基于多种回归分析方法的西北干旱区植被NPP遥感反演研究

发布时间：2018-07-17 03:34

【摘要】：植被净初级生产力(Net Primary Productivity,NPP)是评价陆地生态系统的重要参数,植被NPP的反演为全球碳循环的研究提供了重要的参考依据。本文基于2000-2014年的MODIS及气象站点数据,引入逐步线性回归、主成分回归、偏最小二乘回归以及岭回归分析,构建了多元逐步回归模型、主成分回归模型、偏最小二乘回归模型和岭回归模型,并对这4种模型进行了评估。结果表明:①多元逐步回归模型被认为是一种可以简单、高效、准确地反演西北干旱区植被NPP的模型,且模拟结果与MOD17A3产品及实测值具有很强的相关性;②西北干旱区多年平均植被NPP的分布具有明显的区域差异,山区增加,平原区减少,呈现出北部及西北部高,而南部及东南部低的特征;③西北干旱区NPP在年际变化上呈波动增加趋势,线性增长率为0.40g C/(m·a)。自2000年以来,58.66%区域的NPP呈现增长趋势,13.64%的地区保持不变,27.7%的地区表现为退化趋势。
[Abstract]:Net Primary Productivity NPP (NPP) is an important parameter in evaluating terrestrial ecosystem. The inversion of vegetation NPP provides an important reference for the study of global carbon cycle. Based on the data of MODIS and meteorological stations from 2000 to 2014, this paper introduces stepwise linear regression, principal component regression, partial least square regression and ridge regression analysis to construct a multivariate stepwise regression model and a principal component regression model. The partial least square regression model and the ridge regression model are evaluated. The results show that the multivariate stepwise regression model is considered to be a simple, efficient and accurate model for retrieving vegetation NPP in arid areas of northwest China, and the simulation results are strongly correlated with MOD17A3 products and measured values. (2) the distribution of annual average vegetation NPP in arid region of northwest China has obvious regional difference, the mountain area increases and the plain area decreases, showing the characteristics of high in the north and northwest, and low in the south and southeast; (3) the annual variation of NPP in the arid region of Northwest China shows a fluctuating trend, with a linear growth rate of 0.40g / (m a). Since 2000, the NPP of 58.66% regions showed an increasing trend. 13.64% of the regions remained unchanged and 27.7% showed a trend of degradation.
【作者单位】：中国科学院新疆生态与地理研究所荒漠与绿洲生态国家重点实验室;中国科学院大学;
【基金】：新疆维吾尔自治区自然科学基金(2015211A048)
【分类号】：Q948;TP79

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