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Estimating Soil Organic Carbon in Central Iowa Using Aerial Imagery and Soil Surveys
Author(s) -
Gelder B. K.,
Anex R. P.,
Kaspar T. C.,
Sauer T. J.,
Karlen D. L.
Publication year - 2011
Publication title -
soil science society of america journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.836
H-Index - 168
eISSN - 1435-0661
pISSN - 0361-5995
DOI - 10.2136/sssaj2010.0260
Subject(s) - environmental science , soil carbon , soil survey , soil water , sampling (signal processing) , digital soil mapping , soil science , soil map , soil test , total organic carbon , remote sensing , hydrology (agriculture) , geography , geology , computer science , environmental chemistry , chemistry , geotechnical engineering , filter (signal processing) , computer vision
Widespread implementation of precision agriculture practices requires low‐cost, high‐quality data such as soil organic C (SOC) content, but SOC mapping currently requires expensive sample collection and analysis techniques. Soils higher in organic C appear darker than surrounding soils in aerial imagery after tillage, although this difference is only relative without knowledge of the range of SOC. This range could be estimated from Soil Survey Geographic (SSURGO) database. To verify this, the SSURGO database was used to estimate the SOC range at three sites in central Iowa. Soil organic C content across each field was then linearly interpolated within the SSURGO‐estimated range for each field using the brightness values at each pixel in the aerial photograph as a scaling factor. Measured SOC data from the three sites ranged from 3.4 to 50 g kg −1 and the R 2 and RMSE values between the measured and estimated SOC concentrations ranged from 0.60 to 0.82 and 3.5 to 7.6 g kg −1 , respectively. Limited thresholding of the brightest and darkest pixels improved the accuracy and precision of SOC estimates over raw imagery. These results imply that aerial imagery supplemented by SSURGO‐estimated SOC ranges can provide georeferenced SOC estimates suitable for site‐specific recommendations and analysis without field sampling.