title: Rapid identification of soil cadmium pollution risk at regional scale based on visible and near-infrared spectroscopy.
abstract: Soil heavy metal pollution due to long-term sewage irrigation is a serious environmental problem in many irrigation areas in northern China. Quickly identifying its pollution status is an important basis for remediation. Visible-near-infrared reflectance spectroscopy (VNIRS) provides a useful tool. In a case study, 76 soil samples were collected and their reflectance spectra were used to estimate cadmium (Cd) concentration by partial least squares regression (PLSR) and back propagation neural network (BPNN). To reduce noise, six pre-treatments were compared, in which orthogonal signal correction (OSC) was first used in soil Cd estimation. Spectral analysis and geostatistics were combined to identify Cd pollution hotspots. Results showed that Cd was accumulated in topsoil at the study area. OSC can effectively remove irrelevant information to improve prediction accuracy. More accurate estimation was achieved by applying a BPNN. Soil Cd pollution hotspots could be identified by interpolating the predicted values obtained from spectral estimates.
authors.affiliation: College of Resources and Environment, Northwest A&F University, Shaanxi, Yangling 712100, China. Electronic address: davidlp77@zju.edu.cn.
authors.forename: Tao
authors.initials: T
authors.lastname: Chen
authors.affiliation: College of Resources and Environment, Northwest A&F University, Shaanxi, Yangling 712100, China. Electronic address: changqr@nwsuaf.edu.cn.
authors.forename: Qingrui
authors.initials: Q
authors.lastname: Chang
authors.affiliation: Laboratory of Geo-Information Science and Remote Sensing, Wageningen University, Droevendaalsesteeg 3, 6708 PB Wageningen, The Netherlands.
authors.forename: J G P W
authors.initials: JG
authors.lastname: Clevers
authors.affiliation: Laboratory of Geo-Information Science and Remote Sensing, Wageningen University, Droevendaalsesteeg 3, 6708 PB Wageningen, The Netherlands.
authors.forename: L
authors.initials: L
authors.lastname: Kooistra
mesh_terms: D057914:Agricultural Irrigation; D002104:Cadmium / Q000032:analysis*; D002681:China; D004784:Environmental Monitoring / Q000295:instrumentation / Q000379:methods*; D004787:Environmental Pollution / Q000032:analysis; D016018:Least-Squares Analysis; D016571:Neural Networks, Computer; D012722:Sewage / Q000032:analysis; D012987:Soil / Q000737:chemistry / Q000592:standards; D012989:Soil Pollutants / Q000032:analysis*; D019265:Spectroscopy, Near-Infrared / Q000295:instrumentation / Q000379:methods*; D013997:Time Factors
chemical_list: D012722:Sewage; D012987:Soil; D012989:Soil Pollutants; D002104:Cadmium
keywords: Back propagation neural network; Indicator kriging; Orthogonal signal correction; Soil cadmium; Visible and near-infrared spectroscopy