A New Index for Remote Sensing of Soil Organic Carbon Based Solely on Visible Wavelengths

Abstract

Core Ideas A soil carbon remote sensing index was developed using visible wavelengths. The new index performs as well as or better than existing indices. The new index can be applied to any true color image to map soil organic carbon. Remote sensing is a powerful method for mapping soil properties, such as soil organic carbon (SOC), a key property of soil quality. Spectral remote sensing indices that rely on shortwave‐infrared (SWIR) or near‐infrared (NIR) wavelengths have been developed to quantify spatial patterns in SOC. However, the application of SWIR‐ and NIR‐based indices for quantifying fine‐scale patterns of SOC is limited due to the requirement of high‐resolution multispectral or hyperspectral imagery. Visible wavelengths are measured by virtually all sensors, often at high resolution; hence, development of a visible wavelength–based index can greatly increase the ability to remotely estimate SOC. Here we develop such an index by assessing the relationship between laboratory‐measured SOC and spectral reflectance using 7916 SOC and hyperspectral measurements from the nationwide USDA Rapid Carbon Assessment. Our new SOC index (SOCI) predicts SOC concentrations for the 7916 samples with a RMSE of 1.5%, which is comparable to predictions from the SWIR/NIR ratio (RMSE = 1.3%) and outperforms the predictions of an index based on NIR and red wavelengths (RMSE = 2.8%). We applied the index to a high‐resolution satellite image and tested the ability of the image‐based SOCI to predict measured SOC concentrations for a plowed field in Iowa. Regression models with and without local calibration data accurately predict measured SOC, with RMSE values of ∼0.5%. Given the widespread availability of imagery with spectral data in the visible wavelengths, there is potential to use the SOCI to address a range of soil‐agronomic problems.