Abstract:

Among the many approaches for studying the net primary productivity ( NPP ), a new method by using remote sensing was introduced in this paper. With spectral information source (the visible band, near infrared band and thermal infrared band) of NOAA-AVHRR, we can get the relative index and parameters, which can be used for estimating NPP of terrestrial vegetation. By means of remote sensing, the estimation of biomass and NPP is mainly based on the models of light energy utilization. In other words, the biomass and NPP can be calculated from the relation among NPP , absorbed photosynthetical active radiation (APAR) and the rate (ε) of transformation of APAR to organic matter, thus：NPP=(FPAR×PAR)×［ε*×σT×σE×σS×(1-Ym)×（1-Yg）］ . Based upon remote sensing (RS) and geographic information system (GIS), the NPP of terrestrial vegetation in China in every ten days was calculated, and the annual NPP was integrated. The result showed that the total NPP of terrestrial vegetation in China was 6.13×109 t C·a-1in 1990 and the maximum NPP was 1 812.9 g C/m. According to this result, the spatio-temporal distribution of NPP was analyzed. Comparing to the statistical models, the RS model, using area object other than point one, can better reflect the distribution of NPP , and match the geographic distribution of vegetation in China.

运用遥感估算中国陆地植被净第一性生产力
陈利军*  刘高焕 冯险峰
（中国科学院地理科学和资源研究所资源与环境信息系统国家重点实验室，北京100101）

摘要：净第一性生产力(NPP)研究方法很多,运用NOAA-AVHRR的可见光波段、近红外波段和热红外波段来提取和反演地面参数,进而准确估算陆地植被净第一性生产力,是一种全新的研究手段.利用遥感数据进行生物量和净第一性生产力的估算,主要是采用光能利用率模型,即通过NPP与植物吸收的光合有效辐射(APAR)和植物将所吸收的光合有效辐射转化为有机物的转化率(ε)的关系来实现的.用数学公式可表达为: NPP=(FPAR×PAR)×[ε *×σT×σE×σS×(1-Ym)×(1-Yg)]. 在遥感和地理信息系统技术的支持下,以1990年每旬的8 km分辨率的NOAA-AVHRR 1～5通道的影像为数据源,对中国每旬的陆地植被净第一性生产力进行估算,然后累加得出全年的 NPP值.估算结果:1990年中国陆地植被NPP总量为6.13×109 t C·a-1,NP P最高值为1 812.9 g C/m2.根据计算的结果,对中国大陆植被NPP的分布规律进行了分析.遥感模型能够以面代点,比较真实地反映陆地植被NPP的时空分布状况,与中国植被分布的地理规律性相符,这是其他统计模型所无法比拟的.

关键词： 遥感；植被净第一性生产力；植物吸收的光合有效辐射；光能利用率；生物量

Key words: remote sensing, net primary productivity, absorbed photosynthetical active radiation, light energy utilization, biomass