computer Science
Information Sciences

Keywords

Hyperspectral Multispectral Remote sensing Spectrometer

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