Chin J Plan Ecolo ›› 2018, Vol. 42 ›› Issue (6): 640-652.DOI: 10.17521/cjpe.2017.0240

• Research Articles • Previous Articles     Next Articles

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

WANG Xing,GONG Zhao-Ning(),JING Ran,ZHANG Lei,JIN Dian-Dian   

  1. College of Resource Environment & Tourism, Capital Normal University, Beijing 100048, China; Key Laboratory of 3D Information Acquisition and Application,Ministry of Education, Beijing 100048, China; Key Laboratory of Resources Environment and GIS of Beijing Municipal, Beijing 100048, China; Base of the State Laboratory of Urban Environmental Processes and Digital Modeling, Beijing 100048, China
  • Received:2017-09-13 Revised:2018-04-04 Online:2018-06-20 Published:2018-06-20
  • Contact: Zhao-Ning GONG
  • Supported by:
    Supported by the International Science & Technology Cooperation Program of China(2014DFA21620)


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 extracted spectral feature information with the multi-temporal Landsat 8 OLI image data analysis.

Methods In analyzing 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 are similar to the atmospheric calibration of Landsat 8 OLI in the same position, and the results of the measured spectral curves can 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 can 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 accuracies of aquatic plants were 86.33%. The distribution of aquatic plants showed that 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.

Key words: continuous removal, spectral absorption depth, one-way ANOVA, spatiotemporal variation, the short wave infrared I band