Infrared Sensors to Map Soil Carbon in Agricultural Ecosystems

Abstract

Rapid methods of measuring soil carbon – such as near-infrared (NIR) and mid-infrared (MIR) diffuse reflectance spectroscopy – have gained interest, but problems of accurate and precise measurement still persist as a result of the high spatial variability of soil carbon within agricultural landscapes. Tillage-based (meaning tine-mounted) and airborne-based spectral sensors offer the opportunity to effectively capture the spatial distribution of soil carbon within agricultural landscapes. We evaluated an airborne hyperspectral sensor covering the range 450–2,450 nm at 2.5 m spatial resolution and a tillage sensor covering the range 920–2,225 nm. We intensively sampled soils within five tilled agricultural fields within the flight path of the airborne sensor. The test fields were located on the Delmarva Peninsula in Maryland, USA. The quality of spectral data acquired by these field-based sensors was compared to laboratory-acquired spectral data in both NIR (1,000–2,500 nm) and MIR (2,500–25,000 nm) spectral regions for the soil samples taken at 304 geo-referenced locations within the fields. Partial least squares regression (PLSR) models developed from the three NIR spectral data sources were very comparable, indicating that the two field-based NIR sensors performed well for generating spatial data. Although the laboratory-based MIR calibration was found to be substantially better than the laboratory-derived NIR calibration, current instrumentation limitations favour the use of NIR for in-field measurements. A 2.5 m resolution soil carbon map was produced for an agricultural field using the airborne hyperspectral image and the PLS calibration. This new approach for mapping soil carbon will permit better assessment of soil carbon sequestration in agricultural ecosystems at the landscape scale. Such data can be used to improve the landscape models which account for biogeochemical and soil redistribution processes that occur within often complex topographic and management settings.