干旱区生态环境知识资源中心(Arid): Quantitative Estimation of Soil Salinization in an Arid Region of the Keriya Oasis Based on Multidimensional Modeling

Arid

DOI	10.3390/w12030880
	Quantitative Estimation of Soil Salinization in an Arid Region of the Keriya Oasis Based on Multidimensional Modeling
	Kasim, Nijat 1; Maihemuti, Balati 2; Sawut, Rukeya 3; Abliz, Abdugheni 2; Dong, Cui 1; Abdumutallip, Munira 4
通讯作者	Maihemuti, Balati
来源期刊	WATER
EISSN	2073-4441
出版年	2020
卷号	12 期号:3
英文摘要	Soil salinity is one of the major factors causing land degradation and desertification on earth, especially its important damage to farming activities and land-use management in arid and semiarid regions. The salt-affected land is predominant in the Keriya River area of Northwestern China. Then, there is an urgent need for rapid, accurate, and economical monitoring in the salt-affected land. In this study, we used the electrical conductivity (EC) of 353 ground-truth measurements and predictive capability parameters of WorldView-2 (WV-2), such as satellite band reflectance and newly optimum spectral indices (OSI) based on two dimensional and three-dimensional data. The features of spectral bands were extracted and tested, and different new OSI and soil salinity indices using reflectance of wavebands were built, in which spectral data was pre-processed (based on First Derivative (R-FD), Second Derivative (R-SD), Square data (R-SQ), Reciprocal inverse (1/R), and Reciprocal First Derivative (1/R-FD)), utilizing the partial least-squares regression (PLSR) method to construct estimation models and mapping the regional soil-affected land. The results of this study are the following: (a) the new OSI had a higher relevance to EC than one-dimensional data, and (b) the cross-validation of established PLSR models indicated that the beta-PLSR model based on the optimal three-band index with different process algorithm performed the best result with R-V(2) = 0.79, Root Mean Square Errors (RMSEV) = 1.51 dSm(-1), and Relative Percent Deviation (RPD) = 2.01 and was used to map the soil salinity over the study site. The results of the study will be helpful for the study of salt-affected land monitoring and evaluation in similar environmental conditions.
英文关键词	soil salinization optimized spectral algorithm Keriya River EC arid region
类型	Article
语种	英语
国家	Peoples R China
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:000529249500265
WOS关键词	SPATIAL VARIABILITY ; ORGANIC-CARBON ; SALINITY ; CHINA ; SPECTROSCOPY
WOS类目	Environmental Sciences ; Water Resources
WOS研究方向	Environmental Sciences & Ecology ; Water Resources
来源机构	新疆大学
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/318875
作者单位	1.Yili Normal Univ, Coll Biol & Geog, Yining 835000, Peoples R China; 2.Xinjiang Univ, Coll Resources & Environm Sci, Urumqi 830046, Peoples R China; 3.Dalian Maritime Univ, Nav Coll, Dalian 116026, Peoples R China; 4.Fudan Univ, Inst Atmospher Sci, Dept Environm Sci & Engn, Shanghai Key Lab Atmospher Particle Pollut & Prev, Shanghai 200438, Peoples R China
推荐引用方式 GB/T 7714	Kasim, Nijat,Maihemuti, Balati,Sawut, Rukeya,et al. Quantitative Estimation of Soil Salinization in an Arid Region of the Keriya Oasis Based on Multidimensional Modeling[J]. 新疆大学,2020,12(3).
APA	Kasim, Nijat,Maihemuti, Balati,Sawut, Rukeya,Abliz, Abdugheni,Dong, Cui,&Abdumutallip, Munira.(2020).Quantitative Estimation of Soil Salinization in an Arid Region of the Keriya Oasis Based on Multidimensional Modeling.WATER,12(3).
MLA	Kasim, Nijat,et al."Quantitative Estimation of Soil Salinization in an Arid Region of the Keriya Oasis Based on Multidimensional Modeling".WATER 12.3(2020).