干旱区生态环境知识资源中心(Arid): Improving Estimates of Soil Salt Content by Using Two-Date Image Spectral Changes in Yinbei, China

Arid

DOI	10.3390/rs13204165
	Improving Estimates of Soil Salt Content by Using Two-Date Image Spectral Changes in Yinbei, China
	Xu, Xibo; Chen, Yunhao; Wang, Mingguo; Wang, Sijia; Li, Kangning; Li, Yongguang
通讯作者	Chen, YH (corresponding author), Beijing Normal Univ, Fac Geog Sci, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China. ; Chen, YH (corresponding author), Beijing Normal Univ, Fac Geog Sci, Beijing Key Lab Environm Remote Sensing & Digital, Beijing 100875, Peoples R China.
来源期刊	REMOTE SENSING
EISSN	2072-4292
出版年	2021
卷号	13 期号:20
英文摘要	Soil salt content (SSC) is normally featured with obvious spatiotemporal variations in arid and semi-arid regions. Space factors such as elevation, temperature, and spatial locations are usually used as input variables for a model to estimate the SSC. However, whether temporal patterns of salt-affected soils (identified as temporal spectral patterns) can indicate the SSC level and be applied as a covariate in a model to estimate the SSC remains unclear. Hence, temporal changes in soil spectral patterns need to be characterized and explored as to their use as an input variable to improve SSC estimates. In this study, a total of 54 field samples and a time-series of Sentinel-2 multispectral images taken at monthly intervals (from October 2017 to April 2018) were collected in the Yinbei area of western China. Then, two-date satellite images were used to quantify significant spectral changes over time using spectral change vector analysis, and four two-date-based index methods were used to characterize soil spectral changes. Lastly, the optimal two-date-based spectral indices and multispectral bands were used as input variables to build the estimation models using a random forest algorithm. Results showed that the two-date-based spectral index could be applied as an input variable to improve the accuracy of SSC estimation at a regional scale. Temporal changes in salt-induced spectral patterns can be indicated by the band difference in the wavelength range from 400 nm to 900 nm. Three two-date-based indices designated as D-28a (i.e., the band difference between band 2 from an image acquired in April 2018 and band 8a from an image acquired in December 2017), D-22, and D-28 were the optimal parameters for characterizing salt-induced spectral changes, which were dominated by the total brightness, chloride, and sulfate accumulation of the soils. The model did not yield satisfactory estimation results (RPD = 1.49) when multispectral bands were used as the input variables. Multispectral bands coupled with two two-date-based indices (D-22 and D-28a) used as the input variables produced the best estimation result (R-2 = 0.92, RPD = 3.27). Incorporating multispectral bands and two-date-based indices into the random forest model provides a remotely-sensed strategy that effectively supports the monitoring of soil salt content.
英文关键词	soil salt content temporal spectral pattern improved estimation satellite imagery
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:000713820100001
WOS关键词	ORGANIC-CARBON ; SENTINEL-2 MSI ; SALINITY ; LAKE ; PREDICTION ; XINJIANG ; REGION ; OLI ; DRY
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
来源机构	北京师范大学
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/368337
作者单位	[Xu, Xibo; Chen, Yunhao; Wang, Sijia; Li, Kangning; Li, Yongguang] Beijing Normal Univ, Fac Geog Sci, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China; [Xu, Xibo; Chen, Yunhao; Wang, Sijia; Li, Kangning] Beijing Normal Univ, Fac Geog Sci, Beijing Key Lab Environm Remote Sensing & Digital, Beijing 100875, Peoples R China; [Wang, Mingguo] NingXia Agr Technol Extens Serv Ctr, Yinchuan 750001, Ningxia, Peoples R China
推荐引用方式 GB/T 7714	Xu, Xibo,Chen, Yunhao,Wang, Mingguo,et al. Improving Estimates of Soil Salt Content by Using Two-Date Image Spectral Changes in Yinbei, China[J]. 北京师范大学,2021,13(20).
APA	Xu, Xibo,Chen, Yunhao,Wang, Mingguo,Wang, Sijia,Li, Kangning,&Li, Yongguang.(2021).Improving Estimates of Soil Salt Content by Using Two-Date Image Spectral Changes in Yinbei, China.REMOTE SENSING,13(20).
MLA	Xu, Xibo,et al."Improving Estimates of Soil Salt Content by Using Two-Date Image Spectral Changes in Yinbei, China".REMOTE SENSING 13.20(2021).