Remote sensing monitoring of salinization in Hetao irrigation district based on SI-MSAVI feature space

doi:10.6046/gtzyyg.2020.01.23

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Abstract

The soil salinization in Hetao irrigation district of Inner Mongolia has exerted severe impact on the sustainable development of local agriculture and economy. Remote sensing can be applied to achieve the real-time information of soil salinization so as to monitor salinization’s future changes. The authors used the satellite images of Landsat to extract salt index (SI) and modified soil mediation vegetation index (MSAVI) and then combined them to construct modified salinization detection index (MSDI) model so as to quantitatively analyze and monitor the soil salinization in this research. After that, the soil salinization information in the study areas obtained in 2001, 2010 and 2017 was further classified and statistically analyzed, which showed an obvious diversity of MSDI mean among various alkali soil types. The result of MSDI was validated by the precision test, field investigation and the salinity of soil samples. The validation demonstrated a strong correlation of 0.856 8 between MSDI and soil salinity, a precision test accuracy of 87.5%, and a Kappa index of 0.726. The soil salinization of this area had been mitigated according to portion changes of non-alkali soil area (from 18.5% to 30.47%) and the fragmented tendency of moderately saline land since 2001. The result indicates that MSDI based on the SI-MSAVI feature space could be applied to quantitatively extract the information of soil salinization and proves to be efficient in monitoring the development of salinization in this region.

Keywords SI-MSAVI feature space image of Landsat Hetao irrigation district salinization MSDI

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Corresponding Authors: Xujiao ZHANG E-mail: zhangxj@cugb.edu.cn

Issue Date: 14 March 2020

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	Jing LU
	Xujiao ZHANG
	Peisheng YE
	Hang WU
	Tao WANG

Cite this article:

Jing LU,Xujiao ZHANG,Peisheng YE, et al. Remote sensing monitoring of salinization in Hetao irrigation district based on SI-MSAVI feature space[J]. Remote Sensing for Land & Resources, 2020, 32(1): 169-175.

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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2020.01.23 OR https://www.gtzyyg.com/EN/Y2020/V32/I1/169

Fig.1 Location of the study area

Fig.2 Extraction of water and sand information

Fig.3 Comparison of SI-MSAVI feature space with different types of saline-alkali land

Fig.4 Remote sensing monitoring model MSDI schematic

Fig.5 Scatter plot of MSDI and soil salinity

Tab.1 Correlation between OLI image spectral index and soil salinity

Tab.2 Accuracy verification of MSDI

Tab.3 Mean value of MSDI for different degrees of saline-alkali land

Fig.6 Classification of saline-alkali land in the study area in 2001, 2010 and 2017

Tab.4 Area and proportion of different saline-alkali land types in the study area in 2001, 2010 and 2017

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