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林业资源管理 ›› 2018, Vol. 0 ›› Issue (4): 105-111.doi: 10.13466/j.cnki.lyzygl.2018.04.017

• 科学研究 • 上一篇    下一篇

盐城海滨湿地植被地上生物量遥感反演研究

韩爽1(), 甄艳2, 谭清梅3, 刘玉卿1, 张华兵1()   

  1. 1.盐城师范学院 城市与规划学院,江苏 盐城 224007
    2.西南石油大学 地球科学与技术学院,成都 610500
    3.江苏省辐射环境保护咨询中心,南京 210019
  • 收稿日期:2018-05-16 修回日期:2018-07-11 出版日期:2018-08-28 发布日期:2020-09-25
  • 通讯作者: 张华兵
  • 作者简介:韩爽(1982-),女,江苏盐城人,讲师,硕士,主要从事湿地生态研究。Email:hanshuang412@163.com
  • 基金资助:
    国家自然科学基金项目(41771199);国家自然科学基金项目(41501567);江苏省基础研究计划(自然科学基金项目)(BK20171277);江苏省基础研究计划(自然科学基金项目)(BK20160446);江苏省高等学校自然科学研究项目(18KJD170001)

Remote Sensing Inversion of Aboveground Biomass in Yancheng Coastal Wetlands

HAN Shuang1(), ZHEN Yan2, TAN Qingmei3, LIU Yuqing1, ZHANG Huabing1()   

  1. 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:2018-05-16 Revised:2018-07-11 Online:2018-08-28 Published:2020-09-25
  • Contact: ZHANG Huabing

摘要:

以盐城自然保护区核心区的ETM+遥感影像和同期野外实测生物量为数据源,建立BP神经网络模型反演研究区地上生物量。结果表明:运用BP神经网络模型反演生物量湿重、干重精度分别达到了70%和74%;研究区生物量总量湿重为4.996×108kg,干重为9.370×107kg;在空间上呈现出海陆分异明显,海岸方向变化缓慢;米草、芦苇、碱蓬这3种植物的单位面积生物量呈现由高到低的特征,碱蓬的生物量干重集中在0~1.5kg/m2,湿重集中在0~6kg/m2;米草的生物量干重集中在1~2kg/m2,湿重集中在8kg/m2以上;芦苇的生物量干重集中在0~2kg/m2,湿重集中在2~6kg/m2,生物量与株高、盖度呈正相关,干重与二者相关性更强;生物量与生态位、土壤环境要素呈正相关,尤其与土壤养分相关性最强。

关键词: 湿地植被生物量, 遥感, BP神经网络模型, 影响因素, 盐城自然保护区

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.

Key words: wetlands vegetation biomass, remote sensing, BP neural network model, impacts, Yancheng Natural Reserve

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