Estimating Soil Salinity in the Yellow River Delta, Eastern China-An Integrated Approach Using Spectral and Terrain Indices with the Generalized Additive Model

doi:10.1016/S1002-0160(15)60071-6

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	Estimating Soil Salinity in the Yellow River Delta, Eastern China-An Integrated Approach Using Spectral and Terrain Indices with the Generalized Additive Model
	Song Chuangye ; Ren Hongxu 1; Huang Chong 3
刊名	PEDOSPHERE
	2016
卷号	26 期号:5 页码:626-635
关键词	Akaike's information criterion digital elevation model Landsat TM image soil salt content terrain in indices vegetation cover
ISSN号	1002-0160
DOI	10.1016/S1002-0160(15)60071-6
文献子类	Article
英文摘要	Soil salinity is one of the most severe environmental problems worldwide. It is necessary to develop a soil-salinity-estimation model to project the spatial distribution of soil salinity. The aims of this study were to use remote sensed images and digital elevation model (DEM) to develop quantitative models for estimating soil salinity and to investigate the influence of vegetation on soil salinity estimation. Digital bands of Landsat Thematic Mapper (TM) images, vegetation indices, and terrain indices were selected as predictive variables for the estimation. The generalized additive model (GAM) was used to analyze the quantitative relationship between soil salt content, spectral properties, and terrain indices. Akaike's information criterion (AIC) was used to select relevant predictive variables for fitted GAMs. A correlation analysis and root mean square error between predicted and observed soil salt contents were used to validate the fitted GAMs. A high ratio of explained deviance suggests that an integrated approach using spectral and terrain indices with GAM was practical and efficient for estimating soil salinity. The performance of the fitted GAMs varied with changes in vegetation cover. Salinity in sparsely vegetated areas was estimated better than in densely vegetated areas. Visible red and near-infrared bands, and the second and third components of the tasseled cap transformation were the most important spectral variables for the estimation. Variable combinations in the fitted GAMs and their contribution varied with changes in vegetation cover. The contribution of terrain indices was smaller than that of spectral indices, possibly due to the low spatial resolution of DEM. This research may provide some beneficial references for regional soil salinity estimation.
学科主题	Soil Science
电子版国际标准刊号	2210-5107
出版地	BEIJING
WOS关键词	SALT-AFFECTED SOILS ; DECISION-TREE ; REFLECTANCE ; PREDICTION ; REGION ; COUNTY
WOS研究方向	Science Citation Index Expanded (SCI-EXPANDED)
语种	英语
出版者	SCIENCE PRESS
WOS记录号	WOS:000383219200004
资助机构	National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [4100-1363, 41471335] ; Ocean Public Welfare Scientific Research Project, China [201305021]
内容类型	期刊论文
源URL	[http://ir.ibcas.ac.cn/handle/2S10CLM1/25144]
专题	植被与环境变化国家重点实验室
作者单位	1.Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, Beijing 100093, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources, Beijing 101001, Peoples R China 3.Chinese Acad Sci, Inst Bot, Key Lab Plant Resources, Beijing 100093, Peoples R China
推荐引用方式 GB/T 7714	Song Chuangye,Ren Hongxu,Huang Chong. Estimating Soil Salinity in the Yellow River Delta, Eastern China-An Integrated Approach Using Spectral and Terrain Indices with the Generalized Additive Model[J]. PEDOSPHERE,2016,26(5):626-635.
APA	Song Chuangye,Ren Hongxu,&Huang Chong.(2016).Estimating Soil Salinity in the Yellow River Delta, Eastern China-An Integrated Approach Using Spectral and Terrain Indices with the Generalized Additive Model.PEDOSPHERE,26(5),626-635.
MLA	Song Chuangye,et al."Estimating Soil Salinity in the Yellow River Delta, Eastern China-An Integrated Approach Using Spectral and Terrain Indices with the Generalized Additive Model".PEDOSPHERE 26.5(2016):626-635.