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Land Use Land Cover Classification And Wheat Yield Prediction In The Lower Chenab Canal System Using Remote Sensing And Gis

Author

Listed:
  • Aftab Nazeer

    (Department of Agricultural Engineering, BZU, Multan, Pakistan)

  • Muhammad Mohsin Waqas

    (Department of Irrigation and Drainage, University of Agriculture, Faisalabad, Pakistan)

  • Sikandar Ali

    (Department of Irrigation and Drainage, University of Agriculture, Faisalabad, Pakistan)

  • Usman Khalid Awan

    (International Center for Agricultural Research in the Dry Areas, Egypt)

  • MuhammadJehanzeb Masud Cheema

    (Department of Irrigation and Drainage, University of Agriculture, Faisalabad, Pakistan)

  • Allah Baksh

    (Department of Irrigation and Drainage, University of Agriculture, Faisalabad, Pakistan)

Abstract

Reliable and timely information regarding area under wheat and its yield prediction can help in better management of the commodity. The remotely sensed data especially in combination with Geographic Information System (GIS) can provide an important and powerful tool for both, land use land cover (LULC) classification and crop yield prediction. The study objectives include LULC classification and wheat yield prediction. The study was conducted for Rabi Season from Nov. 2011 to April 2012, in the command area of three distributaries i.e. Khurrian Wala, Killian Wala and Mungi of Lower Chennai Canal (LCC) system. The Landsat-7 imagery data with spatial resolution of 30 m was used for this study. Physical features were monitored and assessed using Normalized Difference Vegetative Index (NDVI). LULC classification was done for wheat and non-wheat area which shows wheat proportion and area 87.22% and 28867.95 Ha in Khurrian wala, 71.07% and 22423.20 Ha in Killian Wala and 79.18% and 17974.34 Ha in Mungi distributary, respectively. The correlation values between maximum NDVI value and yield data were 0.45, 0.36 and 0.39 for Khurrian Wala, Killian Wala and Mungi distributary, respectively. On the basis of this correlation, average wheat yield was estimated as 3.48 T/Ha, 3.83 T/Ha and 3.80 T/Ha for Khurrian Wala, Killian Wala and Mungi distributary, respectively.

Suggested Citation

  • Aftab Nazeer & Muhammad Mohsin Waqas & Sikandar Ali & Usman Khalid Awan & MuhammadJehanzeb Masud Cheema & Allah Baksh, 2020. "Land Use Land Cover Classification And Wheat Yield Prediction In The Lower Chenab Canal System Using Remote Sensing And Gis," Big Data In Agriculture (BDA), Zibeline International Publishing, vol. 2(2), pages 47-51, March.
    • Handle: RePEc:zib:zbnbda:v:2:y:2020:i:2:p:47-51
    DOI: 10.26480/bda.02.2020.47.51
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    References listed on IDEAS

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    1. Cheema, M.J.M. & Bastiaanssen, W.G.M., 2010. "Land use and land cover classification in the irrigated Indus Basin using growth phenology information from satellite data to support water management analysis," Agricultural Water Management, Elsevier, vol. 97(10), pages 1541-1552, October.
    2. Cheema, Muhammad Jehanzeb Masud & Bakhsh, Allah & Mahmood, Talha & Liaqat, Muhammad Usman, 2016. "Assessment of water allocations using remote sensing and GIS modeling for Indus Basin, Pakistan:," PSSP working papers 36, International Food Policy Research Institute (IFPRI).
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