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Development of Decision Support Framework for Soil Conservation and Profitability Mapping using Drone Imagery
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  • Syed Hamid Hussain Shah,
  • Evan McDonald,
  • Salem Al- Naemi,
  • Aitazaz A. Farooque,
  • Saad Javed Cheema,
  • Hassan Afzaal,
  • Woon Kok Sin,
  • Mumtaz Ali
Syed Hamid Hussain Shah
University of Prince Edward Island

Corresponding Author:[email protected]

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Evan McDonald
University of Prince Edward Island
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Salem Al- Naemi
University of Doha for Science & Technology
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Aitazaz A. Farooque
University of Prince Edward Island
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Saad Javed Cheema
University of Prince Edward Island
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Hassan Afzaal
University of Prince Edward Island Faculty of Sustainable Design Engineering
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Woon Kok Sin
Xiamen University - Malaysia
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Mumtaz Ali
University of Southern Queensland
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Abstract

Soil erosion causes fluctuations in potato ( Solanum tuberosum L) yield, deteriorates soil health, lowers profit margins for growers, and creates adverse environmental impacts. This study focuses on developing a decision support system to improve soil health, increase profitability for growers, and lower environmental risks. Two fields are selected for this research in Prince Edward Island, Canada, during 2020-2021. Thermal and topography surveys are conducted to delineate fertility-based management zones (MZs) for soil sampling of organic matter, potato yield, and sensor data collection. Soil temperature are calibrated and validated before the growing season using handheld gun and drone-based thermal imagery. Data analysis from drone imagery reflects the coincided patterns of thermal and multispectral imagery with crop yield, topographical features, and soil water and topography (SWAT) maps. Higher temperature zones lead to excessive soil erosion that reduces soil surface nutrients, lower NDVI values, and show visual variation in bare soil imagery. Moreover, it is found that low thermal zones produce higher yields as compared to the high thermal zones. As such, the slope has a direct impact on the retention of soil moisture content; the low productivity zones retain the least soil moisture content (13.5%), followed by medium (16.1%) and high productivity zones (18.4%). This proposed decision support system can be a useful tool for mapping soil erosion and crop profitability. The data generated from these tools can be a crucial input for improved quantification of sediment transport in watershed scale models.