Soil Salinity Inversion Model of Oasis in Arid Area Based on UAV Multispectral Remote Sensing

doi:10.3390/rs14081804

	Soil Salinity Inversion Model of Oasis in Arid Area Based on UAV Multispectral Remote Sensing
	Zhao, Wenju1 ; Zhou, Chun 1; Zhou, Changquan 1,2; Ma, Hong 1; Wang, Zhijun1,3
	2022-04
发表期刊	Remote Sensing
卷号	14 期号:8
摘要	Soil salinization severely restricts the development of global industry and agriculture and affects human beings. In the arid area of Northwest China, oasis saline-alkali land threatens the development of agriculture and food security. This paper develops and optimizes an inversion monitoring model for monitoring the soil salt content using unmanned aerial vehicle (UAV) multispectral remote sensing data. Using the multispectral remote sensing data in three research areas, the soil salt inversion models based on the support vector machine regression (SVR), random forest (RF), backpropagation neural network (BPNN), and extreme learning machine (ELM) were constructed. The results show that the four constructed models based on the spectral index can achieve good inversion accuracy, and the red edge band can effectively improve the soil salt inversion accuracy in saline-alkali land with vegetation cover. Based on the obtained results, for bare land, the best model for soil salt inversion is the ELM model, which reaches the determination coefficient (Rv2) of 0.707, the root mean square error RMSEv of 0.290, and the performance deviation ratio (RPD) of 1.852 on the test dataset. However, for agricultural land with vegetation cover, the best model for soil salinity inversion using the vegetation index is the BPNN model, which achieves Rv2 of 0.836, RMSEv of 0.027, and RPD of 2.100 on the test dataset. This study provides technical support for rapid monitoring and inversion of soil salinization and salinization control in irrigation areas. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
关键词	Agriculture Antennas Arid regions Decision trees Food supply Mean square error Neural networks Soil surveys Soils Statistical tests Support vector machines Unmanned aerial vehicles (UAV) Vegetation Arid area Inversion models Multi-spectral image data Multispectral remote sensing Remote sensing inversion model Remote-sensing Soil salinity Soil salinization Soil salt content Soil salts
DOI	10.3390/rs14081804
收录类别	EI ; SCIE
语种	英语
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS记录号	WOS:000787403700001
出版者	MDPI
EI入藏号	20221712039757
EI主题词	Remote sensing
EI分类号	443 Meteorology ; 444 Water Resources ; 483.1 Soils and Soil Mechanics ; 652.1 Aircraft, General ; 723 Computer Software, Data Handling and Applications ; 821 Agricultural Equipment and Methods ; Vegetation and Pest Control ; 822.3 Food Products ; 921.4 Combinatorial Mathematics, Includes Graph Theory, Set Theory ; 922.2 Mathematical Statistics ; 961 Systems Science
来源库	WOS
引用统计	被引频次：12[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	https://ir.lut.edu.cn/handle/2XXMBERH/158411
专题	能源与动力工程学院
通讯作者	Zhao, Wenju
作者单位	1.Lanzhou Univ Technol, Coll Energy & Power Engn, Lanzhou 730050, Peoples R China; 2.Lanzhou Coll Informat Sci & Technol, Sch Civil Engn, Lanzhou 730300, Peoples R China; 3.Lanzhou Univ Technol, Baiyin New Mat Res Inst, Baiyin 730900, Peoples R China
第一作者单位	能源与动力工程学院
通讯作者单位	能源与动力工程学院
第一作者的第一单位	能源与动力工程学院
推荐引用方式 GB/T 7714	Zhao, Wenju,Zhou, Chun,Zhou, Changquan,et al. Soil Salinity Inversion Model of Oasis in Arid Area Based on UAV Multispectral Remote Sensing[J]. Remote Sensing,2022,14(8).
APA	Zhao, Wenju,Zhou, Chun,Zhou, Changquan,Ma, Hong,&Wang, Zhijun.(2022).Soil Salinity Inversion Model of Oasis in Arid Area Based on UAV Multispectral Remote Sensing.Remote Sensing,14(8).
MLA	Zhao, Wenju,et al."Soil Salinity Inversion Model of Oasis in Arid Area Based on UAV Multispectral Remote Sensing".Remote Sensing 14.8(2022).