Proximal Sensing in Grasslands and Pastures

Shayan Ghajar and Benjamin Tracy
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Shayan Ghajar: School of Plant and Environmental Sciences, Virginia Tech, Blacksburg, VA 24061, USA
Benjamin Tracy: School of Plant and Environmental Sciences, Virginia Tech, Blacksburg, VA 24061, USA

Agriculture, 2021, vol. 11, issue 8, 1-12

Abstract: Reliable measures of biomass, species composition, nitrogen status, and nutritive value provide important indicators of the status of pastures and rangelands, allowing managers to make informed decisions. Traditional methods of sample collection necessitate significant investments in time and labor. Proximal sensing technologies have the potential to collect more data with a smaller investment in time and labor. However, methods and protocols for conducting pasture assessments with proximal sensors are still in development, equipment and software vary considerably, and the accuracy and utility of these assessments differ between methods and sites. This review summarizes the methods currently being developed to assess pastures and rangelands worldwide and discusses these emerging technologies in the context of diffusion of innovation theory.

Keywords: proximal; sensing; LiDAR; photogrammetry; grasslands; pastures (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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