Extraction of aquatic plants based on continuous removal method and analysis of its temporal and spatial changes—A case study of Guanting Reservoir

WANG Xing1,2,3,4 GONG Zhao-Ning1,2,3,4 JING Ran1,2,3,4 ZHANG Lei1,2,3,4 JIN Dian-Dian1,2,3,4

(1.College of Resource Environment & Tourism, Capital Normal University, Beijing, China 100048)
(2.Key Laboratory of 3D Information Acquisition and Application, Ministry of Education, Beijing, China 100048)
(3.Key Laboratory of Resources Environment and GIS of Beijing Municipal, Beijing, China 100048)
(4.Base of the State Laboratory of Urban Environmental Processes and Digital Modeling, Beijing, China 100048)

【Abstract】 Aims Screening of spectral characteristic variables is one of the important means for aquatic plant recognition, and it is widely applied in aquatic plant species identification. In this paper, a method for identifying aquatic plants species was constructed by combining the extracted spectral feature information with the multi-temporal Landsat 8 OLI image data analysis. Methods In the analysis of reflectance spectra of aquatic plants, the method of continuum removal for mineral analysis was introduced. The spectral resampling was performed on the measured spectral curve, and the spectral absorption depth was characterized by the continuous removal of the spectral resampling results. One-way ANOVA method was used to compare the seven spectral resampling bands and the three continuum removal absorption depth sensitive bands. Then the characteristic bands with significant differentiation of different aquatic plants were selected. The continuum removal was applied on remote sensing image processing. The results of the spectroscopic analysis were used to guide the identification of aquatic plants in using Landsat 8 OLI. The classification of aquatic plants was carried out by using support vector machine (SVM) classification. Important findings The results of the measured spectrum resampling were similar to the atmospheric calibration of Landsat 8 OLI in the same position, and the results of the measured spectral curves could be used to guide the classification of Landsat 8 OLI. The one-way ANOVA method was used to compare seven spectral resampling bands and three continuous systems in absorbing sensitive wavelengths. The results showed that the short wave infrared 1 band, which was processed by continuum removal (SWIR1CR), was the best in distinguishing different types of aquatic plants. In this paper, the continuum removal was applied on remote sensing image processing, and it was found that the SWIR1CR band could better distinguish the submerged plants and the emergent plants. The normalized differential vegetation index and SWIR1CR band were well capable of identifying submerged plants, floating plants, and emergent plants. Based on the SVM classification method, the classification accuracy of aquatic plants was 86.33%. The aquatic plants were mainly distributed in shallow water areas of the south north bank of Guanting Reservoir. When the aquatic plant distribution area reached the peak, it accounted for about 35.13% of the total area of the reservoir. The growth distribution of submerged plants changed significantly during a year. The stem and leaves of submerged plants began to emerge in early June. Aquatic plants began to wither in October, and aquatic plants accounted for only 20% of the total area in November.

【Keywords】 continuous removal; spectral absorption depth; one-way ANOVA; spatiotemporal variation; the short wave infrared I band;


【Funds】 International Science & Technology Cooperation Program of China (2014DFA21620)

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This Article



Vol 42, No. 06, Pages 640-652

June 2018


Article Outline


  • 1 Data acquisition
  • 2 Methods
  • 3 Results and discussion
  • 4 Conclusions and prospects
  • References