Crop Detection and Classification using Remote Sensing Images
N.V.S Natteshan1, N. Suresh Kumar2
1N.V.S Natteshan, Research Scholar, School of CSE, VIT University, Vellore (Tamil Nadu), India.
2Dr. N. Suresh Kumar, Associate Professor, School of CSE, VIT University, Vellore (Tamil Nadu), India.
Manuscript received on 14 October 2019 | Revised Manuscript received on 28 October 2019 | Manuscript Published on 26 December 2019 | PP: 1165-1173 | Volume-8 Issue-12S October 2019 | Retrieval Number: K131810812S19/2019©BEIESP | DOI: 10.35940/ijitee.K1318.10812S19
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Crop type identification timely and accurately is one of the applications of remote sensing (RS). It assists the people to regulate the variations in the costs of the food grains. RS images are utmost beneficial for agricultural productions. Recent research methodologies focuses mainly on the crops classification using satellite RS image. This paper proffers the survey on crop detection and classification utilizing RS images. This paper also highlights the latest studies regarding the implementation of crop detection and classification techniques like, review on disparate methodologies for crop recognition and classification (different classifiers are used to detect the crop), review on crop conditions monitoring system, and review on identification of yield estimation , crop region, and also crop growth. At last, the performances of the state-of-art methods are contrasted centered on the Kappa coefficient metrics and overall accuracy. Here, accuracy is the notable metric in the crop identification system.
Keywords: RS Images, State-of-Art.
Scope of the Article: Remote Sensing