93-7 Soil Salinity Mapping Using Landsat 8 Images in Northern Great Plains Sodium Affected Soil.

See more from this Division: ASA Section: Agronomic Production Systems
See more from this Session: Digital Soil Mapping for Precision Agriculture: I

Monday, November 16, 2015: 2:50 PM
Minneapolis Convention Center, 102 F

Tulsi Prasad Kharel1, David E. Clay2, Rachel K. Owen3, Thomas M. DeSutter4, Douglas D. Malo5, C. Gregg Carlson5 and Cheryl L. Reese6, (1)New York (NY), Cornell University, Ithaca, NY
(2)South Dakota State University, Brookings, SD
(3)University of Missouri, Columbia, MO
(4)North Dakota State University, North Dakota State University, Fargo, ND
(5)Plant Science Department, South Dakota State University, Brookings, SD
(6)Department of Agronomy, Horticulture and Plant Science, South Dakota State University, Brookings, SD
Abstract:
In the northern Great Plains, drainage of saline/sodic soils (Natrustolls, Natraquolls, and associated Argiustolls) can result in soil dispersion. Our bojective is to map soil salinity (Electrical Conductivity, EC and Sodium Absorption Ratio, SAR) using Landsat 8 images. For this study, 62m x 62m regular grid soil samples were collected from Pierpont site on November, 2013.  Soil samples from this 160 acre field were analyzed for saturated paste EC (dS/m) and SAR. Landsat-8 images (2013, 2014 and 2015) were downloaded and clipped for the study site. Surface reflectance (band 1-7) from operational land imager (OLI) and top of atmosphere radiance (band 10 and 11) from thermal infrared sensor (TIRS) were used to predict soil EC.  Results shows Random Forest method was effective to model spatially correlated soil EC using principal components of OLI and TIRS bands.

See more from this Division: ASA Section: Agronomic Production Systems
See more from this Session: Digital Soil Mapping for Precision Agriculture: I