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Remote Sens. 2016, 8(2), 163; doi:10.3390/rs8020163

Remote Sensing of Soil Alkalinity and Salinity in the Wuyu’er-Shuangyang River Basin, Northeast China

1
Key Laboratory of Remote Sensing Monitoring of Geographic Environment, College of Heilongjiang Province, Harbin Normal University, Harbin, Heilongjiang 150025, China
2
Department of Human Geography and Urban-Rural Planning, Qiqihar University, Qiqihar, Heilongjiang 161006, China
3
Department of Geography, University of South Carolina, Columbia, SC 29208, USA
4
Qiqihar Meteorological Bureau, Qiqihar, Heilongjiang 161006, China
*
Author to whom correspondence should be addressed.
Academic Editors: José A.M. Demattê, Magaly Koch and Prasad S. Thenkabail
Received: 2 December 2015 / Revised: 21 January 2016 / Accepted: 29 January 2016 / Published: 20 February 2016
(This article belongs to the Special Issue Remote Sensing Applied to Soils: From Ground to Space)
View Full-Text   |   Download PDF [2818 KB, uploaded 20 February 2016]   |  

Abstract

The Songnen Plain of the Northeast China is one of the three largest soda saline-alkali regions worldwide. To better understand soil alkalinization and salinization in this important agricultural region, it is vital to explore the distribution and variation of soil alkalinity and salinity in space and time. This study examined soil properties and identified the variables to extract soil alkalinity and salinity via physico-chemical, statistical, spectral, and image analysis. The physico-chemical and statistical results suggested that alkaline soils, coming from the main solute Na2CO3 and NaHCO3 in parent rocks, characterized the study area. The pH and electric conductivity (EC ) were correlated with both narrow band and broad band reflectance. For soil pH, the sensitive bands were in short wavelength (VIS) and the band with the highest correlation was 475 nm (r = 0.84). For soil EC, the sensitive bands were also in VIS and the band with the highest correlation was 354 nm (r = 0.84). With the stepwise regression, it was found that the pH was sensitive to reflectance of OLI band 2 and band 6, while the EC was only sensitive to band 1. The R2Adj (0.73 and 0.72) and root mean square error (RMSE) (0.98 and 1.07 dS/m) indicated that, the two stepwise regression models could estimate soil alkalinity and salinity with a considerable accuracy. Spatial distributions of soil alkalinity and salinity were mapped from the OLI image with the RMSE of 1.01 and 0.64 dS/m, respectively. Soil alkalinity was related to salinity but most soils in the study area were non-saline soils. The area of alkaline soils was 44.46% of the basin. Highly alkaline soils were close to the Zhalong wetland and downstream of rivers, which could become a severe concern for crop productivity in this area. View Full-Text
Keywords: soil alkalinity; soil salinity; spectral signature; Landsat 8 OLI; Songnen Plain soil alkalinity; soil salinity; spectral signature; Landsat 8 OLI; Songnen Plain
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Bai, L.; Wang, C.; Zang, S.; Zhang, Y.; Hao, Q.; Wu, Y. Remote Sensing of Soil Alkalinity and Salinity in the Wuyu’er-Shuangyang River Basin, Northeast China. Remote Sens. 2016, 8, 163.

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