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[1]LIU Ji-ping,LIU Jia-xin,YU Yang,et al.Study on Spatial Variability of Available Nitrogen in Different Sampling Scale——A Case Study on Cropland Soil in Yushu City[J].Research of Soil and Water Conservation,2012,19(02):106-110,115.

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Study on Spatial Variability of Available Nitrogen in Different Sampling Scale——A Case Study on Cropland Soil in Yushu City

Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume: 19 Number of periods: 2012 02 Page number: 106-110,115 Column: Public date: 2012-04-20

Title:: Study on Spatial Variability of Available Nitrogen in Different Sampling Scale——A Case Study on Cropland Soil in Yushu City

Author(s):: LIU Ji-ping, LIU Jia-xin, YU Yang, TIAN Xue-zhi, XU Yan-yan; College of Tourist and Geoscience, Jilin Normal University, Siping, Jilin 136000, China

Keywords:: Kriging; BP neural network; available nitrogen of soil; sampling scale; spatial variability

CLC:: S153.6

DOI:: -

Abstract:: During the implementation of precision agriculture,it is a key issue to search for how to use the fewer samples to reflect the spatial variability of the field of information,and then use the scientific method of interpolation and the interpolation to estimate precision agriculture.In this paper,we choose Yushu City,a typical black soil area in northeaster China,which lies in Jilin Province as the study area to select relatively flat soil plots to sample and test soil nutrient in No.13 village of Gongpeng Town in Yushu City.The original sampling grid networks in accordance with certain intervals samples were taken and layed out based on the use of Kriging interpolation method and BP neural network for spatial interpolation,respectively,compared different scales(40m×40m,56m×56m,80m×80m,113m×113m,160m×160m) of spatial interpolation accuracy.The results show that:(1) with the increase of sample size,the spatial structure coefficient C/(C₀+C) of the available nitrogen tends to decrease,indicating that the unpredictable error increases within sampling interval,the performance of its spatial structure the ability to gradually declines;(2) Kriging interpolation accuracy was better than BP neural network.With the increase of sample scale,the simulation accuracy of the two models have decreased,but BP neural network model and Kriging interpolation accuracy and precision of the difference are very small;(3) terms from the Kriging and BP neural network models,from 80 m×80m to 113 m×113m scale change process,the average relative error is suddenly decreased,indicating that in the 113m×113m precision interpolation scale mutations,considering the spatial variability of available nitrogen and economic factors,the optimal sampling size of available nitrogen should be between 80m to 113m.

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