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基于TM影像的表层土壤有机碳空间格局

李欣宇;宇万太;李秀珍   

  1. 中国科学院沈阳应用生态研究所, 沈阳 110016
  • 收稿日期:2007-05-29 修回日期:1900-01-01 出版日期:2008-03-10 发布日期:2008-03-10

Spatial distribution pattern of surface soil organic carbon based on TM image.

LI Xin-yu; YU Wan-tai; LI Xiu-zhen   

  1. Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China
  • Received:2007-05-29 Revised:1900-01-01 Online:2008-03-10 Published:2008-03-10

摘要: 土壤有机碳是土壤肥力的核心指标之一,理解其空间分布格局对促进精准农业的发展和科学施肥具有重要意义。本研究旨在检验TM影像结合地面采样数据分析黑龙江省黑土分布区表层土壤有机碳空间分布格局的可行性。结果表明:1)表层土壤有机碳浓度与TM5波段呈显著正相关(r=0.553,P<0.01),与TM4、TM5波段影像像素值之间满足二次多项式回归关系(R2=0.6791,P<0.05);2)回归模型对表层土壤有机碳空间分布格局具有较好的预测效果(R2=0.7097,P<0.05);3)海拔高于200 m的地区表层土壤有机碳浓度显著高于海拔低于200 m的地区(P<0.05)。

关键词: 凋落物, 琉球松, 亚热带松林, 养分动态, 养分利用效率

Abstract: Soil organic carbon (SOC) is one of the core indices of soil fertility. To understand the spatial distribution pattern of SOC is of importance in promoting the development of precision agriculture and in implementing scientific fertilization. The objective of this study was to examine the feasibility of using TM image combined with field observation data in approaching the spatial distribution pattern of surface SOC in Heilongjiang Phaeozem region. The results indicated that the SOC had a significant positive correlation (r=0.553, P<0.01) with TM 5 band, and a binomial regression (R2=0.6791, P<0.05) with the image intensities of TM 4 and 5 bands. Regression model could better predict the spatial distribution pattern of SOC (R2=0.7097, P<0.05), and the SOC concentration was significantly higher in the regions with an altitude >200 than those with the altitude of < 200 m (P<0.05).

Key words: Litterfall, Pinus luchuensis, Subtropical pine forest, Nutrient dynamics, Nutrient use efficiency