干旱区生态环境知识资源中心(Arid): Soil salinity inversion based on novel spectral index

Arid

DOI	10.1007/s12665-021-09752-x
	Soil salinity inversion based on novel spectral index
	Zhou, Xiaohong; Zhang, Fei; Liu, Changjiang; Kung, Hsiang-te; Johnson, Verner Carl
通讯作者	Zhou, XH ; Zhang, F (corresponding author), Xinjiang Univ, Coll Resources & Environm Sci, Key Lab Smart City & Environm Modeling Higher Edu, Urumqi 830046, Peoples R China. ; Zhou, XH ; Zhang, F (corresponding author), Xinjiang Univ, Key Lab Oasis Ecol, Urumqi 830046, Peoples R China. ; Zhang, F (corresponding author), Natl Adm Surveying Mapping & Geoinformat, Engn Res Ctr Cent Asia Geoinformat Dev & Utilizat, Urumqi 830002, Peoples R China.
来源期刊	ENVIRONMENTAL EARTH SCIENCES
ISSN	1866-6280
EISSN	1866-6299
出版年	2021
卷号	80 期号:16
英文摘要	Soil salinization is one of the most important causes for land degradation and desertification and is an important threat to land management, farming activities, water quality, and sustainable development, with the management of saline soil crucial in arid and semi-arid areas. The salt-affected soil is predominant in the Ebinur Lake Wetland National Nature Reserve (ELWNNR) in the Northwestern China. It influences the development of agricultural economy. Rapid and accurate measurement of the soil salt content (SSC) is significant for the soil salinization control. However, the traditional method of obtaining soil salt is time-consuming and laborious. Nowadays, it is an unprecedented perspective to monitor soil salinity through Sentinel-2A multispectral remote sensing image to construct three-dimensional spectral index. In this study, through soil salt data of 97 ground-truth measurements, Sentinel-2A data-derived spectral indices, based on particle swarm optimization support vector machine (PSO-SVM), gray wolf optimization support vector machine (GWO-SVM) and differential evolution support vector machine (DE-SVM) algorithm to construct a best soil salt inversion models. The results show that three-band (3D) spectral index has better correlation with soil salinity than single band and two-band (2D) spectral index, among TBI5 and TBI7 has a high correlation with the salinity of the soil, and the points are concentrated on the 1:1 line. Therefore, this approach could be applied to estimate the soil salinity in the Ebinur Lake region. The established models were validated using the Machine learning algorithm. The DE-SVM model performed the best by the three Model of accuracy with R-2, Bias, and SEPC2 of 0.56, - 2.03, and 8.62, respectively. Therefore through the soil salinity value predicted by the modeling constructs a linear relationship with the indexes TBI5 and TBI7, and draw the soil salt inversion map, soil salinity around the lake is relatively high, and decreases outward along the lake, which is consistent with the field. The result from this model will be useful for soil salinization monitoring in the study area and can provide theoretical support for the estimation of SSC in arid and semi-arid areas.
英文关键词	Machine learning algorithm Sentinel-2A Spectral indices
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000681312900002
WOS关键词	DIFFERENTIAL EVOLUTION ALGORITHM ; PARTICLE SWARM OPTIMIZATION ; ORGANIC-MATTER CONTENT ; NATURE-RESERVE ELWNNR ; EBINUR LAKE ; REMOTE ESTIMATION ; SPECTROSCOPY ; PREDICTION ; CHINA ; MODEL
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary ; Water Resources
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Water Resources
来源机构	新疆大学
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/363104
作者单位	[Zhou, Xiaohong; Zhang, Fei; Liu, Changjiang] Xinjiang Univ, Coll Resources & Environm Sci, Key Lab Smart City & Environm Modeling Higher Edu, Urumqi 830046, Peoples R China; [Zhou, Xiaohong; Zhang, Fei; Liu, Changjiang] Xinjiang Univ, Key Lab Oasis Ecol, Urumqi 830046, Peoples R China; [Zhang, Fei] Natl Adm Surveying Mapping & Geoinformat, Engn Res Ctr Cent Asia Geoinformat Dev & Utilizat, Urumqi 830002, Peoples R China; [Kung, Hsiang-te] Univ Memphis, Dept Earth Sci, Memphis, TN 38152 USA; [Johnson, Verner Carl] Colorado Mesa Univ, Dept Phys & Environm Sci, Grand Junction, CO 81501 USA
推荐引用方式 GB/T 7714	Zhou, Xiaohong,Zhang, Fei,Liu, Changjiang,et al. Soil salinity inversion based on novel spectral index[J]. 新疆大学,2021,80(16).
APA	Zhou, Xiaohong,Zhang, Fei,Liu, Changjiang,Kung, Hsiang-te,&Johnson, Verner Carl.(2021).Soil salinity inversion based on novel spectral index.ENVIRONMENTAL EARTH SCIENCES,80(16).
MLA	Zhou, Xiaohong,et al."Soil salinity inversion based on novel spectral index".ENVIRONMENTAL EARTH SCIENCES 80.16(2021).