基于水热因子波动的呼伦贝尔草原产草量模型

基于多年气象资料(温度和降水量)和产草量监测数据,采用相关分析、主成分分析和回归分析等方法,构建呼伦贝尔草原产草量与气象因子统计学模型,并对二者之间的关系进行了分析.结果表明:利用水热波动因子建立的多项式回归模型具有较好的拟合效果,所建立的呼伦贝尔草原产草量预测模型为y=100.209+1.6410x-0.00559x2.F值显著性检验表明,其复相关系数R2=0.4713,F=8.0239(P=0.0033),在α=0.01水平上显著.利用1989─2009年呼伦贝尔草原产草量数据进行模型精度检验,模型预测精度在85%以上.该预测模型具有选用参数易得、易于代入遥感数据中进行栅格计算、精度高于基于植被指数预测模型等特点.

Above Ground Biomass Forecasting Model Based on Fluctuations of Precipitation and Temperature in Hulunbei'er Grassland

Based on data of above ground biomass and meteorological parameters (temperature and precipitation) in Hulunbeier grassland, correlation analysis, principal component analysis and regression analysis were adopted to identify relationships between above ground biomass and meteorological parameters and to establish a forecasting model for above ground biomass. Results showed that the polynomial regression model considering fluctuations of precipitation and temperature had better fitting results. The forecasting model could be expressed as y=100.209+1.6410x-0.005 59x~2. F-value checking indicated that the multiple correlation coefficient R2=0.4713, F=8.0239(P=0.0033), indicating a 0.01 significant level. The model accuracy tested with the data of above ground biomass in the past 21 years is over 85%. The selection parameter data of model are more accessible and easier to be imported into remote-sensing data for raster calculation. In accuracy, the model was higher than forecasting model based on NDVI.