基于哨兵数据与特征空间模型的新疆渭库绿洲土壤盐渍化遥感反演

doi:10.12118/j.issn.1000-6060.2025.064

Abstract

Abstract:

Xinjiang requires timely and accurate monitoring of soil salinization dynamics to support effective management and sustainable land use. This study examines the Weigan-Kuqa River Delta Oasis (Weiku Oasis) in Xinjiang. Based on Sentinel-1 synthetic aperture radar imagery and Sentinel-2 optical imagery from July 2022, characteristic parameters that were significantly correlated with measured soil salinity values were extracted and optimized. Six feature space models were constructed, including three polarization combination models from Sentinel-1 ([V²-H]-[H], [V²-H]-[(V²+H²)/V], and [V²-H]-[V-H]) and three spectral index models from Sentinel-2 (CRSI-COSRI, CRSI-NDWI, and CRSI-GARI). Using the optimal model, soil salinity in the study area was inversely estimated, revealing its spatial distribution patterns and enabling precise monitoring of typical salinized areas within the Weigan-Kuqa River Delta Oasis. The results indicate that (1) The Sentinel-2-based CRSI-COSRI model achieved the best inversion performance, with a correlation coefficient (r) of 0.639 and a coefficient of determination (R²) of 0.670, significantly outperforming all other models. (2) The simulated spatial distribution of soil salinization indicated that the overall degree of soil salinization in the study area is relatively high, with an increasing trend from west to east. This study verifies the effectiveness of feature space models in the remote sensing-based inversion of soil salinization in arid regions, providing reliable data support and methodological references for regional salinized soil monitoring and management.

Key words: soil salinization, Sentinel-1 data, Sentinel-2 data, feature space model, Weigan-Kuqa River Delta Oasis

Nigara TASHPOLAT, MA Yingxuan, Abuduwaili REHEMAN, YANG Lei. Remote sensing inversion of soil salinization in the Weiku Oasis of Xinjiang using Sentinel data and a feature space model[J].Arid Land Geography, 2026, 49(2): 287-300.

Figures/Tables 17

Fig. 1

Fig. 2

Tab. 1

Tab. 2

Sentinel-2 spectral indices"

光谱指数	计算公式	参考文献
综合光谱响应指数（COSRI）	$B 2 + B 3 B 4 + B 8 × B 8 - B 4 B 8 + B 4$	[24]
归一化差异植被指数（NDVI）	$B 8 - B 4 B 8 + B 4$	[24]
差值植被指数（DVI）	B₈-B₄	[25]
绿色大气阻抗植被指数（GARI）	$B 8 - [B 3 + 0.9 B 2 - B 4] B 8 + [B 3 + 0.9 B 2 - B 4]$	[26]
盐分比指数（SRI）	(B₄-B₈)×(B₃+B₈)	[26]
强度指数1（Int1）	$B 3 + B 4 2$	[27]
强度指数2（Int2）	$B 3 + B 4 + B 8 2$	[27]
归一化差异水体指数（NDWI）	$B 3 - B 8 B 3 + B 8$	[28]
比值植被指数（RVI）	$B 8 B 4$	[29]
归一化差异盐分指数（NDSI）	$B 4 - B 8 B 4 + B 8$	[30]
盐分指数1（S1）	$B 2 B 4$	[31]
盐分指数2（S2）	$B 2 - B 4 B 2 + B 4$	[31]
盐分指数3（S3）	$B 3 × B 4 B 2$	[31]
盐分指数5（S5）	$B 2 × B 4 B 3$	[31]
盐分指数6（S6）	$B 4 × B 8 a B 3$	[31]
土壤调节植被指数（SAVI）	$(1 + L) (B 8 - B 4) B 8 + B 4 + L$	[31]
盐分指数（SI）	$B 2 × B 4$	[31]
盐分指数1（SI1）	$B 3 × B 4$	[31]
盐分指数2（SI2）	$B 3 2 + B 4 2 + B 8 2$	[31]
盐分指数3（SI3）	$B 3 2 + B 4 2$	[31]
冠层响应盐分指数（CRSI）	$B 8 × B 4 - (B 3 × B 2) B 8 × B 4 + (B 3 × B 2)$	[32]
盐分指数7（SI7）	$B 4 × B 8 B 3$	[32]

Tab. 2

Tab. 3

Tab. 4

Fig. 3

Fig. 4

Fig. 5

Fig. 6

Fig. 7

Fig. 8

Fig. 9

Fig. 10

Tab. 5

Fig. 11

Fig. 12

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极化组合指数	相关系数（r）	极化组合指数	相关系数（r）
V	-0.252^*	H	-0.482^**
V+H	-0.432^**	V-H	0.474^**
V²+H	-0.457^**	V²-H	0.488^**
H²+V	-0.413^**	H²-V	-0.337^**
V²+H²	-0.450^**	V²-H²	0.468^**
(V²+H²)/V	-0.481^**	(V²-H²)/V	0.465^**
(V²+H²)/H	-0.209	(V²-H²)/H	0.462^**
(V-H)/(V+H)	0.439^**	(V²+H²)/(V²-H²)	0.076
H/V	-0.449^**	10lg(V)+10lg(H)	-0.391^**
10lg(V)	-0.227^*	10lg(H)	-0.432^**

影像类别	模型	相关系数（r）	决定系数（R²）
Sentinel-1	[V²-H]-[H]特征空间模型	0.535^**	0.510
	[V²-H]-[(V²+H²)/V]特征空间模型	0.523^**	0.502
	[V²-H]-[V-H]特征空间模型	0.519^**	0.478
Sentinel-2	CRSI-COSRI特征空间模型	0.639^**	0.670
	CRSI-NDWI特征空间模型	0.623^**	0.656
	CRSI-GARI特征空间模型	0.615^**	0.604

Remote sensing inversion of soil salinization in the Weiku Oasis of Xinjiang using Sentinel data and a feature space model

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光谱指数	相关系数（r）	光谱指数	相关系数（r）
COSRI	-0.612^**	S2	0.229^*
CRSI	-0.622^**	S3	0.444^**
DVI	-0.576^**	S5	0.557^**
GARI	-0.605^**	S6	-0.420^**
Int1	0.538^**	SAVI	-0.576^**
Int2	0.341^**	SI	0.554^**
NDSI	0.576^**	SI1	0.539^**
NDVI	-0.576^**	SI2	0.195
NDWI	0.609^**	SI3	0.538^**
RVI	-0.516^**	SI7	-0.420^**
S1	0.224^*	SRI	0.558^**

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