CAJ | 학술논문

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+1.641 0x-0.005 59x~2. F值显著性检验表明,其复相关系数R2=0.471 3,F=8.023 9(P=0.003 3),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.
기우다년기상자료(온도화강수량)화산초량감측수거,채용상관분석、주성분분석화회귀분석등방법,구건호륜패이초원산초량여기상인자통계학모형,병대이자지간적관계진행료분석. 결과표명:이용수열파동인자건립적다항식회귀모형구유교호적의합효과,소건립적호륜패이초원산초량예측모형위y=100.209+1.641 0x-0.005 59x~2. F치현저성검험표명,기복상관계수R2=0.471 3,F=8.023 9(P=0.003 3),재α=0.01수평상현저. 이용1989─2009년호륜패이초원산초량수거진행모형정도검험,모형예측정도재85%이상.해예측모형구유선용삼수역득、역우대입요감수거중진행책격계산、정도고우기우식피지수예측모형등특점.
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.