JOURNAL OF NATURAL RESOURCES ›› 2013, Vol. 28 ›› Issue (12): 2056-2067.doi: 10.11849/zrzyxb.2013.12.004

• Resources Ecology • Previous Articles     Next Articles

Hyperspectral Estimating Models of Aboveground Fresh Biomass and Density in Minjiang River Estuary Marsh Vegetation

ZHANG Wen-long, ZENG Cong-sheng, TONG Chuan, WANG Wei-qi, LIN Xian-biao, ZHANG Zi-chuan   

  1. 1. School of Geographical Sciences, Fujian Normal University, Fuzhou 350007, China;
    2. Key Laboratory of Humid Subtropical Eco-geographical Process (Fujian Normal University), Ministry of Education, Fuzhou 350007, China;
    3. Research Center of Wetlands in Subtropical Region, Fujian Normal University, Fuzhou 350007, China
  • Received:2012-10-17 Revised:2013-02-01 Online:2013-12-20 Published:2013-12-19
  • Contact: 曾从盛(1954-),男,研究员,博士生导师,主要从事湿地生态环境研究。E-mail:cszeng@fjnu.edu.cn E-mail:cszeng@fjnu.edu.cn

Abstract: Aboveground biomass of wetland vegetation is closely related with wetland ecosystem productivity, carbon cycle and nutrient cycle, and so on, is one of the main concerns in the present study. The canopy hyperspectral reflectance data of two tidal marshes dominated respectively by Phragmites australis and Cyperus malaccensis Lam. var. brevifolius Bocklr. was determined by ASDFieldSpec 2500 in the Shanyutan wetland in the Minjiang River estuary in October 2011 and October 2012, and the aboveground fresh biomass and plant density of the two marshes were collected simultaneously. The correlation between canopy reflectance, first derivative spectra and aboveground fresh biomass of P. australis and C. malaccensis was analyzed. The sensitive band was confirmed so as to improve vegetation index. Furthermore, using the regression analysis method, based on various vegetation indexes, the aboveground fresh biomass and plant density estimation model was constructed. The results showed that the aboveground fresh biomass was more closely correlated with the two marshes canopy reflectance in blue, red and near infrared band, and was relatively well correlated with first derivative spectra at blue edge and red edge. No matter canopy reflectance or first derivative spectra, the correlation of P. australis is better than C. malaccensis. Compared with other parameters, BNDVI, NDCI and MGBNDVI also have higher estimation accuracy of aboveground fresh biomass for both species, and BNDVI was the best estimated parameter of aboveground fresh biomass for both species and the estimation accuracy was higher for P. australis (R2=0.4085-0.765), while for C. malaccensis R2 ranged from 0.1019 to 0.3153. Furthermore, GBNDVI, BNDVI, MGBNDVI, NDCI and SR also have higher estimation accuracy in plant density for both species, and there is a higher plant density estimation accuracy for P. australis as well (R2=0.0930-0.718), while for C. malaccensis it ranges from 0.1389 to 0.2337, and the best estimate parameter are GBNDVI and NDCI respectively. To some extent, it is feasible to use remote sensing data to estimate aboveground fresh biomass and plant density based on the models built in this work.

Key words: aboveground fresh biomass, vegetation index, Minjiang River estuary, hyperspectral remote sensing, plant density

CLC Number: 

  • Q948