Spatial Information Research

, Volume 26, Issue 4, pp 415–425 | Cite as

Sugarcane ratoon discrimination using LANDSAT NDVI temporal data

  • Sandeep Kumar Singla
  • Rahul Dev Garg
  • Om Prakash Dubey


Pre harvest prediction of sugarcane and sugar production is essential for obtaining the objectives of the national food security mission. Traditional field experimentation results are not reliable and are biased. Improvement in the accuracy and timeliness of crop yield estimation by blending of ancillary data and remotely sensed data in the temporal domain is indispensable. Ratoon sugarcane and planted sugarcane are the two prevalent agricultural practices in India. Ratoon sugarcane crop is suitable both from economic and production consideration. Identification of ratoon sugarcane and monitoring of its growth has been poorly studied. The objective of this study is to extract the information related to the ratoon sugarcane using remote sensing data. The present study proposed NDVIT, an index based on temporal values of NDVI data of Landsat 8 for monitoring and discrimination of ratoon sugarcane. This index has been found to provide 91% accuracy when tested on the ground in the Himalayan foothills region of Uttarakhand. Study indicated that the best period for discrimination of ratoon sugarcane crop is during the first week of April and last week of August to the end of September. This matches with the start of tillering stage and during the period of grand growth stage of the sugarcane.


Remote sensing NDVI NDVIT Discrimination Crop yield estimation Crop growth monitoring Temporal data 


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Copyright information

© Korean Spatial Information Society 2018

Authors and Affiliations

  • Sandeep Kumar Singla
    • 1
  • Rahul Dev Garg
    • 1
  • Om Prakash Dubey
    • 1
  1. 1.Geomatics Engineering Group, Department of Civil EngineeringIndian Institute of Technology Roorkee (IIT)RoorkeeIndia

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