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基于因子分析的黑土反射光谱特征的主要影响因素 被引量:5

Principle Influence Factors for Hyperspectral Reflectance on Black-soil based on Factorial Analysis
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摘要 为明确土壤反射光谱特征的主要影响因素、避免非相关土壤理化参数的反射光谱模型,以单一土壤类型黑土为研究对象,利用数理统计与因子分析方法分析影响黑土反射光谱特征的主要土壤理化参数。结果表明:1)土壤理化参数与黑土高光谱反射率的相关系数随波长变化呈4种模式,分别为有机质控制型、水分控制型、正相关型和不相关型,有机质与水分是黑土反射光谱特征的主导因素;2)黑土高光谱反射率的4个主要公因子分别对应水分响应波段(2 210nm)、可见光有机质响应波段(485nm)、光谱曲线快速上升阶段(1 290nm)和可见光范围噪声较多波段(360nm);3)有机质、pH、全氮、全磷可以利用黑土反射光谱特征进行预测。 To identify the principle influence factors for soil spectral reflectance characteristics for its reflection spectrum model,and to avoid other non-relevant physicochemical properties,a single soil type, black-soil was analyzed by statistics and factorial analysis.The results showed that there were 4 types of the correlation coefficients between black-soil reflectance and soil properties,including organic matter control type,moisture control type,positive correlation type,and non-correlation type,among them,soil organic matter and moisture were the dominant factors.The four common factors derived from black-soil reflectance were moisture response bands (2210 nm),organic matter response bands (485 nm),rapid rising bands (1290 nm),and noise bands (360 nm).It could be concluded that soil organic matter,pH, total N,and total P be predicted by black-soil hyperspectral reflectance.
出处 《贵州农业科学》 CAS 北大核心 2014年第10期148-151,共4页 Guizhou Agricultural Sciences
基金 国家自然科学基金项目"基于土壤不同理化参数光谱特征差异的黑土有机质高光谱遥感反演研究"(40801167) 黑龙江省普通高等学校青年学术骨干支持计划"黑龙江玉米带农业灾害遥感监测与评价研究"(1251G010) 黑龙江省教育厅科学技术研究项目"哈大齐区域城市化水平遥感监测与城市生态安全研究"(11551038)
关键词 因子分析 黑土 有机质 土壤水分 反射光谱特征 factorial analysis black-soil organic matter moisture reflectance characteristics
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  • 1Casa R, Castaldi F, Pascucci S, et al. A comparison of sensor resolution and calibration strategies for soil texture estimation [ J ]. from hyperspectral remote sensing. Geoderma, 2013,197 : 17-26.
  • 2Martin P, Malley D, Manning G, et al. Determina- tion of soil organic carbon and nitrogen at the field level using near-infrared spectroscopy [J]. Canadian journal of soil science,2002,82(4):413-422.
  • 3李娜,赵慧洁,贾国瑞.因子分析模型的高光谱数据降维方法[J].中国图象图形学报,2011,16(11):2030-2035. 被引量:6
  • 4Huete A R. Separation of soil-plant spectral mixtures by factor analysis. Remote sensing of environment [J]. 1986,19(3) : 237-251.
  • 5Gomez C, Le Bissonnais Y, Annabi M, et al. Labo-ratory vis - nir spectroscopy as an alternative method for estimating the soil aggregate stability indexes of mediterranean soils[J]. Geoderma, 2013,209 : 86-97.
  • 6Volkan Bilgili A, Van Es H, Akbas F, et al. Visi- ble-near infrared reflectance spectroscopy for assess- ment of soil properties in a semi-arid area of turkey [J]. Journal of arid environments, 2010,74 (2) : 229- 238.
  • 7程朋根,吴剑,李大军,何挺.土壤有机质高光谱遥感和地统计定量预测[J].农业工程学报,2009,25(3):142-147. 被引量:32
  • 8Brown D J. Using a global vnir soibspectral library for local soil characterization and landscape modeling in a 2nd-order Uganda watershed [J]. Geoderma, 2007,140(4) :444-453.
  • 9Udelhoven T, Emmerling C, Jarmer T. Quantitative analysis of soil chemical properties with diffuse reflec- tance spectrometry and partial least-square regres- sion: A feasibility study[J]. Plant and Soil, 2003,251 (2) :319-329.
  • 10Weidong L, Baret F, Xingfa G, et al. Relating soil surface moisture to reflectance. Remote sensing of environment[J]. 2002,81 (2) : 238-246.

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