Study on species identification of submerged aquatic vegetation based on spectral characteristics

ZOU Wei-na; ZHANG Li-quan; YUAN Lin

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Jul. 2014

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Article Navigation > Journal of East China Normal University (Natural Sciences) > 2014 > (4): 132-140

ZOU Wei-na, ZHANG Li-quan, YUAN Lin. Study on species identification of submerged aquatic vegetation based on spectral characteristics[J]. Journal of East China Normal University (Natural Sciences), 2014, (4): 132-140.

Citation:

ZOU Wei-na, ZHANG Li-quan, YUAN Lin. Study on species identification of submerged aquatic vegetation based on spectral characteristics[J]. Journal of East China Normal University (Natural Sciences), 2014, (4): 132-140.

Citation:

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Study on species identification of submerged aquatic vegetation based on spectral characteristics

1.
State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai 200062, China;
2.
School of Ecological Technology and Engineering, Shanghai Institute of Technology, Shanghai 201418, China

Received Date: 2013-07-01
Rev Recd Date: 2013-10-01
Publish Date: 2014-07-25

Abstract

Abstract

The among-species spectral characteristics of submerged aquatic vegetation (SAV) could provide effective parameters for species identification to timely monitor the distribution and growth status of SAV using remote sensing technology. In this study, the spectral reflectance of the typical SAV plants were measured using a FieldSpecTM Pro JR Spectroradiometer in Dianshan Lake, the largest natural freshwater lake in Shanghai suburbs, including 6 SAV species Najas marina, Hydrilla verticillata, Myriophyllum spicatum, Ceratophyllum demersum, Vallisneria natans and Potamogeton malaianus. The spectral characteristics of reflectance curves and first derivative curves for different species were analyzed, while vegetation indexes and spectral indexes were screened for identifying species of SAV using Principal Components Analysis (PCA). The results show that the reflectancecurves were similar in shape but much variable in magnitude at the visible and near infrared wavebands for different SAV species. The spectral index NAV, REP and NGP were the most sensitive characteristic index for identifying 6 SAV species. The index NAV, REP and NGP could well reflect and amplify the differences in morphological structure of plant, physiological and biochemical composition among different SAV species and the among-species discrimination of their habitat synthetically. The results from this study could be helpful to accurately interpret the community composition, distribution and biodiversity dynamics of SAV on a large scale from hyperspectral remote sensing image.
- submerged aquatic vegetation,
- species identification,
- spectral characteristics,
- reflectance,
- hyperspectral

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References(1)

References

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