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Area estimating of cotton crop in major districts of Haryana using satellite data

Journal of Entomology and Zoology Studies · 2021 · Vol. 9(2) · pp. 379–384
Vinod VinodPriyankaSonu KumarSurender Kumar

Abstract

Satellite remote sensing based crop monitoring has the advantage of synoptic, spatial and temporal coverage of an area Recent advances on the resolutions (i.e. spectral, spatial, radiometric, and temporal) and availability of remote sensing imagery have allowed us timely collection of information on the growth and development stages of the cotton crop. The aim of this paper was to review the applicability of the remote sensing-based imagery for cotton area mapping in Major Cotton growing districts of Haryana, India. Landsat 8 and images for kharif season 2019 used for analysis. Growing season of Cotton (April to May) coincides with monsoon season. These images were available on (www.usgs.gov) download portal. In ERDAS unsupervised classification was performed using Iterative Self-Organizing Data Analysis Technique (ISODATA) algorithm. Using this algorithm, the analyst input the number of clusters desired and a confidence threshold. In Haryana, cotton crop found concentrated in western parts of state. Fatehabd, Jind and parts of adjoining districts of Rajasthan had vast area under cotton. Landsat data gives good quality interpretation because of high resolution.

Remote Sensing in AgricultureAgricultural Economics and PracticesKharif cropRemote sensingCropMultispectral pattern recognitionSatellite imagerySatelliteEnvironmental scienceMultispectral imageGeographyForestry
Citations
0
FWCI
0.00
field-weighted impact
References
9
Percentile
2%
vs. same field & year
References
Decision tree classification of land cover from remotely sensed data
Remote Sensing of Environment · 1997 · 1,526 citations
International Journal of Remote Sensing
International Journal of Remote Sensing · 2011 · 1,907 citations
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