干旱区生态环境知识资源中心(Arid): Monitoring of Soil Salinization in the Keriya Oasis Based on Deep Learning with PALSAR-2 and Landsat-8 Datasets

Arid

DOI	10.3390/su14052666
	Monitoring of Soil Salinization in the Keriya Oasis Based on Deep Learning with PALSAR-2 and Landsat-8 Datasets
	Abulaiti, Adilai; Nurmemet, Ilyas; Muhetaer, Nuerbiye; Xiao, Sentian; Zhao, Jing
通讯作者	Nurmemet, I
来源期刊	SUSTAINABILITY
EISSN	2071-1050
出版年	2022
卷号	14 期号:5
英文摘要	Currently, soil salinization is one of the main forms of land degradation and desertification. Soil salinization not only seriously restricts the development of agriculture and the economy, but also poses a threat to the ecological environment. The main purpose of this study is to map soil salinity in Keriya Oasis, northwestern China using the PALSAR-2 fully polarized synthetic aperture radar (PolSAR) L-band data and Landsat-8-OLI (OLI) optical data combined with deep learning (DL) methods. A field survey is conducted, and soil samples are collected from 20 April 2015 to 1 May 2015. To mine the hidden information in the PALSAR-2 data, multiple polarimetric decomposition methods are implemented, and a wide range of polarimetric parameters and synthetic aperture radar discriminators are derived. The radar vegetation index (RVI) is calculated using PALSAR-2 data, while the normalized difference vegetation index (NDVI) and salinity index (SI) are calculated using OLI data. The random forest (RF)-integrated learning algorithm is used to select the optimal feature subset composed of eight polarimetric elements. The RF, support vector machine, and DL methods are used to extract different degrees of salinized soil. The results show that the OLI+PALSAR-2 image classification result of the DL classification was relatively good, having the highest overall accuracy of 91.86% and a kappa coefficient of 0.90. This method is helpful to understand and monitor the spatial distribution of soil salinity more effectively to achieve sustainable agricultural development and ecological stability.
英文关键词	soil salinization PALSAR-2 polarimetric decomposition deep learning
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E ; SSCI
WOS记录号	WOS:000769443400001
WOS关键词	POLARIMETRIC SAR DATA ; SCATTERING MODEL ; SALINITY ; CLASSIFICATIONS ; VEGETATION ; ACCURACY ; MOISTURE ; DESERT ; RIVER
WOS类目	Green & Sustainable Science & Technology ; Environmental Sciences ; Environmental Studies
WOS研究方向	Science & Technology - Other Topics ; Environmental Sciences & Ecology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/394545
推荐引用方式 GB/T 7714	Abulaiti, Adilai,Nurmemet, Ilyas,Muhetaer, Nuerbiye,et al. Monitoring of Soil Salinization in the Keriya Oasis Based on Deep Learning with PALSAR-2 and Landsat-8 Datasets[J],2022,14(5).
APA	Abulaiti, Adilai,Nurmemet, Ilyas,Muhetaer, Nuerbiye,Xiao, Sentian,&Zhao, Jing.(2022).Monitoring of Soil Salinization in the Keriya Oasis Based on Deep Learning with PALSAR-2 and Landsat-8 Datasets.SUSTAINABILITY,14(5).
MLA	Abulaiti, Adilai,et al."Monitoring of Soil Salinization in the Keriya Oasis Based on Deep Learning with PALSAR-2 and Landsat-8 Datasets".SUSTAINABILITY 14.5(2022).