DOI: 10.1016/j.jag.2016.05.003
Scopus记录号: 2-s2.0-84997124457
论文题名: Regional heavy metal pollution in crops by integrating physiological function variability with spatio-temporal stability using multi-temporal thermal remote sensing
作者: Liu M ; , Liu X ; , Zhang B ; , Ding C
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2016
卷: 51 起始页码: 91
结束页码: 102
语种: 英语
英文关键词: Heavy metal stress
; Physiological function variability
; Spatio-temporal stability
; Thermal infrared remote sensing
; Time-spectrum feature space model
英文摘要: Heavy metal stress in crops is characterized by stability in space and time, which differs from other stressors that are typically more transient (e.g., drought, pests/diseases, and mismanagement). The objective of this study is to assess regional heavy metal stress in rice by integrating physiological function variability with spatio-temporal stability based on multi-temporal thermal infrared (TIR) remote sensing images. The field in which the experiment was conducted is located in Zhuzhou City, Hunan Province, China. HJ-1B images and in-situ measured data were collected from rice growing in heavy metal contaminated soils. A stress index (SI) was devised as an indicator for the degree of heavy metal stress of the rice in different growth stages, and a time-spectrum feature space (TSFS) model was used to determine rice heavy metal stress levels. The results indicate that (i) SI is a good indicator of rice damage caused by heavy metal stress. Minimum values of SI occur in rice subject to high pollution, followed by larger SI with medium pollution and maximum SI for low pollution, for the same growth stage. (ii) SI shows some variation for different growth stages of rice, and the minimum SI occurs at the flowering stage. (iii) The TSFS model is successful at identifying rice heavy metal stress, and stress levels in rice stabilized regardless of the model being applied in the two different years. This study suggests that regional heavy metal stress in crops can be accurately detected using TIR technology, if a sensitive indicator of crop physiological function impairment is used and an effective model is selected. A combination of spectrum and spatio-temporal information appears to be a very promising method for monitoring crops with various stressors. © 2016 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/80067
Appears in Collections: 气候变化事实与影响
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作者单位: School of Information Engineering, China University of Geosciences, 29 Xueyuan Road, Beijing, China
Recommended Citation:
Liu M,, Liu X,, Zhang B,et al. Regional heavy metal pollution in crops by integrating physiological function variability with spatio-temporal stability using multi-temporal thermal remote sensing[J]. International Journal of Applied Earth Observation and Geoinformation,2016-01-01,51