The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLII-3/W6
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W6, 307–313, 2019
https://doi.org/10.5194/isprs-archives-XLII-3-W6-307-2019
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W6, 307–313, 2019
https://doi.org/10.5194/isprs-archives-XLII-3-W6-307-2019

  26 Jul 2019

26 Jul 2019

SENTINEL 2 AND LANDSAT-8 BANDS SENSITIVITY ANALYSIS FOR MAPPING OF ALKALINE SOIL IN NORTHERN DRY ZONE OF KARNATAKA, INDIA

S. Meti1, Hanumesh2, P. D. Lakshmi2, M. S. Nagaraja3, and V. Shreepad4 S. Meti et al.
  • 1DR Office, University of Horticultural Sciences (UHS), Bagalkot, India
  • 2M.Sc (Hort) students, Department of Soil Science and Agricultural Chemistry, College of Horticulture (COH), Bagalkot, India
  • 3Soil Science, College of Horticulture (COH), Bagalkot, India
  • 4DE Office, University of Horticultural Sciences (UHS), Bagalkot, India

Keywords: Soil salinity, pH, SAR, Landsat 8, Sentinel 2, Dry lands

Abstract. Soil salinization is most common land degradation process occurring in deep vertisol of northern dry zone of Karnataka, India. Accurate and high resolution spatial information on salinization can assist policy makers to better target areas for interventions to avoid aggravation of soil degradation process. Digital soil mapping using satellite data has been identified as a potential means of obtaining soil information. This paper focuses on exploring possibility of using new generation medium resolution Landsat-8 and Sentinel-2 satellite data to map alkaline soils of Ramthal irrigation project area in north Karnataka. Surface soil salinity parameters of zone 20 were correlated with reflectance values of different band and band combination and traditional salinity indices and result has indicated that SWIR bands of both satellite showed significant negative correlation with soil pH, EC (r = −0.39 to −0.45) whereas visible and NIR bands did not show significant relation. However rationing of SWIR bands with visible blue band has significantly improved the correlation with soil pH and EC (r = +0.60 to +0.70). Traditional salinity index based on visible bands failed to show significant correlation with soil parameters. It is interesting to note that SWIR bands alone did not show significant correlation with soil sodicity parameters like exchangeable Na, SAR, RSC but band rationing with blue bands has significantly improved the correlation (r = 0.45). High resolution soil salinity map was prepared using simple linear regression model and using this map will serve as base map for the policy makers.