Comparison of artificial neural networks, geographically weighted regression and Cokriging methods for predicting the spatial distribution of soil macronutrients (N, P, and K)
作者: Samad EmamgholizadehShahin ShahsavaniMohamad Amin Eslami
作者单位: 1Shahrood University of Technology
刊名: Chinese Geographical Science, 2017, Vol.27 (5), pp.747-759
来源数据库: Springer Journal
DOI: 10.1007/s11769-017-0906-6
关键词: Precision agricultureSoil characteristicsInterpolationArtificial neural networksGeographically weighted regressionCokriging
英文摘要: Soil macronutrients (i.e. nitrogen (N), phosphorus (P), and potassium (K)) are important soils components and knowing the spatial distribution of these parameters are necessary at precision agriculture. The purpose of this study was to evaluate the feasibility of different methods such as artificial neural networks (ANN) and two geostatistical methods (geographically weighted regression (GWR) and cokriging (CK)) to estimate N, P and K contents. For this purpose, soil samples were taken from topsoil (0–30 cm) at 106 points and analyzed for their chemical and physical parameters. These data were divided into calibration ( n = 84) and validation ( n = 22). Chemical and physical variables including clay, pH and organic carbon (OC) were used as auxiliary soil variables to estimate the N, P and...
原始语种摘要: Soil macronutrients (i.e. nitrogen (N), phosphorus (P), and potassium (K)) are important soils components and knowing the spatial distribution of these parameters are necessary at precision agriculture. The purpose of this study was to evaluate the feasibility of different methods such as artificial neural networks (ANN) and two geostatistical methods (geographically weighted regression (GWR) and cokriging (CK)) to estimate N, P and K contents. For this purpose, soil samples were taken from topsoil (0–30 cm) at 106 points and analyzed for their chemical and physical parameters. These data were divided into calibration ( n = 84) and validation ( n = 22). Chemical and physical variables including clay, pH and organic carbon (OC) were used as auxiliary soil variables to estimate the N, P and...
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影响因子:0.5 (2012)

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关键词翻译
关键词翻译
  • estimate 估计
  • regression 海退
  • neural 神经系统的
  • weighted 加权
  • macro 
  • purpose 目的
  • variable 变量
  • ANN All Numeral Numbering
  • artificial 人为的
  • model 模型