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	Mapping soil texture based on field soil moisture observations at a high temporal resolution in an oasis agricultural area
	Yang Renmin1,2; Liu Feng1; Zhang Ganlin1; Zhao Yuguo1; Li Decheng1; Yang Jinling1; Yang Fei1,2; Yang Fan1,2
刊名	Pedosphere
	2016-10-01
卷号	26期号:5页码:699-708
关键词	Digital soil mapping Fuzzy c-means clustering Low relief Particle-size distribution Semi-arid region Water content
ISSN号	1002-0160
DOI	10.1016/s1002-0160(15)60078-9
通讯作者	Zhang ganlin(glzhang@issas.ac.cn)
英文摘要	Due to the almost homogeneous topography in low relief areas, it is usually difficult to make accurate predictions of soil properties using topographic covariates. in this study, we examined how time series of field soil moisture observations can be used to estimate soil texture in an oasis agricultural area with low relief in the semi-arid region of northwest china. time series of field-observed soil moisture variations were recorded for 132 h beginning at the end of an irrigation event during which the surface soil was saturated. spatial correlation between two time-adjacent soil moisture conditions was used to select the factors for fuzzy c-means clustering. in each of the ten generated clusters, soil texture of the soil sample with the maximum fuzzy membership value was taken as the cluster centroid. finally, a linearly weighted average was used to predict soil texture from the centroids. the results showed that soil moisture increased with the increase of clay and silt contents, but decreased with the increase of sand content. the spatial patterns of soil moisture changed during the entire soil drying phase. we assumed that these changes were mainly caused by spatial heterogeneity of soil texture. a total of 64 independent samples were used to evaluate the prediction accuracy. the root mean square error (rmse) values of clay, silt and sand were 1.63, 2.81 and 3.71, respectively. the mean relative error (re) values were 9.57% for clay, 3.77% for silt and 12.83% for sand. it could be concluded that the method used in this study was effective for soil texture mapping in the low-relief oasis agricultural area and could be applicable in other similar irrigation agricultural areas.
WOS关键词	PARTICLE-SIZE DISTRIBUTION ; FEEDBACK DYNAMIC PATTERNS ; WIRELESS SENSOR NETWORK ; HEIHE RIVER-BASIN ; BRIGHTNESS TEMPERATURE ; HYDRAULIC-PROPERTIES ; PHYSICAL-PROPERTIES ; SPATIAL PREDICTION ; MODEL ; ATTRIBUTES
WOS研究方向	Agriculture
WOS类目	Soil Science
语种	英语
出版者	SCIENCE PRESS
WOS记录号	WOS:000383219200011
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/2376318
专题	中国科学院大学
通讯作者	Zhang Ganlin
作者单位	1.Chinese Acad Sci, Inst Soil Sci, State Key Lab Soil & Sustainable Agr, Nanjing 210008, Jiangsu, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式 GB/T 7714	Yang Renmin,Liu Feng,Zhang Ganlin,et al. Mapping soil texture based on field soil moisture observations at a high temporal resolution in an oasis agricultural area[J]. Pedosphere,2016,26(5):699-708.
APA	Yang Renmin.,Liu Feng.,Zhang Ganlin.,Zhao Yuguo.,Li Decheng.,...&Yang Fan.(2016).Mapping soil texture based on field soil moisture observations at a high temporal resolution in an oasis agricultural area.Pedosphere,26(5),699-708.
MLA	Yang Renmin,et al."Mapping soil texture based on field soil moisture observations at a high temporal resolution in an oasis agricultural area".Pedosphere 26.5(2016):699-708.

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