干旱区生态环境知识资源中心(Arid): Soil Moisture and Salinity Inversion Based on New Remote Sensing Index and Neural Network at a Salina-Alkaline Wetland

Arid

DOI	10.3390/w13192762
	Soil Moisture and Salinity Inversion Based on New Remote Sensing Index and Neural Network at a Salina-Alkaline Wetland
	Wang, Jie; Wang, Weikun; Hu, Yuehong; Tian, Songni; Liu, Dongwei
通讯作者	Liu, DW (corresponding author), Inner Mongolia Univ, Sch Ecol & Environm, Hohhot 010021, Peoples R China. ; Liu, DW (corresponding author), Inner Mongolia Key Lab River & Lake Ecol, Hohhot 010021, Peoples R China.
来源期刊	WATER
EISSN	2073-4441
出版年	2021
卷号	13 期号:19
英文摘要	In arid and semi-arid regions, soil moisture and salinity are important elements to control regional ecology and climate, vegetation growth and land function. Soil moisture and salt content are more important in arid wetlands. The Ebinur Lake wetland is an important part of the ecological barrier of Junggar Basin in Xinjiang, China. The Ebinur Lake Basin is a representative area of the arid climate and ecological degradation in central Asia. It is of great significance to study the spatial distribution of soil moisture and salinity and its causes for land and wetland ecological restoration in the Ebinur Lake Basin. Based on the field measurement and Landsat 8 satellite data, a variety of remote sensing indexes related to soil moisture and salinity were tested and compared, and the prediction models of soil moisture and salinity were established, and the accuracy of the models was assessed. Among them, the salinity indexes D1 and D2 were the latest ones that we proposed according to the research area and data. The distribution maps of soil moisture and salinity in the Ebinur Lake Basin were retrieved from remote sensing data, and the correlation analysis between soil moisture and salinity was performed. Among several soil moisture and salinity prediction indexes, the normalized moisture index NDWI had the highest correlation with soil moisture, and the salinity index D2 had the highest correlation with soil salinity, reaching 0.600 and 0.637, respectively. The accuracy of the BP neural network model for estimating soil salinity was higher than the one of other models; R-2 = 0.624, RMSE = 0.083 S/m. The effect of the cubic function prediction model for estimating soil moisture was also higher than that of the BP neural network, support vector machine and other models; R-2 = 0.538, RMSE = 0.230. The regularity of soil moisture and salinity changes seemed to be consistent, the correlation degree was 0.817, and the synchronous change degree was higher. The soil salinity in the Ebinur Lake Basin was generally low in the surrounding area, high in the middle area, high in the lake area and low in the vegetation coverage area. The soil moisture in the Ebinur Lake Basin slightly decreased outward with the Ebinur Lake as the center and was higher in the west and lower in the east. However, the spatial distribution of soil moisture had a higher mutation rate and stronger heterogeneity than that of soil salinity.
英文关键词	soil moisture and salinity multispectral remote sensing BP neural network salina-alkaline wetland Ebinur Lake Basin
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:000709538100001
WOS关键词	PERPENDICULAR DROUGHT INDEX ; VEGETATION ; CHINA ; LAKE ; STRESS ; SALT ; SALINIZATION ; MODEL ; AREA
WOS类目	Environmental Sciences ; Water Resources
WOS研究方向	Environmental Sciences & Ecology ; Water Resources
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/364849
作者单位	[Wang, Jie; Wang, Weikun; Hu, Yuehong; Tian, Songni; Liu, Dongwei] Inner Mongolia Univ, Sch Ecol & Environm, Hohhot 010021, Peoples R China; [Liu, Dongwei] Inner Mongolia Key Lab River & Lake Ecol, Hohhot 010021, Peoples R China
推荐引用方式 GB/T 7714	Wang, Jie,Wang, Weikun,Hu, Yuehong,et al. Soil Moisture and Salinity Inversion Based on New Remote Sensing Index and Neural Network at a Salina-Alkaline Wetland[J],2021,13(19).
APA	Wang, Jie,Wang, Weikun,Hu, Yuehong,Tian, Songni,&Liu, Dongwei.(2021).Soil Moisture and Salinity Inversion Based on New Remote Sensing Index and Neural Network at a Salina-Alkaline Wetland.WATER,13(19).
MLA	Wang, Jie,et al."Soil Moisture and Salinity Inversion Based on New Remote Sensing Index and Neural Network at a Salina-Alkaline Wetland".WATER 13.19(2021).