干旱区生态环境知识资源中心(Arid): Upscaling remote sensing inversion and dynamic monitoring of soil salinization in the Yellow River Delta, China

Arid

DOI	10.1016/j.ecolind.2023.110087
	Upscaling remote sensing inversion and dynamic monitoring of soil salinization in the Yellow River Delta, China
	Li, Yinshuai; Chang, Chunyan; Wang, Zhuoran; Zhao, Gengxing
通讯作者	Chang, CY ; Zhao, GX
来源期刊	ECOLOGICAL INDICATORS
ISSN	1470-160X
EISSN	1872-7034
出版年	2023
卷号	148
英文摘要	As a global problem of soil degradation, salinization has become a major obstacle to the sustainable development of the ecological environment and agriculture in coastal plains. However, the traditional process of salinity survey is too cumbersome, expensive and time-consuming to meet the mapping needs in a large scale. Remote sensing technology has become an important tool for digital soil mapping because of its rich sources, real-time and low cost. In order to meet the objective demand for rapid, accurate, and efficient acquisition and monitoring of soil salinization. This paper collected 61 soil samples from the Kenli District (experimental area) and extracted vegetation and salinity indicators from the Landsat image to construct the salinity inversion model by random forest algorithm. Then, taking the Yellow River Delta as the study area, the conversion coefficient of spectral indicators between Landsat and MODIS images was constructed in the form of the ratio of the mean value. Through optimization, the upscaling conversion method based on land use regionalization was proposed to realize the upscaling inversion and dynamic monitoring of soil salinization. The results showed that: (1) The random forest model based on NDVI, RVI, EVI, SI3, and SI5 can better predict the soil salinity in the experimental area, with R2 = 0.821 and RMSE = 2.811 (validation accuracy). (2) The upscaling conversion method based on land use regionalization can effectively reduce the statistical error and collinearity of spectral indicators con-structed by MODIS images and improve their correlation with OLI data and soil salinity. (3) From coastal to inland, soil salinization gradually decreases in the Yellow River Delta. From 2000 to 2020, soil salinization increased first and then decreased, and the salinized soil accounted for 20.35%similar to 35.10%. This study used multi-source remote sensing data to realize the collaborative inversion at different scales, which was significant for the quantitative estimation of soil salinity, salinization control, and sustainable agricultural development in coastal plains.
英文关键词	Soil salinization Remote sensing inversion Spectral indicator Upscaling conversion Yellow River Delta China
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:000953223600001
WOS关键词	MODIS TIME-SERIES ; SALINITY ; IMAGES ; LAND ; MESOPOTAMIA ; XINJIANG ; PROVINCE ; MACHINE ; IMPACT ; OASIS
WOS类目	Biodiversity Conservation ; Environmental Sciences
WOS研究方向	Biodiversity & Conservation ; Environmental Sciences & Ecology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/395927
推荐引用方式 GB/T 7714	Li, Yinshuai,Chang, Chunyan,Wang, Zhuoran,et al. Upscaling remote sensing inversion and dynamic monitoring of soil salinization in the Yellow River Delta, China[J],2023,148.
APA	Li, Yinshuai,Chang, Chunyan,Wang, Zhuoran,&Zhao, Gengxing.(2023).Upscaling remote sensing inversion and dynamic monitoring of soil salinization in the Yellow River Delta, China.ECOLOGICAL INDICATORS,148.
MLA	Li, Yinshuai,et al."Upscaling remote sensing inversion and dynamic monitoring of soil salinization in the Yellow River Delta, China".ECOLOGICAL INDICATORS 148(2023).