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ARS Home » Southeast Area » Tifton, Georgia » Southeast Watershed Research » Research » Publications at this Location » Publication #180068
Title: USING REMOTE SENSING DATA TO EVALUATE SURFACE SOIL PROPERTIES IN ALABAMA ULTISOLS

Author
item Sullivan, Dana
item SHAW, J - AUBURN UNIV
item RICKMAN, D - NASA MFSC
item MASK, P - ALABAMA COOP.EXT.SERV.
item LUVALL, J - NASA MFSC

Submitted to: Soil Science Society of America Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/5/2005
Publication Date: 10/26/2005
Citation: Sullivan, D.G., Shaw, J.N., Rickman, D., Mask, P., Luvall, J. 2005. Using remote sensing data to evaluate surface soil properties in alabama ultisols. Soil Science Society of America Journal. 170:954-968.

Interpretive Summary: Remotely sensed imagery offers an aerial view of near-surface soil features and may be used to streamline landscape scale assessments of soil properties. Soil spectral signatures may be used to delineate management zones for agrochemical applications and soil sampling, as well as guide soil mapping efforts and natural resource inventory. The primary objective of this study was to evaluate an airborne multispectral sensor as a new tool for depicting differences in near-surface soil attributes. Study sites were located in four different physiographic regions within the state of Alabama in an attempt to encompass the inherent variability in soil features. Remotely sensed imagery was acquired in May 2000 via the Airborne Terrestrial Applications Sensor (ATLAS) multispectral scanner, which collects data in 15 bands throughout the visible, near-infrared, and thermal infrared regions of the spectrum. Along with image acquisitions, near-surface soil samples (0-1 cm) from bare fields were collected from 163 sampling points for soil water content, soil organic carbon (SOC), particle size distribution (PSD), and citrate dithionite extractable iron (Fed) content. Results showed that thermal infrared imagery was most useful in differentiating among small changes in surface soil texture. Thermal infrared were also highly correlated with SOC contents, however, typically low levels of SOC contents were difficult to measure at the landscape scale. Estimates iron oxide contents were a function of mineralogy and best accomplished using specific regions of the visible and middle infrared spectrum.

Technical Abstract: Evaluation of surface soil properties via remote sensing (RS) could facilitate soil survey mapping, erosion prediction and allocation of agrochemicals for precision management. The objective of this study was to evaluate the relationship between soil spectral signature and surface soil properties in conventionally managed row crop systems. High-resolution RS data were acquired over bare fields in the Coastal Plain, Appalachian Plateau, and Ridge and Valley provinces of Alabama using the Airborne Terrestrial Applications Sensor (ATLAS) multispectral scanner. Soils ranged from sandy Kandiudults to fine textured Rhodudults. Surface soil samples (0-1 cm) were collected from 163 sampling points for soil organic carbon (SOC), particle size distribution (PSD), and citrate dithionite extractable iron (Fed) content. Surface roughness, soil water content, and crusting were also measured during sampling. Two methods of analysis were evaluated: 1) multiple linear regression using common spectral band ratios, and 2) partial least squares regression (PLS). Our data show that thermal infrared spectra are highly, linearly related to SOC, sand and clay content. Soil organic carbon content was the most difficult to quantify in these highly weathered systems, where SOC was generally < 1.2 %. Estimates of sand and clay content were best using PLS at the Valley site, explaining 42 –59 % of the variability. In the Coastal Plain, sandy surfaces prone to crusting limited estimates of sand and clay content via PLS and regression with common band ratios. Estimates of Fed were a function of mineralogy and best accomplished using specific band ratios, explaining 36-65 % of the variability at the Valley and Coastal Plain sites, respectively.