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Measuring Soil Colour to Estimate Soil Organic Carbon Using a Large-Scale Citizen Science-Based Approach
Rapid, low-cost methods for large-scale assessments of soil organic carbon (SOC) are essential for climate change mitigation. Our work explores the potential for citizen scientists to gather soil colour data as a cost-effective proxy of SOC instead of conventional lab analyses. The research took place during a 2-year period using topsoil data gathered by citizen scientists and scientists from urban parks in the UK and France. We evaluated the accuracy and consistency of colour identification by comparing “observed” Munsell soil colour estimates to “measured” colour derived from reflectance spectroscopy, and calibrated colour observations to ensure data robustness. Statistical relationships between carbon content obtained by loss on ignition (LOI) and (i) observed and (ii) measured soil colour were derived for SOC prediction using three colour components: hue, lightness, and chroma. Results demonstrate that although the spectrophotometer offers higher precision, there was a correlation between observed and measured colour for both scientists (R2 = 0.42; R2 = 0.26) and citizen scientists (R2 = 0.39; R2 = 0.19) for lightness and chroma, respectively. Foremost, a slightly stronger relationship was found for predicted SOC using the spectrophotometer (R2 = 0.69), and citizen scientists produced comparable results (R2 = 0.58), highlighting the potential of a large-scale citizen-based approach for SOC monitoring.
Measuring Soil Colour to Estimate Soil Organic Carbon Using a Large-Scale Citizen Science-Based Approach
Rapid, low-cost methods for large-scale assessments of soil organic carbon (SOC) are essential for climate change mitigation. Our work explores the potential for citizen scientists to gather soil colour data as a cost-effective proxy of SOC instead of conventional lab analyses. The research took place during a 2-year period using topsoil data gathered by citizen scientists and scientists from urban parks in the UK and France. We evaluated the accuracy and consistency of colour identification by comparing “observed” Munsell soil colour estimates to “measured” colour derived from reflectance spectroscopy, and calibrated colour observations to ensure data robustness. Statistical relationships between carbon content obtained by loss on ignition (LOI) and (i) observed and (ii) measured soil colour were derived for SOC prediction using three colour components: hue, lightness, and chroma. Results demonstrate that although the spectrophotometer offers higher precision, there was a correlation between observed and measured colour for both scientists (R2 = 0.42; R2 = 0.26) and citizen scientists (R2 = 0.39; R2 = 0.19) for lightness and chroma, respectively. Foremost, a slightly stronger relationship was found for predicted SOC using the spectrophotometer (R2 = 0.69), and citizen scientists produced comparable results (R2 = 0.58), highlighting the potential of a large-scale citizen-based approach for SOC monitoring.
Measuring Soil Colour to Estimate Soil Organic Carbon Using a Large-Scale Citizen Science-Based Approach
Nerea Ferrando Jorge (author) / Joanna Clark (author) / Macarena L. Cárdenas (author) / Hilary Geoghegan (author) / Vicky Shannon (author)
2021
Article (Journal)
Electronic Resource
Unknown
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