基于CASA模型的瓦屋山林场植被净初级生产力估算

在地理信息系统和遥感技术支持下,利用改进的CASA模型,并结合Landsat TM遥感影像、气象数据和林班数据,估算出瓦屋山林场2008—2009年的植被净初级生产力(PNPP),并通过实测植被生物量和生产力的关系,验证CASA模型在研究地区估算结果。结果表明:CASA模型估测植被PNPP与实测结果有较好的一致性,能够适用于瓦屋山林场植被净生产力估算;CASA模型估算结果主要植被类型年均PNPP区别明显,从高到低依次是:中国山杨、麻栎、板栗、马尾松、湿地松、灌木、杉木和池杉;瓦屋山林场植被PNPP季节变化显著,夏季贡献率最大,其次是春季和秋季,冬季最少,主要由于不同季节环境因素不同,其中又以太阳辐射最为重要。

Estimation of net primary productivity by a satellite data-driven Carnegie-Ames-Stanford Approach model in Wawu Mountain forest farm

Based on geographic information system and remote sensing technology,by use of the improved CASA(Carnegie-Ames-Stanford Approach) model,Landsat TM remote sensing image,meteorological data and compartment,the net primary productivity(PNPP) of Wawu Mountain forest farm was estimated during 2008 to 2009.By use of the relationship of forest biomass and PNPP,the results of CASA model was verified in Wawu Mountain forest farm.The results indicated that CASA model can be used to estimate vegetation PNPP well,and can be applied in Wawu Mountain forest farm vegetation net productivity estimation.The differences of the PNPP among different vegetation types were marked.According to the high and low order,the estimated PNPP of the vegetation were as follows: Populus devidiana,Quercus acutissima,Castanea mollissima,Pinus massoniana,P.elliottii,shrub,Cunninghamia lanceolata,Taxodium ascendens.The seasonal change of the PNPP in Wawu Mountain forest farm was marked.The PNPP was high in summer,and next high in spring and autumn,and lowest in winter.Mainly due to different season which has the different environmental factors,and the sun radiation is the most important factor among many factors.