The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIII-B3-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2021, 617–622, 2021
https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-617-2021
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2021, 617–622, 2021
https://doi.org/10.5194/isprs-archives-XLIII-B3-2021-617-2021

  29 Jun 2021

29 Jun 2021

APPLICATION OF UAV SURVEYS FOR EVALUATING THE PRODUCTIVITY LEVELS OF TRADITIONAL AND MECHANISED FARMERS IN A CUSTOMARY LAND TENURE SYSTEM

D. N. Olayinka1,2, K. L. Omolaye1,3, A. J. Ilesanmi1,4, C. J. Okolie1, and I. D. Arungwa5 D. N. Olayinka et al.
  • 1Department of Surveying and Geoinformatics, Faculty of Engineering, University of Lagos, Lagos State, Nigeria
  • 2Federal School of Surveying, Oyo State, Nigeria
  • 3Geospatial Research Limited, Lagos State, Nigeria
  • 4Office of the State Surveyor-General, Lagos State, Nigeria
  • 5Department of Surveying and Geoinformatics, Faculty of Engineering, Abia State University, Abia State, Nigeria

Keywords: Remote Sensing, Unmanned Aerial Vehicle, Orthomosaic, Customary Land Tenure, Mechanisation, Agriculture, Crop Field Fraction, Crop Yield Index

Abstract. In most of Nigeria’s rural communities, land holdings are small and uneven; and this impacts significantly on their mechanisation potentials. This fragmented nature of the farmlands also inhibits the creation of an effective land market. This study utilised a digital orthomosaic generated from an Unmanned Aerial Vehicle (UAV) survey in evaluating the productivity levels of traditional and mechanised farmers in Okeho Community of Oyo State, South-Western Nigeria. The aerial survey was conducted with a DJI Phantom 4 Professional UAV covering 250 acres of traditional and mechanised farmlands to produce a very high resolution orthomosaic at 6 cm spatial resolution. Sixty-three respondents (61 traditional farmers and 2 mechanised farmers) were also interviewed using questionnaires. Their responses were keyed into a database with the Open Data Kit (ODK) data collector. The orthomosaic was classified into farmland units and a database of the farmers land holdings was created in ArcGIS software. Some parameters influencing their productivity were computed – Crop Field Fraction (CFF) and Crop Yield Index (CYI). The results showed that very few farmers had a shared equity on land (only 3%); most farms were acquired under freehold or lease. Also, only 1% of their farm sizes was larger than 5 acres. There was a sharp disparity in the crop field fraction (traditional farms – 32.2; mechanised farms – 68.8), and the productivity from the mechanised farmers surpasses that of the traditional farmers. It is recommended that the Government should support cluster farming systems among farmers to boost productivity.