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Remote Sensing Inversion of Aboveground Biomass in Yancheng Coastal Wetlands

  • Shuang HAN ,
  • Yan ZHEN ,
  • Qingmei TAN ,
  • Yuqing LIU ,
  • Huabing ZHANG
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  • 1. College of City and Flanning,Yancheng Teacher’s University,Yancheng 224007,Jiangsu,China
    2. School of Geoscience and Technology,Southwest Petroleum University,Chengdu 610500,China
    3. Jiangsu Radiation Environmental Protection Consultation Center,Nanjing 210019,China

Received date: 2018-05-16

  Revised date: 2018-07-11

  Online published: 2020-09-25

Abstract

Taking the ETM + remote sensing image of the core area of Yancheng Nature Reserve and the field aboveground biomass measured in the same period as the data source,we built BP artificial neural network model and simulated biomass distribution of the study area.The conclusions of the study are as follows:The BP neural network model was used to retrieve the biomass of wet weight and dry weight,their accuracy arrived at 70% and 74% respectively.The total biomass of dry weight is 9.370×107kg and the total biomass of wet weight is 4.996×108kg.In the spatial variation,it mainly presents obvious difference from the land to the sea and slow change along the coast.The biomass of Spartina,reed and Suaeda range from high to low.The dry weight of Suaeda salsa’s biomass mainly concentrated in 1.5kg/m2,while its biomass of wet weight is concentrated in 0~6kg/m2; The dry weight of Spartina alterniflora’s biomass mainly concentrated in 1~2kg/m2,while its biomass of wet weight is over 8kg/m2; The dry weight of Reed’s biomass mainly concentrated in 0~2kg/m2,while its biomass of wet weight is concentrated in 2~6kg/m2.The biomass is positively correlated with plant height and coverage,and the correlation between dry weight and the two was stronger.The biomass was positively correlated with ecological niche and soil environmental factors,especially with soil nutrients.

Cite this article

Shuang HAN , Yan ZHEN , Qingmei TAN , Yuqing LIU , Huabing ZHANG . Remote Sensing Inversion of Aboveground Biomass in Yancheng Coastal Wetlands[J]. Forest and Grassland Resources Research, 2018 , 0(4) : 105 -111 . DOI: 10.13466/j.cnki.lyzygl.2018.04.017

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