4.6 Article

Hyper-spectral remote sensing to monitor vegetation stress

Journal

JOURNAL OF SOILS AND SEDIMENTS
Volume 8, Issue 5, Pages 323-326

Publisher

SPRINGER HEIDELBERG
DOI: 10.1007/s11368-008-0030-4

Keywords

Agricultural soil; Pb contamination; Reflectance spectroscopy; Rice; Vegetation stress

Funding

  1. National Natural Science Foundation of China [40231016, 40621001]
  2. Frontier Project of the Chinese Academy of Sciences [ISSASIP0715]

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Background, aim, and scope Vegetation stress diagnoses based on plant sampling and physiochemical analysis using traditional methods are commonly time-consuming, destructive and expensive. The measurement of field spectral reflectance is one basis of airborne or spaceborne remote sensing monitoring. Materials and methods In this study, paddy plants were grown in the barrels evenly filled with 10.0 kg soil that was mixed respectively with 0, 2.5 x 207.2 and 5.0 x 207.2 mg Pb per 1,000 g soil. Rice canopy spectra were gathered by mobile hyper-spectral radiometer (ASD FieldSpec Pro FR, USA). Meanwhile, canopy leaves in the field-of-view (FOV) of spectroradiometer were collected and then prepared in the laboratory, (1) for chlorophyll measurement by Model 721 spectrophotometer, and (2) for Pb determination by atomic absorption spectrophotometer (SpectraAA-220FS). Results and discussion Canopy spectral reflectance in the region of visible-to-near-infrared light (VNIR) increased, because ascended Pb concentration caused the decrease of canopy chlorophyll content. In the agro-ecosystem, however, heavy metal contamination is presented typically as mixture and their interactions strongly affect actually occurring effects. Normalized spectral absorption depth (D-n), and shifting distance (DS) of red edge position (REPs) revealed the differences in Pb concentration for canopy leaves, especially at the early tillering stage. Due to insufficient biomass of rice plants, the 30th day was not reliable enough for the selection of crucial growth stages. Some special sensitive bands might be omitted at the same time because of limited sample sets. Conclusions Our initial experiments are still too few in the amounts of both metals and plants neither to build accurate prediction models nor to discuss the transformation from ground to air/spaceborne remote sensing. However, we are pleased to communicate that ground remote sensing measurements would provide reliable information for the estimation of Pb concentration in rice plants at the early tillering stage when proper features (such as DS and D-n) of reflectance spectra are applied. Recommendations and perspectives Hyper-spectral remote sensing is a potential and promising technology for monitoring environmental stresses on agricultural vegetation. Further ground remote sensing experiments are necessary to evaluate the possibility of hyper-spectral reflectance spectroscopy in monitoring different kinds of metals' stress on various plants.

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