An alternative approach for estimating above ground biomass using Resourcesat-2 satellite data and artificial neural network in Bundelkhand region of India
作者: Dibyendu DebJ. P. SinghShovik DebDebajit DattaArunava GhoshR. S. Chaurasia
作者单位: 1Indian Grassland and Fodder Research Institute
2Uttar Banga Krishi Viswavidyalaya
3Jadavpur University
刊名: Environmental Monitoring and Assessment, 2017, Vol.189 (11)
来源数据库: Springer Nature Journal
DOI: 10.1007/s10661-017-6307-6
关键词: Above ground biomassAllometric equationArtificial neural networkNormalized difference vegetation indexSatellite image
英文摘要: Determination of above ground biomass (AGB) of any forest is a longstanding scientific endeavor, which helps to estimate net primary productivity, carbon stock and other biophysical parameters of that forest. With advancement of geospatial technology in last few decades, AGB estimation now can be done using space-borne and airborne remotely sensed data. It is a well-established, time saving and cost effective technique with high precision and is frequently applied by the scientific community. It involves development of allometric equations based on correlations of ground-based forest biomass measurements with vegetation indices derived from remotely sensed data. However, selection of the best-fit and explanatory models of biomass estimation often becomes a difficult proposition with...
原始语种摘要: Determination of above ground biomass (AGB) of any forest is a longstanding scientific endeavor, which helps to estimate net primary productivity, carbon stock and other biophysical parameters of that forest. With advancement of geospatial technology in last few decades, AGB estimation now can be done using space-borne and airborne remotely sensed data. It is a well-established, time saving and cost effective technique with high precision and is frequently applied by the scientific community. It involves development of allometric equations based on correlations of ground-based forest biomass measurements with vegetation indices derived from remotely sensed data. However, selection of the best-fit and explanatory models of biomass estimation often becomes a difficult proposition with...
全文获取路径: Springer Nature  (合作)
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影响因子:1.592 (2012)

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关键词翻译
关键词翻译
  • estimating 价值估计
  • neural 神经系统的
  • approach 
  • above 在上面
  • artificial 人为的
  • biomass 生物量
  • explanatory 说明
  • estimate 估计
  • ANN All Numeral Numbering
  • saving 节省