干旱区生态环境知识资源中心(Arid): A longitudinal analysis of soil salinity changes using remotely sensed imageries

Arid

DOI	10.1038/s41598-024-60033-6
	A longitudinal analysis of soil salinity changes using remotely sensed imageries
	Bandak, Soraya; Movahedi-Naeini, Seyed Alireza; Mehri, Saeed; Lotfata, Aynaz
通讯作者	Bandak, S
来源期刊	SCIENTIFIC REPORTS
ISSN	2045-2322
出版年	2024
卷号	14 期号:1
英文摘要	Soil salinization threatens agricultural productivity, leading to desertification and land degradation. Given the challenges of conducting labor-intensive and expensive field studies and laboratory analyses on a large scale, recent efforts have focused on leveraging remote sensing techniques to study soil salinity. This study assesses the importance of soil salinity indices' derived from remotely sensed imagery. Indices derived from Landsat 8 (L8) and Sentinel 2 (S2) imagery are used in Random Forest (RF), eXtreme Gradient Boosting (XGBoost), Decision Tree (DT), and Support Vector Machine (SVR) are associated with the electrical (EC) conductivity of 280 soil samples across 24,000 hectares in Northeast Iran. The results indicated that the DT is the best-performing method (RMSE = 12.25, MAE = 2.15, R-2 = 0.85 using L8 data and RMSE = 10.9, MAE = 2.12, and R-2 = 0.86 using S2 data). Also, the results showed that Multi-resolution Valley Bottom Flatness (MrVBF), moisture index, Topographic Wetness Index (TWI), and Topographic Position Indicator (TPI) are the most important salinity indices. Subsequently, a time series analysis indicated a reduction in salinity and sodium levels in regions with installed drainage networks, underscoring the effectiveness of the drainage system. These findings can assist decision-making about land use and conservation efforts, particularly in regions with high soil salinity.
英文关键词	Soil salinization Remote sensing Predictive modeling Decision tree
类型	Article
语种	英语
开放获取类型	Green Published, gold
收录类别	SCI-E
WOS记录号	WOS:001253949600026
WOS关键词	MACHINE LEARNING ALGORITHMS ; DIFFERENCE WATER INDEX ; RANDOM FOREST ; VEGETATION INDEX ; SENTINEL-2 DATA ; PREDICTION ; REGION ; LAND ; MSI ; CLASSIFICATION
WOS类目	Multidisciplinary Sciences
WOS研究方向	Science & Technology - Other Topics
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/405613
推荐引用方式 GB/T 7714	Bandak, Soraya,Movahedi-Naeini, Seyed Alireza,Mehri, Saeed,et al. A longitudinal analysis of soil salinity changes using remotely sensed imageries[J],2024,14(1).
APA	Bandak, Soraya,Movahedi-Naeini, Seyed Alireza,Mehri, Saeed,&Lotfata, Aynaz.(2024).A longitudinal analysis of soil salinity changes using remotely sensed imageries.SCIENTIFIC REPORTS,14(1).
MLA	Bandak, Soraya,et al."A longitudinal analysis of soil salinity changes using remotely sensed imageries".SCIENTIFIC REPORTS 14.1(2024).