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应用生态学报 ›› 2010, Vol. 21 ›› Issue (12): 3099-3104.

• 研究报告 • 上一篇    下一篇

基于环境辅助变量的拔山茶园土壤肥力空间预测

邱乐丰1,杨 超1,林芬芳2,杨 宁1,郑辛煜1,许红卫1,王 珂1**   

  1. 1浙江大学环境与资源学院农业遥感和信息技术应用研究所,杭州 310029;2南京信息工程大学遥感学院,南京 210044
  • 出版日期:2010-12-18 发布日期:2010-12-18

Spatial pattern of soil fertility |in Bashan tea garden: A prediction based on environmental auxiliary variables.

QIU Le-feng1, YANG Chao1, LIN Fen-fang2, YANG Ning1, ZHENG Xin-yu1, XU Hong-wei1, WANG Ke1   

  1. 1Institute of Agricultural Remote Sensing and Information Technology Application, Zhejiang University, Hangzhou 310029, China;2School of Remote Sensing, Nanjing University of Information Science &|Technology, Nanjing 210044, China
  • Online:2010-12-18 Published:2010-12-18

摘要: 以地形因子、植被覆盖度等为辅助变量,利用回归克里格法预测低山丘陵区茶园土壤肥力,分析了富阳市拔山茶园土壤肥力的空间变异规律.结果表明:相对高程、平/纵向曲率等结构性因素是引起研究区土壤肥力空间变异的主要原因,研究区土壤肥力沿海拔高度呈垂直变化,随着海拔高度的降低土壤肥力水平也逐渐降低;拔山茶园土壤肥力总体较高,肥力较低的区域面积仅占研究区总面积的5%.回归克里格法所得土壤肥力的预测精度明显高于普通克里格,其平均预测误差和预测均方根误差分别为0.028和0.108.该方法能充分反映环境变量对土壤肥力的影响,提高土壤肥力的空间预测精度,可为茶园的精准管理提供依据.

关键词: 茶园, 土壤肥力, 回归克里格, 地形, 棉秆炭, Biolog, DGGE, 根际, 连作棉花

Abstract: Taking topographic factors and NDVI as auxiliary variables, and by using regression-kriging method, the spatial variation pattern of soil fertility  in Bashan tea garden in the hilly area of Fuyang City was explored. The spatial variability of the soil fertility  was mainly attributed to the structural factors such as relative elevation and flat/vertical curvature. The lower the relative elevation, the worse the soil fertility  was. The overall soil fertility level was relatively high, and the area with lower soil fertility only accounted for 5% of the total. By using regression-kriging method with relative elevation as auxiliary variable, the prediction accuracy of soil fertility  was obviously higher than that by using ordinary kriging method, with the mean error and root mean square error being 0.028 and 0.108, respectively. It was suggested that the prediction method used in this paper could fully reflect the effects of environmental variables on soil fertility , improve the prediction accuracy about the spatial pattern of soil fertility, and provide scientific basis for the precise management of tea garden.

Key words: tea garden, soil fertility, regression-kriging, topography, cotton stalk biochar, Biolog, DGGE, rhizosphere, continuous cropping cotton.